Will AI replace Industrial Engineers?

Not as a job, but it is already doing parts of the work. Across the 91 official task statements scored for Industrial Engineers (United States, SOC 17-2112), 37% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 46 out of 100 (range 41–51, band: partial). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.

Which tasks in “Industrial Engineers” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Complete production reports, purchase orders, and material, tool, and equipment lists” (93/100, very high); “Prepare reports summarizing information or trends related to manufacturing performance” (93/100, very high); “Perform statistical analyses, such as social network pattern analysis, network modeling, discrete event simulation, agent-based modeling, statistical natural…” (83/100, very high). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.

Which tasks in “Industrial Engineers” stay human?

About 44% of this job's task weight sits in work that scores low for AI exposure. The lowest-scoring tasks in release 2026-q4.1 are: “Draw samples of raw materials, intermediate products, or finished products for validation testing” (0/100, minimal); “Maintain validation test equipment” (0/100, minimal); “Collect data through direct observation of work activities or witnessing the conduct of tests” (0/100, minimal). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.

What should someone working in “Industrial Engineers” do about AI?

Start from the ledger rather than the headline: 37% of this job's weighted core work is exposed, and roughly 44% is not. The practical move is to spend more of your week on the tasks that score low, the ones above, and to get fluent at directing AI through the tasks that score high, because those are the parts that change whether or not you are ready for them. This page does not predict your job, and nothing here is career advice tailored to you: the score describes the occupation, not the person.

How is the AI exposure score for Industrial Engineers calculated?

Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 91 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.

US dataswitch to UK

Industrial Engineers

collecting data through direct observation of work activities or witnessing the conduct of tests, incorporating new manufacturing methods or processes to improve existing operations and conducting research to evaluate potential solutions related to changes in equipment design. If that's your week, this page is about your job.

The honest answer

This job is splitting in two: preparing reports or presentations summarizing results or conclusions of human factors engineering or ergonomics activities is work AI now does quickly and cheaply, and collecting data through direct observation of work activities or witnessing the conduct of tests is work it can't touch.

Your move: what you can actually do about this ↓

Where the work sits, by task weight

shifting to AI: 37%
changing shape: 19%
staying human: 44%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

Whole-job exposure score 46 out of 100 (41–51 allowing for uncertainty): partial exposure, across 91 scored tasks. The number is the support for the sentence above it, not a headline about anyone’s future.

How we know this

What is measured: Every published task statement for industrial engineers is rated on five dimensions: can a model produce the output, does the work need a body in a room, does it need a legally accountable person, does it depend on a person being trusted in the moment, and how much data exists. A published formula turns those five ratings into the score; the model never writes the number.

How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.

Release: 2026-q4.1, scores computed 2026-08-04. Read the full method.

Which half fills your week decides your exposure. The ledger below shows which rows you can move toward.

Your week, as this page understands it

Design, develop, test, and evaluate integrated systems for managing industrial production processes, including human work factors, quality control, inventory control, logistics and material flow, cost analysis, and production coordination. The job title says “industrial engineers”. The real job is the part underneath: collecting data through direct observation of work activities or witnessing the conduct of tests. That is the thing someone has to be right about.

The exposed part of this job is specific, and we won’t pretend it is coming back. But industrial engineers is not one task. It is 91 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is collecting data through direct observation of work activities or witnessing the conduct of tests, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 37%
changing shape: 19%
staying human: 44%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

How we know this

How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.

Release: 2026-q4.1, scores computed 2026-08-04. Read the full method.

Your job, task by task

These are the official task statements for this occupation, in plain English, sorted by what the evidence says is happening to each one. The official wording sits under every line so you can check the rewrite against it.

6 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.

Shifting to AI

35 tasks

Tasks today’s tools can already do most of. This is the part we will not soften: where these rows are the bulk of your week, the week changes.

Studying product characteristics or customer requirements to determine validation objectives and standards
This is reading one thing and writing another: product characteristics in, a record out. That is the shape today's tools are built for.
importance 5 · Core
Source: “Study product characteristics or customer requirements to determine validation objectives and standards.” (O*NET task statement)
How this row was scored
Exposure score: 66 out of 100 (59–73 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Turning product characteristics and customer requirements into validation objectives is structured analysis of written inputs.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Analyzing validation test data to determine whether systems or processes have met validation criteria or to identify root causes of production problems
This is reading one thing and writing another: validation test data in, a record out. That is the shape today's tools are built for.
importance 5 · Core
Source: “Analyze validation test data to determine whether systems or processes have met validation criteria or to identify root causes of production problems.” (O*NET task statement)
How this row was scored
Exposure score: 66 out of 100 (62–70 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Analysing test data against criteria and hunting root causes is number work software does well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Preparing reports or presentations summarizing results or conclusions of human factors engineering or ergonomics activities
This is reading one thing and writing another: reports in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Prepare reports or presentations summarizing results or conclusions of human factors engineering or ergonomics activities, such as testing, investigation, or validation.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Turning test and investigation results into a report or presentation is well suited to current tools.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Developing validation master plans, process flow diagrams, test cases or standard operating procedures
This is reading one thing and writing another: validation master plans, process flow diagrams in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Develop validation master plans, process flow diagrams, test cases, or standard operating procedures.” (O*NET task statement)
How this row was scored
Exposure score: 66 out of 100 (62–70 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Validation plans, flow diagrams and procedures follow standard formats that current tools draft well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.

Changing shape

17 tasks

Tasks where the machine takes the producing and a person keeps the checking, the deciding, or the answering-for-it. For most jobs this is the biggest group, and it is where "transformation, not termination" is literally visible.

Recommending workplace changes to improve health and safety
The software now makes the first pass at workplace changes, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Recommend workplace changes to improve health and safety, using knowledge of potentially harmful factors, such as heavy loads or repetitive motions.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (52–60 allowing for uncertainty): partial exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Recommending safety changes draws on well documented ergonomics knowledge applied to recorded workplace data.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Assessing the user-interface or usability characteristics of products
The software now makes the first pass at the user-interface, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Assess the user-interface or usability characteristics of products.” (O*NET task statement)
How this row was scored
Exposure score: 43 out of 100 (36–50 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Usability judgements draw on documented principles, though real assessment usually needs the actual product and users.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Designing or evaluating human work systems
The software now makes the first pass at human work systems, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Design or evaluate human work systems, using human factors engineering and ergonomic principles to optimize usability, cost, quality, safety, or performance.” (O*NET task statement)
How this row was scored
Exposure score: 43 out of 100 (36–50 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Design principles are documented, but shaping a work system that fits real people needs observation on site.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.

