Hello and welcome to Eye on AI. In this edition…a mega seed round for ex-OpenAI CTO Mira Murati’s new startup…the impact of AI on cognitive skills…and why the effects of AI automation may vary so much across sectors.Insurance is not considered the most cutting edge industry. But AI has been making slow, steady in-roads in the sector for years. Many companies have begun using computer vision applications that automatically assess damage—whether that is to cars following a collision or to the roofs of houses following a major storm—to help claims adjusters work more efficiently. Companies are also using machine learning algorithms to help detect fraud and build risk models for underwriting. And, of course, like many other industries, insurance companies are using AI to boost productivity in many support functions, from chatbots that can answer customer queries to AI that can help design marketing materials to AI coding assistants to help internal tech teams.Which insurance companies are doing it best? That’s what the London-based research and analytics firm Evident Insights set out to discover with a new index assessing major insurance firms’ AI prowess. Evident has become known in recent years for its detailed benchmarking of banks’ AI capabilities. But this is the first time the research firm has moved beyond banking to look at another sector.Like its banking index, Evident’s assessment is based almost entirely on quantitative metrics derived mostly from public sources of information—management statements in financial disclosures, press releases, company websites, social media accounts, patent filings, LinkedIn profiles, and news articles. In all, Evident looked at 76 individual metrics, organized into four “pillars” that the research firm said it believes are critical to deploying AI successfully: talent (which counts for 45% of the overall ranking), innovation (30%), leadership (15%), and transparency of responsible AI activity (10%). It used these to rank the 30 largest North American and European insurers when judged by total premiums underwritten or total assets under management.Two insurers, Axa and Allianz emerged as clear leaders in Evident’s assessment. They were the only two to rank in the top five across all four pillars and had a substantial lead over third-place insurer USAA.
Even in the age of AI, human capital can be decisive
Alexandra Mousavizadeh, the cofounder and co-CEO of Evident, tells me that the result is surprising, in part because both Axa and Allianz are based in Europe, where large companies have generally been seen as lagging their North American peers in AI adoption. (And in Evident’s banking index, all of the highest ranked firms are North American.) But Mousavizadeh says that she thinks Axa and Allianz have 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.”Mousavizadeh says that claims and underwriting automation are both big engineering challenges that require large teams of skilled developers and technology experts to make work 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.”Companies that invest most heavily in human AI expertise are most likely to excel at using AI to run their businesses more efficiently, opening up an ever-widening gap between these companies and those that are AI laggards. (Of course, in Evident’s methodology, it helps if management talks about what it’s doing with AI and publicizes its AI governance policies too. USAA actually ranks first on Evident’s talent pillar, but falls down to third place because it ranks near the bottom of the pack on both “leadership”—which is mostly about management’s statements about how the company is using AI—and “transparency of responsible AI policies.”)
Show us the money
Still, as in many industries, there still seems to be a substantial gap in the insurance sector between AI hype and actual ROI. Of the 30 insurers Evident evaluated, only 12 had disclosed at least one AI use case with “a tangible business outcome.” Just three insurers—Intact Financial, Zurich Insurance Group, and Aviva—had publicly disclosed a monetary return from their AI efforts. That’s pretty poor.The most transparent of this group was Canada-based Intact Financial, a property and casualty insurer that said publicly in 2024 that it had invested $500 million in technology (that’s all tech, not just AI) across its business, had deployed 500 AI models, and had seen $150 million dollars in benefit so far. One of its use cases was using AI models that transform speech-to-text and then language models on top of those transcripts to assess the quality of how its human customer service agents handled the up to 20,000 customer calls the company receives daily.That’s still a cost-savings example—a way of boosting the bottom line—and not one in which a company is using AI to grow its sales or move into new business areas. Evident found that insurers were primarily applying AI this way—attacking the industry’s largest cost centers, namely claims processing, customer service, and underwriting. As the research firm notes: “Revenue-generating AI is yet to appear on our outside-in assessment.”The story here isn’t just about insurance—it’s about every industry grappling with AI. Executives everywhere are still figuring out which AI investments will pay off, but the early winners share a common thread: they’re not just buying AI tools, they’re building AI teams. They’re hiring engineers, experimenting relentlessly, measuring results—and then expanding the successful use cases everywhere they can. And benchmarking, like the kind Evident is doing, can play a vital role in both informing executives about what seems to be working—and pushing entire industries to adopt AI faster, as well as to being more transparent about how they’re using AI and what policies they have in place around its responsible use. That’s a lesson worth learning, whether you’re insuring cars or building them.With that, here’s more AI news. And, before we get to the other sections, I want to flag this deep dive article from my colleagues Sharon Goldman and Allie Garfinkle into the background behind Meta’s $14 billion investment into Scale AI and the hiring of Scale cofounder and CEO Alexandr Wang for a major new role at Meta. Their story is a must-read. Check it out here.
Jeremy [email protected]@jeremyakahnWant to know more about how to use AI to transform your business? Interested in what AI will mean for the fate of companies, and countries? Then join me at the Ritz-Carlton, Millenia in Singapore on July 22 and 23 for Fortune Brainstorm AI Singapore. This year’s theme is The Age of Intelligence. We will be joined by leading executives from DBS Bank, Walmart, OpenAI, Arm, Qualcomm, Standard Chartered, Temasek, and our founding partner Accenture, plus many others, along with key government ministers from Singapore and the region, top academics, investors and analysts. We will dive deep into the latest on AI agents, examine the data center build out in Asia, examine how to create AI systems that produce business value, and talk about how to ensure AI is deployed responsibly and safely. You can apply to attend here and, as loyal Eye on AI readers, I’m able to offer complimentary tickets to the event. Just use the discount code BAI100JeremyK when you checkout.
This story was originally featured on Fortune.com
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