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AI deployment isn’t uniform. The same role can face high exposure in one industry and moderate exposure in another — because the rate at which companies actually run AI for those tasks varies. Below: 7 sectors, ranked by current deployment intensity, with the most-exposed roles in each.
SaaS, infrastructure, AI/ML, cybersecurity, and platform companies — the fastest AI adoption curve.
Avg deployment
3%
Adoption signals
299
Most-exposed roles in tech
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
274
Most-exposed roles in retail / e-commerce
Banks, asset managers, insurance, fintech — heavily regulated, capital-intensive AI deployment.
Avg deployment
1%
Adoption signals
276
Most-exposed roles in financial services
Providers, payers, pharma, medtech — high consequence stakes slow but do not stop AI deployment.
Avg deployment
1%
Adoption signals
283
Most-exposed roles in healthcare
Industrial, automotive, energy, supply chain — embodied work blends with AI-driven planning and design.
Avg deployment
1%
Adoption signals
274
Most-exposed roles in manufacturing
Public sector and academia — slow procurement cycles, but high political pressure on AI accountability.
Avg deployment
1%
Adoption signals
274
Most-exposed roles in government / education
Each industry page synthesises the slice of our adoption signal pipeline filtered to that sector. We track how many companies have publicly demonstrated AI deployment for specific tasks (as a percentage), how that percentage is changing quarter-over-quarter, and which capabilities have the strongest evidence base. Roles then inherit industry-specific exposure based on which of their tasks are most affected in that sector.
Read the full methodology →