Staying human

39 tasks

Tasks that stay with a person, because they happen in the physical world, because the rules need someone accountable, or because the value is that a specific person does them.

Collecting data through direct observation of work activities or witnessing the conduct of tests
This work happens in the physical world: data, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Collect data through direct observation of work activities or witnessing the conduct of tests.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Watching work happen or witnessing a test means being physically present while it takes place.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Conducting interviews or surveys of users or customers to collect information on topics
The value here is that a specific person handles interviews and stands behind it. That is earned, not computed.
importance 5 · Core
Source: “Conduct interviews or surveys of users or customers to collect information on topics, such as requirements, needs, fatigue, ergonomics, or interfaces.” (O*NET task statement)
How this row was scored
Exposure score: 26 out of 100 (19–33 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Surveys can be drafted and analysed easily, but getting honest answers from workers often needs a person asking.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Advocating for end users in collaboration with other professionals
The value here is that a specific person handles end users and stands behind it. That is earned, not computed.
importance 5 · Core
Source: “Advocate for end users in collaboration with other professionals, including engineers, designers, managers, or customers.” (O*NET task statement)
How this row was scored
Exposure score: 14 out of 100 (10–18 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Speaking up for users in a room full of engineers and managers depends on standing and relationships.
The five ratings: output a model can produce 1/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 3/4 · how much data exists 1/4.

