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AI readiness assessment for claims teams

Insurers that scaled AI in claims are already seeing the payoff: Capgemini found trailblazers report 21% higher revenue growth than the rest of the industry.1 Answer 10 short questions across data, process, technology, governance and people to see where your claims organization stands, mapped to MIT CISR's enterprise AI maturity model.2

  • 10 questions, 5 dimensions
  • Mapped to a recognized maturity model
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AI readiness assessment

Data · Question 1 of 10How accessible is your claims data for analysis?

Why AI readiness matters now

Insurance is no longer waiting on AI. The gap is opening between carriers that have scaled it in claims and those still piloting.

21%

higher revenue growth reported by P&C "trailblazers" furthest along in AI adoption, versus the rest of the industry.1

78%

of global insurers say data readiness, not the AI itself, is the biggest barrier to getting value from it.3

85%+

of insurance executives say their organization has adopted AI in some form, per BCG's 2025 survey.4

Carriers using advanced analytics and AI report stronger returns and premium growth than those that have not.5 The strategy gap is rarely the AI itself. It is whether the data, workflows, governance and people around it are ready to support it.6

The five dimensions of AI readiness

This assessment scores five dimensions that consistently separate organizations that scale AI from those stuck piloting it, drawing on MIT CISR's enterprise AI maturity research.2,7

  • Data. Is claims data accessible, clean and consistent enough for a model or a person to trust it?
  • Process. Are workflows standardized enough that AI assistance fits into them, rather than adding a parallel, inconsistent path?
  • Technology. Is AI actually in production, and can your core systems integrate with the tools you want to use?
  • Governance. Is there a written policy for reviewing AI use, and a plan for the regulatory requirements that apply to it?
  • People. Are staff trained and willing to work with AI, and is there an executive sponsor backing adoption with resources?

What regulators expect

AI governance in claims is not just good practice. It is increasingly a compliance requirement, and the expectations vary by jurisdiction.

RuleWhat it expects
NAIC Model Bulletin on AI8A written AI program with governance, risk controls and vendor oversight, adopted by regulators in a growing number of states.9
Colorado SB21-169 and Regulation 10-1-110,11A governance and risk management framework for insurers using external data and algorithms in life insurance, including testing for unfair discrimination.
EU AI Act12,13Risk-based obligations for AI systems, with insurance underwriting and pricing use cases treated as high-risk in the original regulation.

Rules continue to evolve. Treat this table as a starting point for your compliance review, not a substitute for legal advice.

Updated by the amaise team.

Frequently asked questions

What is AI readiness in insurance claims?

It is how prepared a claims organization is to adopt AI successfully: whether its data, workflows, technology, governance and people can support AI tools in production, not just in a pilot.

What is the MIT CISR enterprise AI maturity model?

Research from MIT's Center for Information Systems Research that maps how organizations progress from ad hoc AI experiments to AI embedded across their operations, backed by data and governance.2

Why is data readiness the biggest barrier to AI in insurance?

Because AI is only as good as the data behind it. Insurers report that inconsistent, siloed or poor-quality claims data, more than the technology itself, is what stalls AI projects.3,14

Do I need a written AI governance policy?

Regulators increasingly expect one. The NAIC Model Bulletin calls for a written AI program with governance and risk controls, and more states are adopting it.8,9

How is the AI readiness score calculated?

Each of the 10 questions scores 0 to 3 points, for a total out of 30. The total maps to a maturity stage, and each of the five dimensions is scored separately to show your strongest and weakest areas.

Is this assessment specific to claims, or all of insurance?

The questions are written for claims organizations, but the five dimensions, data, process, technology, governance and people, apply to AI adoption anywhere in insurance.

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Claims document review ROI calculator

Size the hours, FTEs and dollars your team spends reading medical records, and what AI-assisted review returns.

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See what AI-ready claims review looks like

amaise reads the full medical record and surfaces diagnoses, procedures and gaps in treatment, with a citation to the source page for every fact, built for the governance this assessment scores.

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Sources

  1. Capgemini, World Property and Casualty Insurance Report 2026 (press release) (May 2026).
  2. MIT Center for Information Systems Research, The Enterprise AI Maturity Model (Dec 2024).
  3. LIMRA and Equisoft, LIMRA and Equisoft report: 78% of global life insurers believe data readiness is the biggest challenge to getting value from AI (Jan 2025).
  4. Boston Consulting Group, Insurance leads in AI adoption. Now it's time to scale. (Sep 2025).
  5. WTW, Insurers using advanced analytics and AI report strong returns on investment and premium growth (Mar 2026).
  6. Deloitte Insights, Scaling gen AI in insurance (Apr 2025).
  7. MIT Center for Information Systems Research, Enterprise AI maturity update (Aug 2025).
  8. National Association of Insurance Commissioners, Model Bulletin: Use of Artificial Intelligence Systems by Insurers (Dec 2023).
  9. National Association of Insurance Commissioners, Implementation of the NAIC Model Bulletin on the use of AI systems by insurers (adoption map) (Aug 2026).
  10. Colorado General Assembly, SB21-169: Restrict insurers' use of external consumer data (2021).
  11. Colorado Division of Insurance, Notice of adoption: amended Regulation 10-1-1 (governance and risk management framework) (2025).
  12. EUR-Lex, Regulation (EU) 2024/1689 (Artificial Intelligence Act) (Jul 2024).
  13. European Commission, AI Omnibus enters into force (Jul 2026).
  14. Gartner, Lack of AI-ready data puts AI projects at risk (Feb 2025).

These tools provide educational estimates based on published benchmarks and your inputs. They are not legal, actuarial or financial advice. Everything you enter stays in your browser.