Why decades of digital neglect may be a barrier to AI adoption

This spring’s insurance conference season provided one coherent theme: “AI is the future.” Executives discussed progress in testing and releasing their latest artificial intelligence tools in underwriting, claims, fraud detection, and chatbots for customer services. These conferences are packed with sessions on new AI tools and use cases, while LinkedIn has become a crowded source of insurance professionals discussing how they will be implementing the technology. The insurance sector, long seen as a digital laggard, has suddenly taken a strong interest in AI. With insurance being one of the most clear-cut use cases for it, this is a welcome development. 

However, beneath this excitement lies a paradox. People who have spent time in insurance and insurtech are familiar with an adage that insurance is 10+ years behind its financial services relatives. While a newfound focus on innovation is great to see, is the industry ready for the AI revolution?

It’s easy to see why insurance organizations are excited about AI. According to this year’s Conning survey, 90% of insurance executives have begun the evaluation of AI tools, while 55% say they’ve already begun implementing it. The pressure is on: insurtech startups are generating huge amounts of buzz, promising faster quotes, seamless claims, and personalized coverage - all powered by AI. Many of the largest and most prestigious names in our industry are making headlines with their AI investments, hoping to transform everything from risk assessment to customer engagement.

Here's the catch: for all their newfound AI enthusiasm, most insurance organizations have spent the past couple decades neglecting the broader digital transformation their businesses desperately need. Digital transformation isn’t just about plugging in an AI tool; it means rethinking core systems, digitizing processes end-to-end, modernizing data infrastructure, and putting customer experience at the center. Instead, legacy systems remain pervasive and will be an impediment to AI adoption. A recent Earnix blog iterated that 74% of insurers rely on outdated technology for critical functions like pricing, underwriting, and claims. Manual processes persist, with paper forms and spreadsheets still being widely used in back offices. Data is scattered across silos, making it hard to get a single, accurate view of the customer or the business. In a Genpact survey, nearly 40% of insurance leaders cited poor data quality and availability as their biggest barrier to digital progress. This figure is improved against recent years, but expect it to be a persistent barrier to the widespread adoption of AI in the short term. 

This digital neglect is now coming back to bite the industry. AI, for all its promise, is not a simple flick of a switch. It depends on clean, accessible data, automated workflows, and modern IT infrastructure. Without these foundations, even the most sophisticated AI tools are set up to fail. AI algorithms thrive on high-quality, integrated information. But in insurance, data is often trapped in incompatible systems, riddled with errors, or simply missing. Legacy systems also make it hard to embed AI into day-to-day operations. Many AI solutions can’t (yet) integrate with old, monolithic platforms, driving up costs and increasing project risks.

To help illustrate my point, I will share an image that I think captures this paradox:

Insurance executives are ready to spend big on fancy AI tools but haven’t paid off their proverbial mortgage yet. Paying off one’s mortgage means modernizing core systems, investing in data quality and integration, and building a culture that embraces change. 

Some insurers have been serious about digital transformation from the get-go, and they will be the ones to adopt these most effectively and efficiently. They’re rolling out phased digital transformation roadmaps, starting with high-impact areas like claims and underwriting. They’re partnering with insurtechs and tech providers to accelerate modernization. They’re building cross-functional teams that bridge IT, operations, and business units. For those who plan on buying the fancy car before finding a good place to sleep, it will be a longer road. 

The insurance industry’s AI ambition is real, and for good reason. But unless organizations address decades of digital neglect, their bold visions are at risk to remain stagnant, and they will have to refocus on the fundamentals. To unlock the true value of AI and automation, insurers must prioritize the hard work of digital transformation. Only then can they turn today’s hype into tomorrow’s competitive advantage.