Regulatory affairs

ISCO-08 2422, 2262

Regulatory affairs manager, Regulatory affairs specialist, Regulatory CMC specialist, Regulatory intelligence analyst, Labelling specialist, Regulatory operations specialist

AI exposure38%

Headcount need, in FTE

Exposure range

Your current headcount

FTE

Need in 203091 FTE-10 FTE (-9%)

Need in 203581 FTE-19 FTE (-19%)

How AI is used on these tasks today

Automation 43%Augmentation 57%

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: Regulatory Affairs Specialists, Regulatory Affairs Managers. AEI

1. Exposure 38%Average automation potential of the job's tasks. Range for this family: 24 to 48%.ILO occupations used: Policy Administration Professionals (42%), Pharmacists (33%). 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 50%Default 50%: Submission volumes depend on the portfolio and authority requirements; drafting and publishing gains therefore reduce workload directly, while expert judgement remains needed.

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

AI governance and risk management

Job skills

Growing in value

Regulatory strategy and dialogue with authorities
Verifying AI-drafted submission content
Interpreting new or ambiguous regulations
Coordinating submissions across countries

Losing value

Drafting standard dossier sections
Dossier compilation and publishing formatting
Manual regulatory watch and summaries
Updating labelling across country versions

How the job will change

A large share of regulatory work is document-heavy, and that is where AI goes first. Assistants draft standard dossier sections from source data, check consistency between modules, compile and format submissions, update labelling across country versions and summarise new guidance from authorities. Regulatory intelligence, once a manual reading task, becomes a filtered stream of relevant changes. Publishing teams feel the impact earliest.

The job moves towards strategy and accountability. Regulatory professionals decide how to present data, anticipate the questions an agency will ask and negotiate during reviews. They must verify every AI-drafted statement, because an error in a submission can cost months. A good regulatory professional tomorrow combines scientific depth with sound judgement on grey areas and keeps credibility with the authorities.

2026-2027: Assistants draft standard sections and summarise regulatory watch.
2028-2030: Structured submissions largely assembled automatically; publishing teams shrink.
2031+: Smaller teams centred on strategy, authority relations and complex files.

Watch out

Authorities' acceptance of AI-generated content is still evolving and varies by country. Cutting experienced staff before the rules settle could leave the company short of expertise for a major filing or inspection. 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

The AI Cookbook 2026

albert's guide to cut through the noise around generative AI and turn it into workforce decisions.

What AI actually changes in jobs and skills
Why the junior pipeline matters more than most companies realise
How to integrate AI into workforce planning

Download the AI Cookbook

Run these scenarios on your actual workforce

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

Book a call

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.