Insurance, like many industries, is in full sprint toward artificial intelligence. Conferences are packed with AI demos. Strategy decks are flooded with automation goals. And boardrooms are asking "Why not AI?"
Instead, many might want to ask, "Why now?" or even, "Are we ready?"
From where I sit, too many carriers are chasing AI before they've laid the groundwork. They're eager to run with advanced tools, but their operations are still learning to walk.
Let's be clear: AI and automation are powerful upgrades, like switching from hand tools to power tools when building a house. But it doesn't matter how advanced your tools are if the foundation is cracked. In the same way, if your core systems are fragmented, inefficient, or poorly integrated, AI won't fix them. It will just amplify what's broken.
The Risk of Skipping the Basics
I've seen this happen more than once. A carrier gets excited about AI-powered underwriting or virtual claims assistants. They invest in the tech, build a team and expect results. Immediately. But within months, the project stalls. Budgets balloon. Stakeholders lose faith. Or worse, the tool works, but they produce outputs that are unusable because the surrounding systems aren't connected.
AI doesn't work in isolation. It needs clean, structured, reliable data. It needs integrated workflows. It needs clear visibility into the customer journey. And it needs all of that before you turn on your first model.
Too many insurers are trying to build a smart home, installing smart bulbs, thermostats, and locks, without fixing the faulty wiring behind the walls. Layering AI on top of outdated systems, manual workarounds and siloed data means you're not innovating. You're firefighting.
What Are the Facts?
According to a 2024 Deloitte survey, between 70% and 80% of U.S. insurers have implemented generative AI in at least one business function, such as claims, customer service, or distribution. That aligns with broader findings that indicate that by the end of 2025, around 91% of insurance companies worldwide will have adopted some form of AI technology. Some AI-powered claims automation is already cutting processing time by as much as 70%.
But that adoption isn't without friction. According to another recent survey, 74% of insurers still rely on outdated legacy systems for critical operations like pricing, underwriting and rating.
That gap reveals the heart of the issue: Enthusiasm for AI is real and fast, but operational maturity often isn't keeping pace.
The Must-Haves Before You Automate
If you're an insurer considering AI, there are ways to implement it. Before doing that, I caution you to take a hard look at your operations first. Ask:
- Are our core systems integrated?
- Is our data clean, consistent and accessible in real time?
- Do we have automated workflows that allow AI to act, or do we still depend on email and spreadsheets to get things done?
- Can we trace and audit every customer touchpoint across systems?
If the answer is no to any of the above, AI won't help you, at least not yet. And that's not a critique on AI. It's a call to action for operational readiness.
Modernization First, Then Automation
The insurers seeing real results from AI are the ones who took the time to modernize their business first. They invested in workflow automation. They connected their systems. They focused on data quality and governance. They created operational environments that are scalable, transparent and efficient.
Only then did they start exploring AI, not as a gimmick but as an extension of the maturity they'd already built. The difference is obvious. Their projects hit milestones. Their tools integrate seamlessly. And their teams actually trust and use the outputs.
AI Can't Fix Ops, But Ops Can Make AI Work
AI adoption feels inevitable (maybe even urgent), with pressure coming from all sides. But urgency without readiness doesn't lead to progress. It leads to wasted time, money and trust. You wouldn't run a marathon if you hadn't tried a 5K first, right? The real opportunity in insurance isn't just about being early to AI, it's about being ready for it.
Operational maturity isn't glamorous. It's not as flashy as a chatbot demo or as headline-grabbing as an AI-powered claims system. But it's the difference between innovation that sticks and ideas that quietly fail.
AI will transform insurance; there's no question about it. But it's not a quick fix. It's a multiplier, not a miracle. And only those who've done the hard work of modernization will see it pay off.
