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Technology
Product Manager
Based on 41 assessments · 5 from real users
31%
Moderate risk
Average realistic automation risk across all Product Manager profiles in the dataset.
Score spread
Distribution across 41 profiles.
Middle half of Product Managers score between 28% and 34%.
0%
50%
100%
Task breakdown by work type
Done entirely on a computer. High AI exposure — these tasks are already in the automation zone.
Physical sensing, digital output — e.g. interviewing someone then writing a report. Partially protected.
Computer input, real-world output — needs someone to act on it, not just software.
No computer required. Furthest from automation — the strongest human advantage.
Typical tasks
3 synthetic profiles for a Product Manager, ordered by automation exposure.
Tab between them to see how task mix drives the score difference.
Defining and prioritizing product features based on customer needs, business goals, and technical feasibility
deep expertise
social element
44%
AD
23%
Conducting stakeholder meetings to gather input, present updates, or negotiate trade-offs (e.g., scope vs. timeline)
deep expertise
social core
21%
AA
1%
Collaborating with engineering, design, and marketing teams to align on product development timelines and deliverables
deep expertise
social core
13%
AD
10%
Writing detailed product requirements documents (PRDs) or user stories for engineering teams
11%
DD
57%
Monitoring product performance metrics (e.g., user engagement, retention) and iterating based on data
deep expertise
6%
DD
36%
Coordinating beta tests or user research sessions to validate product assumptions
deep expertise
social element
1%
AD
13%
Analyzing market trends, competitor products, and customer feedback to identify opportunities or gaps
1%
DD
63%
Conducting stakeholder meetings to gather input, present updates, or negotiate trade-offs (e.g., scope vs. timeline)
deep expertise
social element
20%
AA
11%
Monitoring product performance metrics (e.g., user engagement, retention) and iterating based on data
20%
DD
67%
Defining and prioritizing product features based on customer needs, business goals, and technical feasibility
deep expertise
social element
16%
AD
11%
Writing detailed product requirements documents (PRDs) or user stories for engineering teams
15%
DD
45%
Analyzing market trends, competitor products, and customer feedback to identify opportunities or gaps
9%
DD
63%
Coordinating beta tests or user research sessions to validate product assumptions
9%
AD
29%
Collaborating with engineering, design, and marketing teams to align on product development timelines and deliverables
deep expertise
social element
9%
AD
15%
Analyzing market trends, competitor products, and customer feedback to identify opportunities or gaps
24%
DD
62%
Collaborating with engineering, design, and marketing teams to align on product development timelines and deliverables
deep expertise
social core
21%
AD
12%
Monitoring product performance metrics (e.g., user engagement, retention) and iterating based on data
21%
DD
59%
Defining and prioritizing product features based on customer needs, business goals, and technical feasibility
deep expertise
social element
16%
AD
15%
Writing detailed product requirements documents (PRDs) or user stories for engineering teams
12%
DD
63%
Conducting stakeholder meetings to gather input, present updates, or negotiate trade-offs (e.g., scope vs. timeline)
deep expertise
social core
3%
AA
10%
Coordinating beta tests or user research sessions to validate product assumptions
deep expertise
social element
1%
AD
16%
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