AI in manufacturing: which tasks to automate first
Updated
Across the 13 million US jobs in manufacturing, the work scores 35 of 100 for AI exposure, weighted by how many people do each job. AI can take on about 621 hours a year per full-time person, 31% of a working year. The task that frees the most hours across the industry is to read work orders or receive oral instructions, about 106 hours a year for each person who does it.
- AI exposure, weighted by employment
- 35 out of 100 Moderate exposure
- Hours AI can take on
- 621 hours a year per full-time person
- Task time AI can do today
- 13% AI speeds up another 43%
Tasks to automate first
The 15 tasks where AI can take on the most hours across manufacturing: how exposed each task is, how much of the job it takes and how many people do that job. Hours are per person in the role that does the task. How we score each task.
| Task and who does it | AI exposure |
|---|---|
| Read work orders or receive oral instructions to determine work assignments or material or equipment needs. AI reads written orders; oral instructions still need a person. Done by warehouse workers. | 40% AI helps 106 hours a year for each person in the role |
| Keep records of employees' attendance and hours worked. Timekeeping systems already record attendance and hours digitally. Done by production supervisors. | 72% AI can do it 77 hours a year for each person in the role |
| Maintain operations data, such as time, production, and cost records, and prepare management reports of production results. Production and cost records and standard management reports are routine digital work. Done by production supervisors. | 75% AI can do it 72 hours a year for each person in the role |
| Calculate labor and equipment requirements and production specifications, using standard formulas. Standard formulas for labor and equipment needs are easily computed by software. Done by production supervisors. | 72% AI can do it 71 hours a year for each person in the role |
| Prepare documents, such as work orders, bills of lading, or shipping orders, to route materials. Bills of lading and shipping orders are routine, template-driven documents. Done by shipping clerks. | 72% AI can do it 141 hours a year for each person in the role |
| Read and analyze charts, work orders, production schedules, and other records and reports to determine production requirements and to evaluate current production estimates and outputs. AI can read and summarize schedules and reports; supervisor validates. Done by production supervisors. | 60% AI helps 64 hours a year for each person in the role |
| Compute amounts, such as space available, shipping, storage, or demurrage charges, using computer or price list. Charge and space calculations are arithmetic against rate tables. Done by shipping clerks. | 75% AI can do it 136 hours a year for each person in the role |
| Record shipment data, such as weight, charges, space availability, damages, or discrepancies, for reporting, accounting, or recordkeeping purposes. Logging weights, charges and discrepancies is mostly structured data entry. Done by shipping clerks. | 65% AI can do it 125 hours a year for each person in the role |
| Plan and establish work schedules, assignments, and production sequences to meet production goals. Scheduling tools optimize sequences; supervisor sets priorities and assignments. Done by production supervisors. | 55% AI helps 58 hours a year for each person in the role |
| Record numbers of units handled or moved, using daily production sheets or work tickets. Counts are physical, but logging them can be digitized. Done by warehouse workers. | 55% AI helps 71 hours a year for each person in the role |
| Record inspection or test data, such as weights, temperatures, grades, or moisture content, and quantities inspected or graded. Recording instrument readings into structured records is easily automated. Done by quality inspectors. | 85% AI can do it 74 hours a year for each person in the role |
| Requisition materials, supplies, equipment parts, or repair services. Requisition forms and reorder systems are digital; approvals stay with supervisor. Done by production supervisors. | 60% AI helps 56 hours a year for each person in the role |
| Determine shipping methods, routes, or rates for materials to be shipped. Transport management software already selects methods, routes and rates. Done by shipping clerks. | 60% AI can do it 110 hours a year for each person in the role |
| Interpret specifications, blueprints, job orders, and company policies and procedures for workers. AI can explain blueprints and policies; delivery to workers stays human. Done by production supervisors. | 50% AI helps 51 hours a year for each person in the role |
| Review financial statements, sales or activity reports, or other performance data to measure productivity or goal achievement or to identify areas needing cost reduction or program improvement. AI can summarize and flag performance data; manager decides actions. Done by general managers. | 58% AI helps 99 hours a year for each person in the role |
What stays with people
44% of the task time across these roles needs a person, and the output of the rest still needs someone to check it. The tasks below take the most of that time.