Show the other 81 tasks

Completing production reports, purchase orders and material, tool and equipment lists
shifting to AI
This is reading one thing and writing another: production reports, purchase orders and material in, a record out. That is the shape today's tools are built for.
importance 3 · Core
Source: “Complete production reports, purchase orders, and material, tool, and equipment lists.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (86–100 allowing for uncertainty): very high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Filling in production reports, purchase orders and equipment lists is routine form work driven by system data.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Preparing reports summarizing information or trends related to manufacturing performance
shifting to AI
This is reading one thing and writing another: reports summarizing information in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Prepare reports summarizing information or trends related to manufacturing performance.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (86–100 allowing for uncertainty): very high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Summarising manufacturing performance data into a report is routine work that current tools do very well.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Performing statistical analyses, such as social network pattern analysis, network modeling
shifting to AI
This is reading one thing and writing another: statistical analyses in, a record out. That is the shape today's tools are built for.
importance 3 · Core
Source: “Perform statistical analyses, such as social network pattern analysis, network modeling, discrete event simulation, agent-based modeling, statistical natural language processing, computational sociology, mathematical optimization, or systems dynamics.” (O*NET task statement)
How this row was scored
Exposure score: 83 out of 100 (79–87 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Statistical modelling and simulation are heavily documented and run entirely on a computer.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Analyzing statistical data and product specifications to determine standards and establish quality and reliability objectives of finished product
shifting to AI
This is reading one thing and writing another: statistical data in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Analyze statistical data and product specifications to determine standards and establish quality and reliability objectives of finished product.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Setting quality targets from statistical data and specifications is exactly the kind of number work software does well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Recommending methods for improving utilization of personnel
shifting to AI
This is reading one thing and writing another: methods in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Recommend methods for improving utilization of personnel, material, and utilities.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Suggesting better use of staff, materials and utilities is analysis over data the company already records.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Applying statistical methods and performing mathematical calculations to determine manufacturing processes
shifting to AI
This is reading one thing and writing another: statistical methods in, a record out. That is the shape today's tools are built for.
importance 3 · Core
Source: “Apply statistical methods and perform mathematical calculations to determine manufacturing processes, staff requirements, and production standards.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Statistical and engineering calculations are exactly the kind of work software performs accurately.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Reviewing production schedules, engineering specifications, orders and related information to obtain knowledge of manufacturing methods, procedures and activities
shifting to AI
This is reading one thing and writing another: production schedules, engineering specifications, orders and related information in, a record out. That is the shape today's tools are built for.
importance 3 · Core
Source: “Review production schedules, engineering specifications, orders, and related information to obtain knowledge of manufacturing methods, procedures, and activities.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Reading schedules, specifications and orders to build up a picture is document analysis software does well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Formulating sampling procedures and designs and developing forms and instructions
shifting to AI
This is reading one thing and writing another: procedures in, a record out. That is the shape today's tools are built for.
importance 3 · Core
Source: “Formulate sampling procedures and designs and develop forms and instructions for recording, evaluating, and reporting quality and reliability data.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Sampling plans and data recording forms follow published statistical practice and standard formats.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Recording or overseeing recording of information to ensure currency of engineering drawings and documentation of production problems
shifting to AI
This is reading one thing and writing another: information in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Record or oversee recording of information to ensure currency of engineering drawings and documentation of production problems.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Keeping drawings current and logging production problems is document housekeeping software handles well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Studying operations sequence, material flow, functional statements, organization charts and project information to determine worker functions and responsibilities
shifting to AI
This is reading one thing and writing another: operations sequence, material flow, functional statements in, a record out. That is the shape today's tools are built for.
importance 3 · Core
Source: “Study operations sequence, material flow, functional statements, organization charts, and project information to determine worker functions and responsibilities.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Working out who does what from process and organisation documents is desk analysis.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Writing, reviewing or comment on documents, such as proposals, test plans or procedures
shifting to AI
This is reading one thing and writing another: comment in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Write, review, or comment on documents, such as proposals, test plans, or procedures.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Writing and commenting on proposals, test plans and procedures is document work software does strongly.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Reviewing health, safety, accident or worker compensation records to evaluate safety program effectiveness or to identify jobs with high incidence of injury
shifting to AI
This is reading one thing and writing another: health, safety in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Review health, safety, accident, or worker compensation records to evaluate safety program effectiveness or to identify jobs with high incidence of injury.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Reviewing accident and compensation records to find patterns is data analysis over existing files.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Estimating time or resource requirements for ergonomic or human factors research or development projects
shifting to AI
This is reading one thing and writing another: time in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Estimate time or resource requirements for ergonomic or human factors research or development projects.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Estimating time and resources for a project is planning arithmetic over past project records.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Designing cognitive aids, such as procedural storyboards or decision support systems
shifting to AI
This is reading one thing and writing another: cognitive aids in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Design cognitive aids, such as procedural storyboards or decision support systems.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Storyboards and decision aids are documents and screens, which current tools produce well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Applying modeling or quantitative analysis to forecast events
shifting to AI
This is reading one thing and writing another: quantitative analysis in, a record out. That is the shape today's tools are built for.
importance 3 · Core
Source: “Apply modeling or quantitative analysis to forecast events, such as human decisions or behaviors, the structure or processes of organizations, or the attitudes or actions of human groups.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Forecasting behaviour with quantitative models is computer work using established techniques.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Estimating costs, production times or staffing requirements for new designs
shifting to AI
This is reading one thing and writing another: costs, production times or staffing requirements in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Estimate costs, production times, or staffing requirements for new designs.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Estimating cost, time and staffing for a new design is calculation over past project records.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Preparing documentation for new manufacturing processes or engineering procedures
shifting to AI
This is reading one thing and writing another: documentation in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Prepare documentation for new manufacturing processes or engineering procedures.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Writing up new process documentation follows standard formats using information already gathered.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Estimating production costs
shifting to AI
This is reading one thing and writing another: production costs in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Estimate production costs, cost saving methods, and the effects of product design changes on expenditures for management review, action, and control.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Cost estimating and savings analysis runs on production and pricing data already in company systems.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Analyzing the financial impacts of sustainable manufacturing processes or sustainable product manufacturing
shifting to AI
This is reading one thing and writing another: the financial impacts of sustainable manufacturing processes in, a record out. That is the shape today's tools are built for.
importance 3 · Core
Source: “Analyze the financial impacts of sustainable manufacturing processes or sustainable product manufacturing.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Financial analysis of sustainable processes is spreadsheet work over cost and energy data.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Determining root causes of failures or recommending changes in designs
shifting to AI
This is reading one thing and writing another: root causes of failures in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Determine root causes of failures or recommend changes in designs, tolerances, or processing methods, using statistical procedures.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Root cause work using statistical methods is well documented number crunching over recorded data.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Designing tests of finished products or processing capabilities to establish standards or validate process requirements
shifting to AI
This is reading one thing and writing another: tests of finished products in, a record out. That is the shape today's tools are built for.
importance 3 · Core
Source: “Design tests of finished products or process capabilities to establish standards or validate process requirements.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Designing product and process tests follows documented statistical and industry practice.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Creating populate or maintaining databases for tracking validation activities, testing results or validated systems
shifting to AI
This is reading one thing and writing another: populate in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Create, populate, or maintain databases for tracking validation activities, test results, or validated systems.” (O*NET task statement)
