Product management

ISCO-08 2421, 2511

Product manager, Product owner, Senior product manager, Head of product, Business analyst, Product operations manager

AI exposure48%

Headcount need, in FTE

Exposure range

Your current headcount

FTE

Need in 203092 FTE-8 FTE (-8%)

Need in 203583 FTE-17 FTE (-17%)

How AI is used on these tasks today

Automation 62%Augmentation 38%

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: Marketing Managers, Computer Systems Analysts. AEI

1. Exposure 48%Average automation potential of the job's tasks. Range for this family: 36 to 56%.ILO occupations used: Management and Organization Analysts (46%), Systems Analysts (49%). 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 35%Default 35%: Product teams have more ideas than capacity to test them; time saved on documentation goes into discovery, experiments and user contact.

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

AI governance and risk management

Job skills

Growing in value

Evidence-based prioritisation and saying no
Rapid prototyping with AI tools
Specifying and evaluating AI-based features
Direct user research and field observation
Arbitration between business, tech and legal

Losing value

Writing detailed user stories and specifications
Synthesising interview notes and customer feedback
Release notes and product documentation
Manual competitive benchmarks
Backlog grooming and ticket formatting

How the job will change

Much of a product manager's written output is now drafted by AI: user stories, acceptance criteria, release notes, synthesis of customer interviews and support tickets, competitive scans. Prototyping tools turn a description into a clickable mock-up or a working demo in an afternoon, where a design sprint used to be needed. Product managers write less for developers and spend more time deciding what deserves to be built.

The job moves towards judgement and evidence: choosing the problems worth solving, testing ideas quickly with real users, arbitrating between commercial pressure and technical constraints. More products embed AI features, so product managers must also define acceptable error rates and how to measure them. A good product manager tomorrow will be the one who knows customers best and can defend a priority with data.

2026-2027: Specs, user stories and research synthesis drafted with AI assistants.
2028-2030: AI prototypes replace many written specs; product and design roles start merging.
2031+: Leaner product teams, each manager covering a wider scope with agents.

Watch out

Product owner roles focused on writing tickets for developers are the most exposed. Simply renaming them keeps a costly intermediary layer in place instead of building real product ownership. See the seniority outlook below.

What if you hired fewer juniors?

Your 2036 seniors are the juniors you hire today.

Seniors available in 2036-10%2 FTE short

Gap above 5% from2031

Your seniority mix today

Juniors (0 to 2 yrs in the profession)35%Seniors (6+ yrs)20%

Mid-level (2 to 6 yrs in the profession, the remainder)45%

Cut in junior hiring -40%

For

Advanced settings

Juniors promoted each year33%Juniors leaving each year15%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

Juniors35%Mid-level42%Seniors18%

2026 2036

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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.