- 13% AI can do it
- 43% AI helps
- 44% Needs a person
- Maintain equipment storage areas to ensure that inventory is protected. Warehouse workers, 15% exposed
- Move freight, stock, or other materials to and from storage or production areas, loading docks, delivery vehicles, ships, or containers, by hand or using trucks, tractors, or other equipment. Warehouse workers, 8% exposed
- Install protective devices, such as bracing, padding, or strapping, to prevent shifting or damage to items being transported. Warehouse workers, 5% exposed
- Enforce safety and sanitation regulations. Production supervisors, 15% exposed
- Sort cargo before loading and unloading. Warehouse workers, 12% exposed
Adoption path
Start with the tasks where AI helps a person, then automate the routine ones, then give whole workflows to agents with a person approving the output.
Teams in this industry
The business functions in manufacturing, by share of the workforce, with each one's exposure.
Roles in manufacturing
The 20 largest roles, each linked to its task-by-task score. Shares come from the BLS industry staffing estimates, May 2025. Of the roles with at least 2% of the jobs, sales representatives score highest at 63, warehouse workers lowest at 17.
- Production supervisors, 4.5% of the workforce, score 43 out of 100
- Warehouse workers, 3.6% of the workforce, score 17 out of 100
- Quality inspectors, 3.5% of the workforce, score 40 out of 100
- Packaging machine operators, 2.7% of the workforce, score 19 out of 100
- Welders, 2.5% of the workforce, score 19 out of 100
- General managers, 2.3% of the workforce, score 44 out of 100
- Industrial engineers, 2.3% of the workforce, score 55 out of 100
- Machinists, 2.2% of the workforce, score 28 out of 100
- Industrial machinery mechanics, 2.1% of the workforce, score 31 out of 100
- Shipping clerks, 2.1% of the workforce, score 47 out of 100
- Sales representatives, 2.1% of the workforce, score 63 out of 100
- Maintenance workers, 1.9% of the workforce, score 21 out of 100
- Industrial production managers, 1.7% of the workforce, score 44 out of 100
- Forklift operators, 1.6% of the workforce, score 10 out of 100
- CNC operators, 1.4% of the workforce, score 38 out of 100
- Truck drivers, 1.4% of the workforce, score 27 out of 100
- Press operators, 1.4% of the workforce, score 18 out of 100
- Food batchmakers, 1.3% of the workforce, score 24 out of 100
- Molding machine operators, 1.3% of the workforce, score 18 out of 100
- Software developers, 1.2% of the workforce, score 59 out of 100
Questions about AI in manufacturing
Which tasks should a manufacturer automate first?
The first task to automate is to read work orders or receive oral instructions (40% exposed). Next come the tasks to keep records of employees' attendance and hours worked (72%) and to maintain operations data (75%). Together they free the most hours across the industry.
How many hours can AI save a manufacturer?
About 621 hours a year per full-time person, 31% of a 2,000-hour working year. For a team of 10 that is about 6,210 hours, the time of 3.1 full-time people. The figure is the share of task time AI can remove today, weighted by how many people do each job.
Which roles in a manufacturer are most exposed to AI?
Of the roles with at least 2% of the jobs, sales representatives score highest, at 63 of 100, and warehouse workers lowest, at 17. Each role's page lists its tasks one by one.
Will AI replace jobs in manufacturing?
AI can do 13% of the task time across these roles today. Another 43% gets faster with AI while a person stays in charge. 44% needs a person. One task that stays with people is to maintain equipment storage areas.
Where should a manufacturer start with AI?
With the quick wins: approved assistants for the tasks AI helps with, under a written AI policy. Then automate the 8 tasks on this page AI can do end to end. An AI audit maps the tasks in your team and ranks them the same way this page does.
Next steps
Find the tasks to automate first in your team
We map the tasks in your business, score each one the way this page does and build the automations that pay back first.