Where AI investment could translate into measurable value

Our first article asked whether AI investment can genuinely shift value or simply widen the gap between stronger and weaker performers. Here, we consider where that investment is most likely to translate into measurable value.

Market dynamics

Every insurance market and sub-sector has its own dynamics, with different adoption strategies and AI architecture creating different value opportunities. Companies will be judged against peers on measures such as underwriting return, margin and return on capital. Evident identified 133 use cases between 2024 and 2026; 32% of P&C cases focused on claims management, while underwriting and pricing emerged as recent hotspots across multiple business lines.*

Where value could be released

Alongside potential efficiency gains, certain areas could release financial value:

• System improvement and AI integration could support headcount reduction or redeployment, improving margins and profitability. However, it is unclear whether this represents genuine reductions or investment in new AI capability, particularly as AI-specialist headcount grew 32% year on year while overall insurance employment contracted 2.2%**.
• AI-driven underwriting accuracy and discipline can alter balance sheet economics and profitability, with tools such as Manulife MAUDE providing underwriting decisions in as little as two minutes.
• More efficient claims processing could improve fraud detection and reduce losses, while strengthening customer interaction. Allianz launched Nemo, its first fully integrated agentic AI claims platform, in November 2025.
• Personalisation and better client interfaces could strengthen relationships and drive revenue through a more bespoke client experience. Travelers launched AI Claim Assistant in February 2026, a fully agentic voice service built with OpenAI that gathers details dynamically, responds contextually and guides customers through the end-to-end claims process.
• AI-integrated underwriting could support better capital allocation decisions, potentially improving returns either through pricing or freeing capital for other uses. The question is whether this changes the level of capital held or the return on that capital.

The valuation question

Each area could improve financial performance, but will it translate into higher valuations? AI investment may shift the sector’s ‘normal’ base multiple or deliver only incremental gains once efficiencies are realised. However, evidence of wider financial value remains limited: only 2% of the 65 use cases with reported outcomes in 2026 resulted in revenue uplift***.

FRP’s recent wider mid-market AI research supports this view, with 78% of lenders and investors now considering AI readiness important when assessing credit risk. This suggests AI adoption alone is unlikely to move value without evidence of financial performance, forecast credibility and relative market position.

Companies that do not progress are likely to fall behind, while those that do may generate higher profits at the same high multiple, leading to higher value.

The current state of the market leads to two key observations:

1. There is no real evidence currently that shows AI generating financial returns to businesses, although McKinsey found that insurance firms identified as AI leaders generated 6x greater TSR than AI laggards between 2018 and 2022. This is also becoming harder to isolate as AI adoption becomes more prevalent and its impact becomes harder to distinguish from other factors.
2. The time horizon for the realisation of benefit is key. 

We consider there are three factors when assessing insurance businesses and AI returns:

• P/B is typically driven by return on capital, growth and cost of capital, while P/E can be assessed against P/B and RoE.
• Any increase in value can therefore be assessed by what is driving it: a shift in returns, through margin improvement, revenue growth or capital efficiency; a change in the cost of capital; or both.
• This requires understanding the impact of each initiative and the company’s resulting position relative to the market.

Together, these factors determine overall value and therefore ROI.

Point solutions versus end-to-end value

A key question is whether investment targets areas that drive sustained value, or shorter-term gains, and the ongoing cost of maintaining any advantage. Evident found that 68% of disclosed use cases between 2024 and 2026 relate to point solutions, compared with 32% end-to-end solutions. This distinction is central to pricing an insurance business correctly.

Winners, losers and market separation

As in other sectors, AI adoption across insurance varies in speed and depth. Some businesses will translate investment into sustained value, while others will fall behind. As the market accelerates and matures, these will likely become potential consolidation targets for those with deeper pockets seeking to benefit from the AI advances of others. Early movers investing in AI architecture and strategy could build an advantage that becomes increasingly difficult to close.

The reality of any given market is that without incremental improvement or best-in-class performance, value is, in theory, capped relative to peers. Within insurance, a long-term P/B, or equivalent solvency-based ratio, of substantially greater than 1x or 2x will require a fundamental shift in the market and expectation of returns. Each £1 of capital deployed will need to return more than has historically been understood as achievable, factoring in losses and that the insurance market still needs to provide insurance to bad risks as part of the industry’s societal pact, which creates a drag on capital and earnings.

However, the inverse is not necessarily true. Incremental value can continue to accrue through performance improvement, growth in market share or size, and sensible investment strategies. Evident identifies Allianz and AXA as decisively ahead, the only two insurers to demonstrate strength across the full AI maturity framework.

Allianz, in particular, has developed AllianzGPT, partnered with Anthropic, built the largest AI talent pool in the industry, leads the sector for research and patents, and has over 900 registered AI use cases worldwide spanning underwriting, claims, fraud detection and customer service.

What this means for value

As assessors of value, we remain focused on the business plan and strategy. The fundamentals have not shifted, and it remains unclear whether AI investment will rebase valuations until it delivers meaningful margin or RoE improvement. The winners will combine cohesive architecture with human interaction and expertise, adopting AI quickly while remaining agile.

Find out more about FRP’s Valuations team.

Sources
* Evident: 133 AI use cases identified between 2024 and 2026; 32% of P&C use cases clustered around claims management, while underwriting and pricing have been a recent hotspot across multiple business lines.
** Evident: AI-specialist headcount grew 32% year on year, while overall insurance industry employment contracted 2.2%.
*** Evident: only 2% of the 65 use cases with reported outcomes in 2026 resulted in revenue uplift.

Subscribe to our latest insights by topic here