2026 marks a pivotal moment for the insurance industry. After years of pilots and early implementations, insurers are entering the era of real AI performance.
In 2025, insurers built the foundation for responsible adoption through governance, proofs of concept, and hands-on experience in regulated workflows. These efforts prepared the industry to scale with structure, clarity, and confidence.
At Roots, this shift is already visible. In 2025, internal data showed a 68% increase in AI inquiries and more than 40% growth in deployed AI agents, signaling a clear move from experimentation to execution.
In 2026, AI becomes a trusted operational capability. Insurers that succeed will combine governance, cross-functional collaboration, and workforce enablement to deliver measurable results.
This is not about learning AI. It is about leading with it.
From Insurance AI Readiness into AI Reliance
In 2025, many insurers focused on exploration by testing use cases, establishing governance, and validating early pilots. While these efforts were not broadly scaled, they created clarity around where AI delivers value and how it can be integrated responsibly.
That foundation now supports a new level of maturity. In 2026, insurers will be moving from AI readiness to AI reliance, embedding AI into core operations such as submission triage, loss run processing, claims evaluation, and customer service.
Industry events like ITC Vegas highlighted this shift. The growing number of AI vendors reflected strong demand for efficiency and growth, but the message was clear: partner selection matters. For insurers not building AI internally, rigorous vendor validation is critical. The right partner must deliver measurable results, scale with the business, and align with governance and compliance expectations.
This trend was reinforced by the Roots 2025 State of AI Adoption in Insurance report. While over 90% reported exploring or testing AI, only 22% had fully deployed solutions in production. The gap between pilots and scale remains significant, and 2026 is when carriers will begin to close it.
What Separates Leaders from Learners
The difference between insurers still experimenting and those embedding AI across the enterprise is becoming clearer. It lies in how AI is organized, governed, and led.
- Executive Ownership
- Transformation starts with visible leadership commitment. Leading carriers establish AI steering committees with oversight from operations, risk, and technology leaders to ensure alignment with strategy, compliance, and long-term objectives.
- Cross-Functional Governance
- Effective governance goes beyond technical approval. It establishes clear standards for organizational AI use, including employee use of public models, to ensure transparency, oversight, and responsible adoption.
- Workflow Fluency and Talent Integration
- Successful deployment will start with clear workflows and measurable objectives. As retirements outpace new talent, leading insurers will redesign roles early to prioritize judgment, compliance, and strategic work, with human oversight central.
- Measured Scaling
- Scaling AI does not mean deploying everywhere at once. Successful insurers move proven pilots, such as loss run processing or FNOL triage, into production only after accuracy is validated and workflows are stable.
AI leadership in 2026 will be defined not by more pilots, but by the discipline to scale what works.
Culture Over Code: Insurance AI Lessons from 2025
In 2025, insurers learned that responsible AI adoption depends on trust, transparency, and governance, reinforced by education and continuous feedback.
- Trust comes first: Models that lacked transparency struggled to gain adoption. Explainability, not speed, proved essential.
- Governance builds confidence when employees understand and trust it: Clear, reinforced frameworks enable adoption rather than friction.
- Human adoption drives ROI: Change management and AI literacy delivered faster adoption and better accuracy than technical deployment alone.
For insurers preparing to scale, these lessons show what to expand. AI adoption succeeds through culture, not technology.
Executive Insurance AI Priorities for 2026
The groundwork laid in 2025 now demands results. In 2026, the focus will shift from exploring AI's potential to proving consistent, responsible performance at scale.
- Move from vision to execution by translating strategy into measurable outcomes across underwriting, claims, and service operations.
- Expand governance beyond model development to include employee usage, data handling, and ethical oversight.
- Prepare the workforce before deployment by clearly communicating change and redesigning roles to emphasize human judgment and relationships.
- Prioritize adoption over tools. AI succeeds when employees trust it, which requires literacy, training, and structured feedback between people and AI agents.
- Measure what matters, including accuracy, turnaround time, compliance, and customer experience. In AI deployments where organizations embedded KPIs, ROI was achieved within six to nine months.
AI leadership in 2026 is about scaling strategically, proving performance, protecting trust, and preparing people for what comes next.
The Year of Operational Intelligence
Insurers that succeed in 2026 will treat AI as infrastructure, not a tool, embedding it across the organization. AI will strengthen human judgment while improving speed, data quality, compliance, and customer experience.
2026 is the year AI shifts from pilots to production. Success will require clear performance measurement and alignment with transparency, explainability, and fairness expectations.
In 2026, carriers that align governance, workflows, outcomes, and people move from readiness to reliance by scaling confidently and leading with intelligence and integrity.
