Engineering and product R&D

ISCO-08 2141, 2144, 2149

Mechanical engineer, Design engineer, R&D engineer, Industrial engineer, Simulation engineer, Engineering project lead

AI exposure33%

Headcount need, in FTE

Exposure range

Your current headcount

FTE

Need in 203095 FTE-5 FTE (-5%)

Need in 203590 FTE-10 FTE (-10%)

How AI is used on these tasks today

Automation 49%Augmentation 51%

In AI conversations about this job's tasks: the AI does the task itself (automation) or helps the person do it (augmentation).Anthropic Economic Index, April and May 2026. Occupations: Mechanical Engineers, Automotive Engineers. AEI

1. Exposure 33%Average automation potential of the job's tasks. Range for this family: 22 to 44%.ILO occupations used: Industrial and Production Engineers (37%), Mechanical Engineers (32%), Engineering Professionals Not Elsewhere Classified (30%). ILO data

2. Strategic ceiling 100%Your call: how much of this potential do you want to capture? Nobody can set it for you.

3. Adoption speed midpoint 2030

Inherits your company stance, adjustable for this family.

4. Conversion to headcount sensitive 30%Default 30%: Engineering workload follows product roadmaps and time to market; time saved mostly goes into exploring more design options and shorter cycles.

Target AI skills

level 1 to 4

Foundation

Use AI assistants every day

Frame and phrase a request

Check and challenge AI outputs

Protect data and respect the rules

Applied

Rethink one's process with AI

Analyse data with AI

Produce content with AI

Delegate to and supervise AI agents

Expert

Build and integrate AI solutions

Evaluate and make AI solutions reliable

Job skills

Growing in value

Systems engineering and requirement trade-offs
Validating simulation and generative design results
Physical testing and prototype interpretation
Protecting intellectual property when using AI

Losing value

Drafting design files and test reports
Routine CAD modelling of standard parts
Searching standards and past projects
Manual preparation of bills of materials

How the job will change

AI shortens many steps of engineering work without designing products on its own. Assistants search standards, patents and past project files, draft specifications and test reports, and write calculation scripts. Generative design and AI-accelerated simulation explore far more geometry options than an engineer could test by hand. Routine CAD work on standard parts and bills of materials goes faster.

The job moves towards system-level choices and validation. Engineers define requirements and constraints, compare options produced by tools and decide which results deserve a physical prototype. Responsibility for safety and certification stays with them. A good engineer tomorrow masters physics well enough to spot an implausible simulation, works across disciplines and protects company know-how when using external AI tools.

2026-2027: Assistants for documentation, standards search and calculation scripts.
2028-2030: Generative design and AI simulation routine in early design phases.
2031+: Shorter development cycles; engineers focus on architecture, validation and certification.

Watch out

Engineering know-how sits with experienced engineers close to retirement and is poorly documented. Feeding it into AI tools without strict confidentiality rules also exposes the company's intellectual property. See the seniority outlook below.

What if you hired fewer juniors?

Your 2036 seniors are the juniors you hire today.

Seniors available in 2036-5%2 FTE short

Gap above 5% from2036

Your seniority mix today

Juniors (0 to 3 yrs in the profession)25%Seniors (10+ yrs)30%

Mid-level (3 to 10 yrs in the profession, the remainder)45%

Cut in junior hiring -40%

For

Advanced settings

Juniors promoted each year25%Juniors leaving each year12%Senior gap filled by external hiring0%If every company makes the same bet, senior profiles will be scarce and expensive.

Seniority mix, % of today's headcount

Juniors25%Mid-level42%Seniors28%

2026 2036

Free guide

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AI Impact Diagnostic: 6 to 8 weeks, your data in albert, three costed scenarios and the projected seniority mix for each job family.

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How the numbers are built

Every headcount figure combines four assumptions. Three come pre-filled from public research and job family defaults. The strategic ceiling is yours to set.

Public researchExposureAverage automation potential of the job's tasks, from the ILO's 2025 task-level scores.

Your decisionStrategic ceilingHow much of that potential you choose to capture. Your decision, not ours.

Your companyAdoption speedHow fast your company moves, set once for the whole company.

Job family defaultConversion to headcountHow much of the productivity gain becomes fewer people rather than more output.

Headcount effect

Seniority outlook

A flow model with three levels of experience in the profession. Promotion and exit rates are set so that today's mix stays stable when hiring does not change: any gap you see comes from the junior hiring cut alone.