Building an AI Operating Model for a Regional Insurer
A mid-market insurance company needed AI governance, competitive intelligence automation, and a strategic roadmap. We built the operating model and deployed working systems within 60 days.
AI interest without AI infrastructure
The insurer's executive team recognized that AI could transform underwriting efficiency, claims processing, and competitive positioning. Multiple departments had begun experimenting with AI tools independently — marketing was using ChatGPT for content, claims adjusters were testing summarization tools, and the actuarial team had explored predictive modeling vendors.
The result was fragmented adoption with no governance, no shared infrastructure, and no way to measure whether any of it was working. The CIO raised concerns about data security and compliance risk. The CEO wanted a strategic plan but didn't have anyone internally who could own AI at the enterprise level.
They needed an AI operating model — not a strategy deck, but a working system that connected governance, prioritization, and execution under a single accountable function.
Embed first, build second
Spej engaged as the insurer's retained AI Office. In the first two weeks, we conducted stakeholder interviews across seven departments, audited existing tool usage, and assessed data readiness. This wasn't a surface-level survey — we mapped actual workflows, identified where AI could reduce cycle time, and flagged compliance gaps in how teams were already using generative AI.
From the audit, we built a prioritized roadmap organized by business impact and implementation complexity. The first initiative — automated competitive intelligence — was selected because it addressed a clear executive pain point, required no changes to core systems, and could demonstrate value within weeks.
In parallel, we stood up the governance framework: an AI acceptable use policy, a model risk management process aligned to existing enterprise risk standards, and a monthly AI steering committee with the C-suite.
What we delivered
- AI governance framework with acceptable use policy, model risk controls, and compliance documentation
- Enterprise AI roadmap with 12 initiatives prioritized by ROI and implementation complexity
- Automated competitive intelligence system that monitors carrier filings, rate changes, and market movements
- AI operating model defining roles, decision rights, and escalation paths for AI adoption
- Monthly AI steering committee structure with executive reporting templates
- Department-level AI training for claims, underwriting, and marketing teams
Measurable outcomes
Stop experimenting. Start executing.
A 30-minute discovery call to assess where you are, where the gaps are, and what a structured path forward looks like.
Book a Discovery CallNo pitch deck. No pressure. Just clarity.