How this row was scored
Exposure score: 72 out of 100 (68–76 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Building and maintaining tracking databases is standard computer work with abundant reference material.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Designing validation study features, such as sampling, testing or analytical methodologies
shifting to AI
This is reading one thing and writing another: validation study features in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Design validation study features, such as sampling, testing, or analytical methodologies.” (O*NET task statement)
How this row was scored
Exposure score: 66 out of 100 (62–70 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Designing sampling and testing approaches follows well published statistical and industry practice.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Preparing detailed reports or designing statements
shifting to AI
This is reading one thing and writing another: detailed reports in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Prepare detailed reports or design statements, based on results of validation and qualification tests or reviews of procedures and protocols.” (O*NET task statement)
How this row was scored
Exposure score: 66 out of 100 (62–70 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Writing up validation results into a formal report is document work with a clear structure.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Preparing, maintaining or reviewing validation and compliance documentation, such as engineering change notices, schematics or protocols
shifting to AI
This is reading one thing and writing another: validation in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Prepare, maintain, or review validation and compliance documentation, such as engineering change notices, schematics, or protocols.” (O*NET task statement)
How this row was scored
Exposure score: 66 out of 100 (62–70 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Preparing and reviewing change notices and protocols is structured document work.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Evaluating current or proposed manufacturing processes or practices for environmental sustainability
shifting to AI
This is reading one thing and writing another: current or proposed manufacturing processes or practices in, a record out. That is the shape today's tools are built for.
importance 3 · Core
Source: “Evaluate current or proposed manufacturing processes or practices for environmental sustainability, considering factors such as greenhouse gas emissions, air pollution, water pollution, energy use, or waste creation.” (O*NET task statement)
How this row was scored
Exposure score: 66 out of 100 (62–70 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Assessing processes against environmental criteria uses published factors and the plant's own usage data.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Recommending resolution of identified deviations from established product or processing standards
shifting to AI
This is reading one thing and writing another: resolution of identified deviations in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Recommend resolution of identified deviations from established product or process standards.” (O*NET task statement)
How this row was scored
Exposure score: 66 out of 100 (62–70 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Recommending how to fix a deviation follows documented procedures and past cases.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Scheduling deliveries based on production forecasts
shifting to AI
This is reading one thing and writing another: deliveries in, a record out. That is the shape today's tools are built for.
importance 3 · Supplemental
Source: “Schedule deliveries based on production forecasts, material substitutions, storage and handling facilities, and maintenance requirements.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (60–68 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Delivery scheduling from forecasts and lead times is routine planning work over company data.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Regulating and altering workflow schedules according to established manufacturing sequences and leading times to expedite production operations
shifting to AI
This is reading one thing and writing another: workflow schedules in, a record out. That is the shape today's tools are built for.
importance 3 · Supplemental
Source: “Regulate and alter workflow schedules according to established manufacturing sequences and lead times to expedite production operations.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (60–68 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Rescheduling work to established sequences and lead times is planning software territory.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Communicating manufacturing capabilities, production schedules or other information to facilitate production processes
shifting to AI
This is reading one thing and writing another: capabilities, production schedules or other information in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Communicate manufacturing capabilities, production schedules, or other information to facilitate production processes.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (60–68 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Passing on capability and schedule information is routine reporting drawn from company systems.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Purchasing equipment, materials or parts
shifting to AI
This is reading one thing and writing another: equipment, materials or parts in, a record out. That is the shape today's tools are built for.
importance 3 · Core
Source: “Purchase equipment, materials, or parts.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (60–68 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Purchasing equipment and parts is routine ordering work driven by specifications and supplier data.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Developing manufacturing methods, labor utilization standards and cost analysis systems to promote efficient staff and facility utilization
changing shape
The software now makes the first pass at methods, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Develop manufacturing methods, labor utilization standards, and cost analysis systems to promote efficient staff and facility utilization.” (O*NET task statement)
How this row was scored
Exposure score: 58 out of 100 (51–65 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Cost and labour standard systems can be drafted from documented practice, though the methods themselves need shop knowledge.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Drafting and designing layout of equipment
changing shape
The software now makes the first pass at layout of equipment, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Draft and design layout of equipment, materials, and workspace to illustrate maximum efficiency using drafting tools and computer.” (O*NET task statement)
How this row was scored
Exposure score: 58 out of 100 (51–65 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Layout drafting is computer work, but a good layout still leans on knowing how the floor really operates.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Establishing system operating or training requirements to ensure optimized human-machine interfaces
changing shape
The software now makes the first pass at system, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Establish system operating or training requirements to ensure optimized human-machine interfaces.” (O*NET task statement)
How this row was scored
Exposure score: 58 out of 100 (51–65 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Operating and training requirements can be drafted from documented practice, but need checking against the real system.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Analyzing complex systems to determine potential for further development
changing shape
The software now makes the first pass at complex systems, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Analyze complex systems to determine potential for further development, production, interoperability, compatibility, or usefulness in a particular area, such as aviation.” (O*NET task statement)
How this row was scored
Exposure score: 58 out of 100 (51–65 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: System analysis is desk work, though judging real interoperability needs deep experience in that field.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Reviewing product designs for manufacturability or completeness
changing shape
The software now makes the first pass at product designs, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Review product designs for manufacturability or completeness.” (O*NET task statement)
How this row was scored
Exposure score: 58 out of 100 (51–65 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Design review against manufacturability rules is document work, but the rules depend on what the plant can actually do.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Developing or implementing human performance research
changing shape
The software now makes the first pass at human performance research, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Develop or implement human performance research, investigation, or analysis protocols.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (52–60 allowing for uncertainty): partial exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Research and analysis protocols follow published methods that software can draft well.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Conducting research to evaluate potential solutions related to changes in equipment design
changing shape
The software now makes the first pass at research, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Conduct research to evaluate potential solutions related to changes in equipment design, procedures, manpower, personnel, or training.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (52–60 allowing for uncertainty): partial exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Evaluating options for equipment, staffing or training is research and analysis over documented evidence.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Preparing validation or performance qualification protocols for new or modified manufacturing processes
changing shape
The software now makes the first pass at validation, but someone has to be answerable for the result, and it cannot be the software. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Prepare validation or performance qualification protocols for new or modified manufacturing processes, systems, or equipment for production of pharmaceuticals, electronics, or other products.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (49–63 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: Protocols follow standard templates, though regulated production expects a qualified person behind them.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Investigating theoretical or conceptual issues
changing shape
The software now makes the first pass at theoretical, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 3 · Core
Source: “Investigate theoretical or conceptual issues, such as the human design considerations of lunar landers or habitats.” (O*NET task statement)
How this row was scored
Exposure score: 50 out of 100 (43–57 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch.
The rating behind it: Conceptual investigation is desk research, but genuinely new design questions still need original human thinking.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Implementing methods and procedures for disposition of discrepant material and defective or damaged parts
changing shape
The software now makes the first pass at methods, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 3 · Core
Source: “Implement methods and procedures for disposition of discrepant material and defective or damaged parts, and assess cost and responsibility.” (O*NET task statement)
How this row was scored
Exposure score: 43 out of 100 (36–50 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: The cost and responsibility analysis is desk work, though deciding what happens to scrap parts involves the floor.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Providing human factors technical expertise on topics
changing shape
The software now makes the first pass at human factors technical expertise, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Provide human factors technical expertise on topics, such as advanced user-interface technology development or the role of human users in automated or autonomous sub-systems in advanced vehicle systems.” (O*NET task statement)
