Ever used Excel? Maybe you're not a "power user," but chances are you've figured out enough to make it work for you. You didn't need to know every formula or pivot table —when you hit a wall, you asked someone who knew more. Simple.
No one panicked about Excel taking their job. In fact, most people knew they had to at least look proficient in it to get hired.
That's exactly how we should be thinking about AI. It's not something to fear — it's something to learn, use and get better at over time. Not everyone in your organization needs to be an AI expert. But everyone should be familiar enough to use it confidently, ask questions, and experiment.
Start with data — and a clear strategy
Before you dive into AI, you need to get your data house in order. AI runs on data — clean, organized, and accessible data. If your systems are siloed or messy, even the best AI tools won't deliver.
But good data isn't enough. You also need leadership buy-in,
This isn't just an IT project.
Make AI accessible to everyone
Once the foundation is set, it's time to roll out AI in a way that feels approachable. Start with training sessions that show how AI can help with everyday tasks — writing emails, summarizing documents, analyzing data.
Encourage your team to play around with it. Try it in real workflows. Start small, then scale up. Once people are comfortable, you can introduce more specialized tools tailored to each department.
Tools like Microsoft Copilot and Google Gemini are great entry points. They're built for general business use and work across teams. Once people see how helpful these tools are, adoption picks up — and that's when you know your organization is ready for more advanced applications.
Efficiency is just the beginning
Despite being a data-rich industry, insurance remains notoriously inefficient and behind the curve when it comes to adopting modern technologies. Legacy systems, manual processes and siloed data have long slowed progress. This is why the potential of AI isn't just impressive — it's transformative. AI's ability to streamline workflows is well-documented, but in insurance the
Policy reviews, customer service, claims processing and even fraud detection are all low hanging fruit. AI can also predict claim costs more accurately, which helps with reserves. These are great wins — they save time and money. But they don't necessarily grow revenue.
Where AI can actually drive growth
To get and keep leadership excited, AI needs to do more than create efficiencies – it needs to create value.
Think tailored insurance solutions powered by AI-driven risk intelligence. Dynamic models can now adjust in real time based on operational data, claims history, and external risk signals — like weather, cyber threats, or supply chain disruptions. AI can help brokers and underwriters proactively identify client needs and recommend the right coverage across lines such as property, liability, cyber, and workers' comp — boosting cross-sell and upsell opportunities.
Chatbots and virtual assistants can improve customer experience, which helps with retention and lifetime value. And smart dashboards can surface insights across portfolios, helping you spot emerging risks and respond faster.
These aren't just process improvements — they're new ways to differentiate, create a better user experience, and grow your business.
Humans + AI = The future of insurance
AI holds immense promise—but only if it's deployed with intention. Without a clear plan, it risks becoming just another shiny tool that fails to deliver. The same people who can make AI succeed can also cause it to fail if they're not engaged from the start.
This is why organizations must commit to AI not just financially but strategically. Efficiency alone won't sustain momentum. If the only visible outcome is faster email rewrites or automated meeting notes, enthusiasm will fade. AI initiatives must be tied to broader business goals with clear value beyond cost savings — value that resonates with teams, clients and leadership alike.
We are at an inflection point. The future of insurance isn't humans vs. machines — it's humans with machines, working together to manage risk and unlock new opportunities. But if companies sit back and assume AI will simply "happen," that adoption will unfold naturally and efficiency gains are enough, they will miss one of the greatest business opportunities of our time. This is not the moment for passive optimism — it's the moment for bold leadership, decisive action and a relentless focus on transformation.
