Will AI replace automation engineers?
Updated
Industrial engineers score 55 of 100 for AI exposure. The largest share of their task time, 79%, is work AI speeds up while they stay in charge. AI can take over 16% outright, and 5% stays with people.
- 16% AI can do it
- 79% AI helps
- 5% Needs a person
High exposure
Higher than 85% of the 923 occupations we scored.
Task by task
We graded 20 tasks, listed here from most to least exposed. AI can do 3 of them today, speeds up 16 and leaves 1 to people.
| Task | AI exposure |
|---|---|
| Complete production reports, purchase orders, and material, tool, and equipment lists. Production reports and purchase and equipment lists are routine documents AI generates. | 75% AI can do it |
| Record or oversee recording of information to ensure currency of engineering drawings and documentation of production problems. Routine documentation updates from logs and reports are highly automatable. | 65% AI can do it |
| Apply statistical methods and perform mathematical calculations to determine manufacturing processes, staff requirements, and production standards. Statistical calculations and standards math are well suited to software and AI. | 65% AI can do it |
| Review production schedules, engineering specifications, orders, and related information to obtain knowledge of manufacturing methods, procedures, and activities. AI can summarize schedules and specifications; engineer builds process knowledge. | 60% AI helps |
| Formulate sampling procedures and designs and develop forms and instructions for recording, evaluating, and reporting quality and reliability data. AI drafts sampling plans and recording forms; engineer validates statistical design. | 60% AI helps |
| Estimate production costs, cost saving methods, and the effects of product design changes on expenditures for management review, action, and control. AI can build cost models and compare design scenarios; engineer validates assumptions. | 55% AI helps |
| Schedule deliveries based on production forecasts, material substitutions, storage and handling facilities, and maintenance requirements. AI can build delivery schedules from forecasts; planner confirms constraints. | 55% AI helps |
| Analyze statistical data and product specifications to determine standards and establish quality and reliability objectives of finished product. AI analyzes quality data and suggests targets; engineer sets objectives. | 50% AI helps |
| Draft and design layout of equipment, materials, and workspace to illustrate maximum efficiency using drafting tools and computer. AI and CAD tools generate layout options; engineer selects and verifies. | 50% AI helps |
| Regulate and alter workflow schedules according to established manufacturing sequences and lead times to expedite production operations. Scheduling tools adjust sequences; engineer handles floor disruptions and tradeoffs. | 50% AI helps |
Show the other 10 tasks
| Task | AI exposure |
|---|---|
| Plan and establish sequence of operations to fabricate and assemble parts or products and to promote efficient utilization. AI drafts operation sequences; engineer approves routings and floor constraints. | 45% AI helps |
| Develop manufacturing methods, labor utilization standards, and cost analysis systems to promote efficient staff and facility utilization. AI can draft labor standards and cost systems; engineer designs and validates. | 45% AI helps |
| Study operations sequence, material flow, functional statements, organization charts, and project information to determine worker functions and responsibilities. AI can map material flow and org data; engineer defines worker roles. | 45% AI helps |
| Recommend methods for improving utilization of personnel, material, and utilities. AI can analyze utilization data and propose improvements for review. | 40% AI helps |
| Coordinate and implement quality control objectives, activities, or procedures to resolve production problems, maximize product reliability, or minimize costs. QC coordination involves people and floor decisions; AI assists analysis. | 35% AI helps |
| Communicate with management and user personnel to develop production and design standards. Standards come from live discussion with stakeholders; AI helps with drafts. | 30% AI helps |
| Evaluate precision and accuracy of production and testing equipment and engineering drawings to formulate corrective action plan. Equipment accuracy checks need physical measurement; AI aids drawing review. | 30% AI helps |
| Implement methods and procedures for disposition of discrepant material and defective or damaged parts, and assess cost and responsibility. AI can assess cost and responsibility; physical disposition needs people. | 30% AI helps |
| Confer with clients, vendors, staff, and management personnel regarding purchases, product and production specifications, manufacturing capabilities, or project status. Live conversations need people; AI helps only with prep and follow-up. | 25% AI helps |
| Direct workers engaged in product measurement, inspection, and testing activities to ensure quality control and reliability. Directing inspectors and testers is supervisory work on the shop floor. | 15% Needs a person |
How industrial engineers compare
All occupations (923)
Architecture and engineering (56)
Pay and outlook in the US
- Median pay
- $102,440 a year, May 2025
- People employed
- 365,740 in the US, May 2025
- Projected change in jobs
- +12.4% from 2024 to 2034
Skills to build
- Validate AI-drafted sampling plans in MATLAB
- Audit AI cost models against SAP cost records
- Hold the Certified Quality Engineer credential
- Lead disposition of defective and discrepant parts
- Write production schedules in Microsoft Project
- Pull production data with SQL queries
Safer roles nearby
5 related occupations with lower scores.
Questions about industrial engineers and AI
Will automation engineers be replaced by AI?
Partly. About 5 in 10 working hours go to tasks AI can already do, mostly completing production reports and purchase orders, and keeping engineering drawings and problem logs current. What stays with people is the floor work, setting standards with stakeholders, judging equipment accuracy, and deciding how defective parts are disposed of.
Which industrial engineer tasks is AI taking over?
Paperwork and calculations go first. Completing production reports, purchase orders, and equipment lists scores 75 on exposure, because AI fills them from fixed fields. Statistical methods for production standards and staffing score 65, since the math is routine for software.
Which industrial engineer tasks stay human?
Shop floor supervision stays with people. Directing inspectors and testers scores 15 on exposure, the lowest in the job, because it means leading hands-on work on the floor. Live talks with clients, vendors, and management score 25, and checking production equipment precision scores 30 because it takes physical measurement with gauges on the machine.
How can industrial engineers stay valuable?
Take responsibility for the decisions that happen on the floor. Validate AI-drafted sampling plans with your statistical design in MATLAB before they reach quality control. Test AI cost models against actual SAP cost records before management review. Lead the disposition of defective parts and the stakeholder meetings that set production standards.
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