How this row was scored
Exposure score: 43 out of 100 (36–50 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch.
The rating behind it: Expert opinion on interface technology can be researched, though much of the value is judgement built over years.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Developing or implementing research methodologies or statistical analysis plans to test and evaluate developmental prototypes used in new products or processes
changing shape
The software now makes the first pass at research methodologies, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Develop or implement research methodologies or statistical analysis plans to test and evaluate developmental prototypes used in new products or processes, such as cockpit designs, user workstations, or computerized human models.” (O*NET task statement)
How this row was scored
Exposure score: 43 out of 100 (36–50 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Test plans and statistics are documented, but designing prototype evaluations needs hands on the prototype.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Designing layout of equipment or workspaces to achieve maximum efficiency
changing shape
The software now makes the first pass at layout of equipment, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Design layout of equipment or workspaces to achieve maximum efficiency.” (O*NET task statement)
How this row was scored
Exposure score: 43 out of 100 (36–50 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Layouts can be drawn and optimised automatically, though the measurements come from the workspace itself.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Investigating or resolving operational problems
changing shape
The software now makes the first pass at operational problems, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Investigate or resolve operational problems, such as material use variances or bottlenecks.” (O*NET task statement)
How this row was scored
Exposure score: 43 out of 100 (36–50 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Variance and bottleneck analysis runs on production data, though confirming the cause often means going to look.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Planning and establishing sequence of operations to fabricate and assembling parts or products and to promote efficient utilization
staying human
The ratings behind this row put sequence of operations well outside what today's tools can do on their own.
importance 4 · Core
Source: “Plan and establish sequence of operations to fabricate and assemble parts or products and to promote efficient utilization.” (O*NET task statement)
How this row was scored
Exposure score: 38 out of 100 (31–45 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch.
The rating behind it: Operation sequences can be drafted from process data, but getting them right depends on how the actual shop floor runs.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Resolving testing problems by modifying testing methods or revising test objectives and standards
staying human
The ratings behind this row put problems well outside what today's tools can do on their own.
importance 4 · Core
Source: “Resolve testing problems by modifying testing methods or revising test objectives and standards.” (O*NET task statement)
How this row was scored
Exposure score: 38 out of 100 (31–45 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Method changes can be drafted, but working out why a test keeps failing often needs hands on the rig.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Troubleshooting new or existing product problems involving designs
staying human
The ratings behind this row put new or existing product problems involving designs well outside what today's tools can do on their own.
importance 4 · Core
Source: “Troubleshoot new or existing product problems involving designs, materials, or processes.” (O*NET task statement)
How this row was scored
Exposure score: 38 out of 100 (31–45 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch.
The rating behind it: Design and materials problems can be reasoned about, but shop-floor causes usually show up only at the machine.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Redesigning packaging for manufactured products to minimize raw material use or waste
staying human
The ratings behind this row put manufactured products well outside what today's tools can do on their own.
importance 3 · Supplemental
Source: “Redesign packaging for manufactured products to minimize raw material use or waste.” (O*NET task statement)
How this row was scored
Exposure score: 38 out of 100 (31–45 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch.
The rating behind it: Packaging redesign can be explored on a computer, but real material savings get proved on the line.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Identifying opportunities or implementing changes to improve manufacturing processes or products or to reduce costs
staying human
The ratings behind this row put opportunities well outside what today's tools can do on their own.
importance 4 · Core
Source: “Identify opportunities or implement changes to improve manufacturing processes or products or to reduce costs, using knowledge of fabrication processes, tooling and production equipment, assembly methods, quality control standards, or product design, materials and parts.” (O*NET task statement)
How this row was scored
Exposure score: 38 out of 100 (31–45 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch.
The rating behind it: Improvement ideas can be generated from data, but knowing which will actually work depends on the specific plant.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Applying continuous improvement methods, such as lean manufacturing, to enhance manufacturing quality, reliability or cost-effectiveness
staying human
The ratings behind this row put continuous improvement methods well outside what today's tools can do on their own.
importance 4 · Core
Source: “Apply continuous improvement methods, such as lean manufacturing, to enhance manufacturing quality, reliability, or cost-effectiveness.” (O*NET task statement)
How this row was scored
Exposure score: 37 out of 100 (30–44 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Lean methods are extremely well documented, but improvement work happens with the teams doing the job.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Providing technical expertise or supporting related to manufacturing
staying human
The ratings behind this row put technical expertise well outside what today's tools can do on their own.
importance 4 · Core
Source: “Provide technical expertise or support related to manufacturing.” (O*NET task statement)
How this row was scored
Exposure score: 37 out of 100 (30–44 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Documented manufacturing knowledge goes a long way, though support often means being available at the plant.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Coordinating and implementing quality control objectives
staying human
The ratings behind this row put quality control objectives well outside what today's tools can do on their own.
importance 3 · Core
Source: “Coordinate and implement quality control objectives, activities, or procedures to resolve production problems, maximize product reliability, or minimize costs.” (O*NET task statement)
How this row was scored
Exposure score: 37 out of 100 (30–44 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Quality procedures are easy to draft, but making them stick on a running production line needs people there.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Communicating with management and user personnel to develop production and design standards
staying human
The value here is that a specific person handles management and stands behind it. That is earned, not computed.
importance 4 · Core
Source: “Communicate with management and user personnel to develop production and design standards.” (O*NET task statement)
How this row was scored
Exposure score: 35 out of 100 (28–42 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Standards can be drafted quickly, but agreeing them with managers and the people who use them takes discussion.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Coordinating the implementation or scheduling of validation testing with affected departments and personnel
staying human
The value here is that a specific person handles the implementation and stands behind it. That is earned, not computed.
importance 4 · Core
Source: “Coordinate the implementation or scheduling of validation testing with affected departments and personnel.” (O*NET task statement)
How this row was scored
Exposure score: 35 out of 100 (28–42 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Scheduling can be drafted, but lining up several departments takes live negotiation.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Conducting audits of validation or performance qualification processes to ensure compliance with internal or regulatory requirements
staying human
The rules require a named, qualified person to answer for audits of validation, and that person cannot be a piece of software.
importance 4 · Core
Source: “Conduct audits of validation or performance qualification processes to ensure compliance with internal or regulatory requirements.” (O*NET task statement)
How this row was scored
Exposure score: 32 out of 100 (25–39 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: Audit evidence is documentary, though auditors are expected to be qualified people who go and look.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Training users in task techniques or ergonomic principles
staying human
The value here is that a specific person handles users and stands behind it. That is earned, not computed.
importance 4 · Core
Source: “Train users in task techniques or ergonomic principles.” (O*NET task statement)
How this row was scored
Exposure score: 30 out of 100 (23–37 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Training material is easy to produce, but people usually learn task techniques from someone showing them.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Assisting in training equipment operators or other staff on validation protocols and standard operating procedures
staying human
The value here is that a specific person handles training equipment operators and stands behind it. That is earned, not computed.
importance 3 · Core
Source: “Assist in training equipment operators or other staff on validation protocols and standard operating procedures.” (O*NET task statement)
How this row was scored
Exposure score: 30 out of 100 (23–37 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Training material is easy to produce, but operators generally learn procedures from a person on the floor.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Communicating with regulatory agencies regarding compliance documentation or validation results
staying human
The rules require a named, qualified person to answer for regulatory agencies regarding compliance documentation, and that person cannot be a piece of software.
importance 4 · Core
Source: “Communicate with regulatory agencies regarding compliance documentation or validation results.” (O*NET task statement)
How this row was scored
Exposure score: 30 out of 100 (23–37 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; someone qualified has to answer for it; the value is that a specific person does it.
The rating behind it: Submissions can be drafted, but a regulator deals with a named responsible person at the company.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Participating in internal or external training programs to maintain knowledge of validation principles
staying human
The ratings behind this row put internal or external training programs well outside what today's tools can do on their own.
importance 3 · Core
Source: “Participate in internal or external training programs to maintain knowledge of validation principles, industry trends, or novel technologies.” (O*NET task statement)
How this row was scored
Exposure score: 26 out of 100 (19–33 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over.
The rating behind it: Keeping your own knowledge current is something a person has to do for themselves.
The five ratings: output a model can produce 1/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Reading current literature, talk with colleagues, participate in educational programs
staying human
The ratings behind this row put current literature, talk well outside what today's tools can do on their own.
importance 3 · Core
Source: “Read current literature, talk with colleagues, participate in educational programs, attend meetings or workshops, or participate in professional organizations or conferences to keep abreast of developments in the manufacturing field.” (O*NET task statement)
