Board-level agentic AI strategy for an insurer focused on contact-centre automation

Context

We delivered agentic AI strategy for the board of a major retail insurer, operating a high-volume, direct-to-consumer model. The leadership team understood that agentic AI would reshape the economics of customer service, but needed a trusted advisor to turn that conviction into a plan the board could fund and the business could deliver.

The challenge

As with most retail insurers, the bulk of contact-centre effort went into repetitive, high-frequency after-sales requests. The routine intents customers raise again and again once they have bought a policy. These were well understood, well documented. The question was not whether agents could help, but how to extend prior automation projects, how to prove value safely, and how to build a case that stood up to the financial and regulatory scrutiny of retail insurance.

What we did

The engagement focused on three things:

• Contact-centre automation — mapping the priority customer intents and resolution journeys, and identifying where AI agents could reduce handling times while improving customer satisfaction.
• A 90-day lighthouse plan for after-sales automation, giving the board a concrete path from strategy to measurable results.
• An investment case and risk assessment tailored to the regulatory environment, alongside a reference architecture for an agentic stack suited to insurance.

We collaborated with a number of other teams for this large client, providing the agentic AI specialty knowledge.