2026 AI Roadmap and Trends: Execution Defines Leadership

After years of experimentation and pilots, the industry has reached a decisive inflection point where leaders are moving beyond proof-of-concepts into real-world deployment. Organizations that successfully scale AI now outperform their peers by 3–5x across productivity, expense ratio, and speed-to-market metrics.

The report identifies five converging structural forces: persistent economic pressure and margin compression, the explosive surge in the E&S market causing submission overload, increased underwriting complexity due to climate volatility, a structural talent shortage, and rising digital-first customer expectations.

It is a modernized seven-layer digital architecture required to operationalize AI at scale. It builds from a foundation of cloud-native core systems and clean data, through generative and agentic AI capabilities, to enablement layers like modular ecosystems, responsible governance, and a hybrid human-AI workforce, the human-in-the-loop.

For retail agencies, AI acts as a capacity multiplier, allowing them to scale expertise and advisory value without increasing headcount by automating repetitive tasks like policy checking. For MGAs/MGUs, AI serves as the essential infrastructure for maintaining underwriting quality and carrier trust while managing unprecedented submission volumes and compliance demands.

According to the report’s roadmap, the first 0–3 months should focus on the “Foundation” phase: auditing data quality, ensuring secure API integrations for core systems, establishing a governance framework, and launching a high-value, low-risk pilot such as submission summarization or policy checking.