How this row was scored
Exposure score: 26 out of 100 (19–33 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over.
The rating behind it: Keeping up with the field through reading, colleagues and conferences is something a person does for themselves.
The five ratings: output a model can produce 1/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Evaluating precision and accuracy of production and testing equipment and engineering drawings to formulate corrective action plan
staying human
This work happens in the physical world: precision, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Evaluate precision and accuracy of production and testing equipment and engineering drawings to formulate corrective action plan.” (O*NET task statement)
How this row was scored
Exposure score: 25 out of 100 (18–32 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Judging whether equipment is accurate means checking the machines themselves, even though the action plan is paperwork.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Performing functional, task or anthropometric analysis, using tools, such as checklists, surveys, videotaping or force measurement
staying human
This work happens in the physical world: functional, task or anthropometric analysis, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Perform functional, task, or anthropometric analysis, using tools, such as checklists, surveys, videotaping, or force measurement.” (O*NET task statement)
How this row was scored
Exposure score: 25 out of 100 (18–32 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Some measurement can be analysed from video, but force and body measurements are taken on the person at work.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Developing sustainable manufacturing technologies to reduce greenhouse gas emissions
staying human
The ratings behind this row put sustainable manufacturing technologies well outside what today's tools can do on their own.
importance 3 · Core
Source: “Develop sustainable manufacturing technologies to reduce greenhouse gas emissions, minimize raw material use, replace toxic materials with non-toxic materials, replace non-renewable materials with renewable materials, or reduce waste.” (O*NET task statement)
How this row was scored
Exposure score: 24 out of 100 (17–31 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the five ratings behind the score, with no single dominant reason.
The rating behind it: Developing genuinely new sustainable manufacturing technology is original engineering work, not something drawn from existing text.
The five ratings: output a model can produce 1/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Training production personnel in new or existing methods
staying human
This work happens in the physical world: production personnel, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Train production personnel in new or existing methods.” (O*NET task statement)
How this row was scored
Exposure score: 18 out of 100 (11–25 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Training materials are easy to produce, but production staff learn new methods at the machine with a person.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Conferring with clients, vendors, staff and management personnel regarding purchases
staying human
The value here is that a specific person handles clients, vendors, staff and management personnel regarding purchases and stands behind it. That is earned, not computed.
importance 4 · Core
Source: “Confer with clients, vendors, staff, and management personnel regarding purchases, product and production specifications, manufacturing capabilities, or project status.” (O*NET task statement)
How this row was scored
Exposure score: 18 out of 100 (14–22 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Working through specifications and project status with clients and vendors runs on live back-and-forth between people.
The five ratings: output a model can produce 1/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 3/4 · how much data exists 2/4.
Integrating human factors requirements into operational hardware
staying human
This work happens in the physical world: human factors requirements, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Integrate human factors requirements into operational hardware.” (O*NET task statement)
How this row was scored
Exposure score: 16 out of 100 (12–20 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Building human factors requirements into physical hardware means working with the equipment itself.
The five ratings: output a model can produce 1/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Directing validation activities, such as protocol creation or testing
staying human
The rules require a named, qualified person to answer for validation activities, and that person cannot be a piece of software.
importance 4 · Core
Source: “Direct validation activities, such as protocol creation or testing.” (O*NET task statement)
How this row was scored
Exposure score: 16 out of 100 (9–23 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; someone qualified has to answer for it; the value is that a specific person does it.
The rating behind it: Directing validation work means allocating and answering for people, which needs a responsible person.
The five ratings: output a model can produce 1/4 · needs a body in a room 1/4 · needs an accountable person 2/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Devising automated lab validation test stations or other test fixtures or equipment
staying human
This work happens in the physical world: automated lab validation test stations, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Devise automated lab validation test stations or other test fixtures or equipment.” (O*NET task statement)
How this row was scored
Exposure score: 16 out of 100 (12–20 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Building test stations and fixtures means physically making and wiring equipment.
The five ratings: output a model can produce 1/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Incorporating new manufacturing methods or processes to improve existing operations
staying human
This work happens in the physical world: new manufacturing methods, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Incorporate new manufacturing methods or processes to improve existing operations.” (O*NET task statement)
How this row was scored
Exposure score: 14 out of 100 (10–18 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Bringing a new process into a running operation means changing equipment and working practices in place.
The five ratings: output a model can produce 1/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Supervising technicians, technologists, analysts, administrative staff or other engineers
staying human
The value here is that a specific person handles technicians, technologists, analysts, administrative staff or other engineers and stands behind it. That is earned, not computed.
importance 4 · Core
Source: “Supervise technicians, technologists, analysts, administrative staff, or other engineers.” (O*NET task statement)
How this row was scored
Exposure score: 10 out of 100 (6–14 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Supervising a team rests on authority and trust with those particular people.
The five ratings: output a model can produce 1/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 3/4 · how much data exists 1/4.
Conducting validation or qualification tests of new or existing processes
staying human
This work happens in the physical world: validation, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Conduct validation or qualification tests of new or existing processes, equipment, or software in accordance with internal protocols or external standards.” (O*NET task statement)
How this row was scored
Exposure score: 8 out of 100 (4–12 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; someone qualified has to answer for it.
The rating behind it: Running validation tests means operating the actual equipment and process.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Designing, installing or troubleshooting manufacturing equipment
staying human
This work happens in the physical world: equipment, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Design, install, or troubleshoot manufacturing equipment.” (O*NET task statement)
How this row was scored
Exposure score: 8 out of 100 (4–12 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Installing and troubleshooting production equipment means hands on the machines.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Evaluating manufactured products according to specifications and quality standards
staying human
This work happens in the physical world: manufactured products, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Evaluate manufactured products according to specifications and quality standards.” (O*NET task statement)
How this row was scored
Exposure score: 8 out of 100 (4–12 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Judging finished products against specification usually means examining the actual items.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Validating or characterizing sustainable or environmentally friendly products
staying human
This work happens in the physical world: sustainable, in a real place. Software cannot follow it there.
importance 3 · Core
Source: “Validate or characterize sustainable or environmentally friendly products, using electronic testing platforms.” (O*NET task statement)
How this row was scored
Exposure score: 7 out of 100 (3–11 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Characterising products on test platforms means operating the equipment and handling the samples.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Directing workers engaged in product measurement
staying human
This work happens in the physical world: workers, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Direct workers engaged in product measurement, inspection, and testing activities to ensure quality control and reliability.” (O*NET task statement)
How this row was scored
Exposure score: 6 out of 100 (2–10 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Directing inspection and testing means being where the measuring is done.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Providing technical support to clients through activities
staying human
This work happens in the physical world: technical support, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Provide technical support to clients through activities, such as rearranging workplace fixtures to reduce physical hazards or discomfort or modifying task sequences to reduce cycle time.” (O*NET task statement)
How this row was scored
Exposure score: 6 out of 100 (2–10 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Moving fixtures and adjusting someone's workstation is hands-on help at their workplace.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Operating testing equipment, such as heat stress meters, octave band analyzers
staying human
This work happens in the physical world: equipment, in a real place. Software cannot follow it there.
importance 3 · Core
Source: “Operate testing equipment, such as heat stress meters, octave band analyzers, motion analysis equipment, inclinometers, light meters, thermoanemometers, sling psychrometers, or colorimetric detection tubes.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Using meters and analysers means physically operating the instruments where the readings are taken.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Inspecting work sites to identify physical hazards
staying human
This work happens in the physical world: work sites, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Inspect work sites to identify physical hazards.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Spotting physical hazards means walking the actual workplace.
The five ratings: output a model can produce 1/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Maintaining validation test equipment
staying human
This work happens in the physical world: validation test equipment, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Maintain validation test equipment.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Keeping test equipment working means physically servicing it.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Drawing samples of raw materials
staying human
This work happens in the physical world: samples of raw materials, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Draw samples of raw materials, intermediate products, or finished products for validation testing.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Drawing physical samples of material or product is done by hand in the plant.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.

