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AI deployment isn’t uniform. The same role can face very different exposure in different sectors — because the rate at which companies actually run AI for those tasks varies by industry, regulation, and capital depth. Below: 7 sectors, ranked by current production deployment, with the most-affected roles in each.
SaaS, infrastructure, AI/ML, cybersecurity, and platform companies — the fastest AI adoption curve.
Avg deployment
3%
Adoption signals
327
Most-exposed roles in tech
Banks, asset managers, insurance, fintech — heavily regulated, capital-intensive AI deployment.
Avg deployment
2%
Adoption signals
290
Most-exposed roles in financial services
Consulting, legal, accounting, design — knowledge work where AI tooling reshapes margin structure.
Avg deployment
2%
Adoption signals
274
Most-exposed roles in professional services
Direct-to-consumer, marketplaces, brick-and-mortar — operational AI reshaping merchandising and CX.
Avg deployment
2%
Adoption signals
276
Most-exposed roles in retail / e-commerce
Providers, payers, pharma, medtech — high consequence stakes slow but do not stop AI deployment.
Avg deployment
1%
Adoption signals
300
Most-exposed roles in healthcare
Industrial, automotive, energy, supply chain — embodied work blends with AI-driven planning and design.
Avg deployment
1%
Adoption signals
283
Most-exposed roles in manufacturing
Public sector and academia — slow procurement cycles, but high political pressure on AI accountability.
Avg deployment
1%
Adoption signals
275
Most-exposed roles in government / education
Each industry page is our adoption pipeline filtered to that sector: how many companies have publicly deployed AI for specific tasks, how fast that's moving quarter-over-quarter, and which capabilities have the strongest evidence. Roles inherit industry-specific exposure from the tasks most affected there.
Read the full methodology →