By The insurance industry, often seen as a bastion of tradition, is in the midst of a slow but steady technological revolution.
For years, artificial intelligence has been making quiet inroads into the sector, and now, a new index reveals which giants are leading the charge—and how most are still struggling to translate AI hype into tangible financial returns.
Many insurance companies have already begun using AI applications in their core operations.
Computer vision systems can automatically assess damage, whether it’s to a car after a collision or to the roof of a house after a major storm, helping claims adjusters work more efficiently.
Machine learning algorithms are being deployed to detect fraudulent claims and to build more sophisticated risk models for underwriting policies.
And, like countless other industries, insurers are leveraging AI to boost productivity in support functions, from customer service chatbots to AI-powered marketing design and coding assistants for their internal tech teams.
But which insurance companies are truly excelling at this?
That’s the question the London-based research and analytics firm Evident Insights set out to answer with a new index assessing the AI prowess of major insurance firms.
Having gained recognition in recent years for its detailed benchmarking of AI capabilities in the banking sector, this marks Evident’s first foray into another industry.
Evident’s assessment is built almost entirely on quantitative metrics derived from public sources—including management statements in financial disclosures, press releases, company websites, social media, patent filings, LinkedIn profiles, and news articles.
The firm analyzed 76 individual metrics, organized into four key “pillars” it believes are critical for successfully deploying AI: Talent (weighted at 45%), Innovation (30%), Leadership (15%), and Transparency of responsible AI activity (10%).
Using this framework, Evident ranked the 30 largest North American and European insurers, judged by total premiums underwritten or total assets under management.
European giants outpace North American peers
In a surprising result, two European insurers, Axa and Allianz, emerged as the clear leaders in Evident’s assessment.
They were the only two companies to rank in the top five across all four pillars, establishing a substantial lead over the third-place insurer, USAA.
Alexandra Mousavizadeh, the co-founder and co-CEO of Evident, found this result particularly noteworthy, telling me in an interview that it challenges the common perception that European companies lag behind their North American peers in AI adoption.
Indeed, in Evident’s banking index, all of the highest-ranked firms are North American.
Mousavizadeh theorizes that Axa and Allianz share a common corporate cultural trait that may explain their AI dominance. “My theory on this is that it’s embedded in an engineering culture,” she says.
Axa and Allianz have been doing this for a very long time and if you look at their histories, there has been much more of an engineering leadership and engineering mindset.
She explains that automating core processes like claims and underwriting represents significant engineering challenges that require large, skilled teams of developers and technology experts to implement effectively at scale. “You have got to have more engineers,” she says.
For that last mile of getting a use case into production, you have to have AI product managers, and you have to have AI software engineering.
This suggests that even in the age of AI, human capital remains a decisive factor.
Companies that invest most heavily in human AI expertise are the most likely to excel, creating an ever-widening gap between themselves and the industry’s AI laggards.
Evident’s methodology also gives credit to companies whose management openly discusses their AI strategies and publicizes their AI governance policies.
This is where USAA, despite ranking first on the “talent” pillar, ultimately fell to third place overall, as it ranked near the bottom of the pack on both “leadership” and “transparency.”
The glaring gap between AI hype and ROI
Despite the progress and investment, a substantial gap still exists between AI hype and actual, quantifiable Return on Investment (ROI) in the insurance sector.
Of the 30 insurers evaluated by Evident, only 12 had disclosed at least one AI use case with “a tangible business outcome.”
Even more striking, just three insurers—Intact Financial, Zurich Insurance Group, and Aviva—had publicly disclosed a specific monetary return from their AI efforts.
The most transparent of this small group was Canada-based Intact Financial, a property and casualty insurer.
In 2024, the company publicly stated that it had invested $500 million in technology (encompassing all tech, not just AI) across its business, had deployed 500 AI models, and had so far seen a $150 million benefit.
One of its specific use cases involved using AI models to transcribe customer service calls and then applying language models to those transcripts to assess the quality of how its human agents handled the up to 20,000 customer calls the company receives daily.
Notably, this is still a cost-savings example—a way to boost the bottom line rather than grow top-line revenue.
Evident found that this is how insurers are primarily applying AI today: attacking the industry’s largest cost centers, namely claims processing, customer service, and underwriting.
As the research firm notes in its report: “Revenue-generating AI is yet to appear on our outside-in assessment.”
The story here extends far beyond the insurance industry; it’s a narrative playing out in every sector grappling with the promise and complexity of AI.
Executives everywhere are still in the process of figuring out which AI investments will truly pay off.
However, the early winners seem to share a common strategy: they are not just buying off-the-shelf AI tools; they are investing in building dedicated AI teams.
They are hiring engineers, experimenting relentlessly, meticulously measuring results, and then scaling the successful use cases across their entire organization.
Benchmarking exercises, like the one conducted by Evident, can play a vital role in this process, both by informing executives about what strategies appear to be working and by pushing entire industries to adopt AI more rapidly and with greater transparency about its use and governance.
It’s a lesson worth learning, whether you’re insuring cars or building them.
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