What this job pays, and how many people do it

Median pay: $102,440a year, the middle of the range, so half earn more and half earn less.bls-oews, 2025 · May 2025 estimates (national_M2025_dl.xlsx)
How we know this
Source: bls-oews
Reference period: May 2025 estimates (national_M2025_dl.xlsx)
Rounding: Shown as published.
People doing this job: 365,740in the US, 2025.bls-oews · May 2025 estimates (national_M2025_dl.xlsx)

What is deliberately not here: a forecast of how many of these jobs exist in ten years. Where an official projection exists for a market we publish it with its vintage; where it does not, we leave the space empty rather than borrow the other country’s number.

Why this is shifting

The reason is boringly specific. Most of what is shifting here is reading one thing and writing another: product characteristics in, a record out. The rows above are exactly that shape: preparing reports or presentations summarizing results or conclusions of human factors engineering or ergonomics activities and studying product characteristics or customer requirements to determine validation objectives and standards. What it cannot do is be there in the room, and that is still where data gets done. Which is why this page talks about your tasks changing, not your job ending.

Your move

Over a pint: what I’d tell you if you were my friend

Your week is splitting in two, and which half fills it is the whole question. Preparing reports or presentations summarizing results or conclusions of human factors engineering or ergonomics activities is going; collecting data through direct observation of work activities or witnessing the conduct of tests is not.

So, given all that: 37% of this job's task weight sits in rows the software is already learning, 19% in rows that change shape rather than disappear, and 44% in rows it is nowhere near. That is the position, measured across 91 scored tasks. It is not a forecast about you.

The occupation is an average and you are not, so the first job below is finding out where your own week actually sits.

This week: one thing

Print the task ledger above and put your own hours next to each row. Roughly, in pen, in one sitting. Then look at which group your hours actually pile up in. Twenty minutes, this week.

What you end up holding: your own week, on one page, sorted into what is shifting and what is not
How long it takes: about twenty minutes

If printing it isn’t practical: Read the rows off this page and write the same list on the back of an envelope. Same twenty minutes, same page, and it works just as well said out loud to someone who knows the job. The point is your hours next to the rows, not the paper it is on.

Over the next 90 days

Volunteer toward the durable end, visibly. Over the next ninety days put your hand up for the work in the bottom group (collecting data through direct observation of work activities or witnessing the conduct of tests) and let people see you doing it. Not a new project: the same job, with your mix deliberately tilted. The point is that when the rota or the reorganisation comes, the version of you people picture is the one doing the part that stays.

Over the next 12 months

Claim a specialism at the durable end and let the other end go. Over a year, deliberately become the person who handles collecting data through direct observation of work activities or witnessing the conduct of tests, and deliberately stop being the first choice for the rows in the top group. That trade costs something, because the exposed work is often the comfortable work. Decide it on purpose rather than by drift. Before you pay for anything, use CareerOneStop - Find local training. It is free, it is the Labor Department's own service, and it is listed below with the rest of the free routes.

The roads out of here, and why I am not sending you down them

I looked at the obvious moves out of this job, and here is what I found.

I checked the 12 nearest US occupations to industrial engineers (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was life, physical, and social science technicians, all other: only about 3% of its durable work is work you already do, it pays 39.2% less and there are far fewer of those jobs than of yours. Your own job splits about 37/63: that share of the list sits in the top exposure band and the rest does not. On this evidence the honest move is inside the job rather than out of it. Become the person who owns “collect data through direct observation of work activities or witnessing the conduct…”, and let the exposed end go.

How that was checked: this job was compared against all 830 US occupations in this release on their official task statements, and the 12 nearest were examined one by one. A move that turns on an industry, an employer or a qualification rather than on the work itself will not show up in a check like that. And this release carries no licence register, so anything you are weighing needs that looked up separately.

3 moves I checked and rejected

These are the obvious-looking jumps. They are here with their reasons rather than quietly dropped, because the ones that fail are worth knowing about. It is one less thing to turn over at night.

Life, Physical, and Social Science Technicians, All Other
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already design, install, or troubleshoot manufacturing equipment, and their equivalent is to identify and troubleshoot equipment problems. Across both published task lists that is about 3% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 3% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $62,280 against your $102,440, 39.2% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice. And it is a narrow door: about 73,910 of those jobs against 365,740 of yours (OEWS May 2025), 20% as many seats.
Look at that job’s page anyway →
Chemical Engineers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already design, install, or troubleshoot manufacturing equipment, and their equivalent is to troubleshoot problems with chemical manufacturing processes. Across both published task lists that is about 2% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 2% of the durable side of that job. That is a different job, not a next step. And it is a narrow door: about 21,070 of those jobs against 365,740 of yours (OEWS May 2025), 6% as many seats.
Look at that job’s page anyway →
Mechanical Engineers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already design validation study features, and their equivalent is to develop calibration methodologies, test methodologies, or tools. Across both published task lists that is about 2% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 2% of the durable side of that job. That is a different job, not a next step.
Look at that job’s page anyway →

What I’d stop worrying about

A friend tells you what not to spend fear on. This is that list.

The headline number you read somewhere
The big “X% of jobs” figures are about the whole economy, not about you. The number that describes your job is on this page: 37% of its task weight, across 91 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
The whole-job doom story
Nothing on this page says this job ends. It says the mix inside it moves. Half the rows above are unchanged or changing shape, and the plan is about which half your week sits in. That is a very different problem, and a solvable one.
Panic-buying a course
Do the twenty-minute sorting exercise first. Most people who buy a course before they have done it buy the wrong one, and the free services listed below will tell you the same thing without charging for it.
The “obvious” next job everyone suggests
I checked the obvious moves and most of them did not survive. The reasons are printed with the routes above, including the pay and the gate. A move that fails on the numbers is worth knowing about so you can stop turning it over at night.

You are reading the United States figures

The United Kingdom splits this work across more than one official group, of which Production and process engineers is the closest. The pay and employment figures are not directly comparable, and we do not average them together.

Switch to the United Kingdom page →partial match

The other groups this work is counted across:

Engineering project managers and project engineers

In UK official statistics this job is counted as Production and process engineers and Engineering project managers and project engineers. Pay is shown separately for each of those groups (medians cannot be averaged together), while the task list and the scores on this page are for this group only.

Your route through this

Where to go next, and what it costs

Free, and complete

The moves above cost nothing. These are the real services that go with them: public, government-funded, and free at the point of use. Nothing on this page is behind an email address or a payment.

Anywhere in the US:
CareerOneStop - Find local training
Search what's running near you, from the Labor Department's own database, before anyone sells you a course.
Free to search; individual programs vary, and some are funded
Anywhere in the US:
American Job Center locator
An American Job Center will sit down with you for free. Find yours by ZIP code.
Free
- CareerOneStop local help hub
Anywhere in the US:
CareerOneStop - Licensed occupations finder
Check what your state actually requires before you pay for anything.
Free
Anywhere in the US:
CareerOneStop
Free

No Space for this job, but one for what is happening to it

Nothing Collab365 runs is built for industrial engineers, and we are not going to point you at the nearest one and call it a fit.

There is one that is not about a job title at all. The AI Authority is about being the person who directs these tools at work rather than the person they get compared to. That is worth saying here, because 37% of the work on this page is already inside what they can do.

Try The AI Authority free →

7 days free, no card needed. Explore up to 2 Spaces before you choose a plan: you pick a plan later, not now.

The AI Authority is a general community about working with AI, not a course for industrial engineers. You do not need it to act on anything here: the moves above cost nothing and stand on their own. The data on this page is the same either way.

Noted, and thank you. We’ll email you if a Space for industrial engineers launches. Nothing else.

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Questions people ask about this job

Will AI replace Industrial Engineers?: Not as a job, but it is already doing parts of the work. Across the 91 official task statements scored for Industrial Engineers (United States, SOC 17-2112), 37% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 46 out of 100 (range 41–51, band: partial). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.
Which tasks in “Industrial Engineers” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Complete production reports, purchase orders, and material, tool, and equipment lists” (93/100, very high); “Prepare reports summarizing information or trends related to manufacturing performance” (93/100, very high); “Perform statistical analyses, such as social network pattern analysis, network modeling, discrete event simulation, agent-based modeling, statistical natural…” (83/100, very high). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.
Which tasks in “Industrial Engineers” stay human?: About 44% of this job's task weight sits in work that scores low for AI exposure. The lowest-scoring tasks in release 2026-q4.1 are: “Draw samples of raw materials, intermediate products, or finished products for validation testing” (0/100, minimal); “Maintain validation test equipment” (0/100, minimal); “Collect data through direct observation of work activities or witnessing the conduct of tests” (0/100, minimal). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.
What should someone working in “Industrial Engineers” do about AI?: Start from the ledger rather than the headline: 37% of this job's weighted core work is exposed, and roughly 44% is not. The practical move is to spend more of your week on the tasks that score low, the ones above, and to get fluent at directing AI through the tasks that score high, because those are the parts that change whether or not you are ready for them. This page does not predict your job, and nothing here is career advice tailored to you: the score describes the occupation, not the person.
How is the AI exposure score for Industrial Engineers calculated?: Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 91 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.

Where these numbers come from

Worth knowing about these figures

The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
6 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.

Task statements: onet-dbProcessing: catalogue-bridge → onet-im-rt-weighting → task-scoring → score-aggregation
Task weights: onet-db (im-rt)
Scores: Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-04.
Pay and employment: bls-oews (May 2025 estimates (national_M2025_dl.xlsx))bls-oews (May 2025 estimates (national_M2025_dl.xlsx))

Figures on this page come from release 2026-q4.1, published 2026-08-05. Every release keeps its own permanent address, so a figure you cite in March is still there, unchanged, in November.

The plain-English wording on this page is assembled directly from the task statements and the published ratings, not written by hand for this occupation. That is why it is specific, and it is also why we say so.

The routes and free resources further up are today’s, not the release’s (last reviewed 2026-08-05). A route is an offer, not a historical fact, so it moves on its own clock.

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Everything on this site is published under CC BY 4.0. Quote it, chart it, sell something built on it. Just say where it came from, and cite the dated release rather than the site, so the figure you quote stays checkable.

Plain text

Collab365 (2026). Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1 (methodVersion 2.0.0, promptVersion task_scoring_v1.0). https://futureproof.collab365.com/data/2026-q4.1. Licensed CC BY 4.0. Built with O*NET data (USDOL/ETA, CC BY 4.0); ONS data (Open Government Licence v3.0); GAISI task framework (arXiv:2507.22748, MIT); BLS data (public domain).

BibTeX

@misc{collab365futureproof2026q41,
  title        = {Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1},
  author       = {{Collab365}},
  year         = {2026},
  url          = {https://futureproof.collab365.com/data/2026-q4.1},
  note         = {Release 2026-q4.1, methodVersion 2.0.0, promptVersion task_scoring_v1.0, CC BY 4.0}
}

Permalink

https://futureproof.collab365.com/data/2026-q4.1

Data as of release 2026-q4.1, published 2026-08-05. Releases never change after publication; when the figures move, a new dated release is published beside this one and this one stays exactly where it is.