AI’s Transformative Impact on Insurance: Reflections from Insurity’s Excellence in Insurance Event

Last week, I had the privilege of attending Insurity’s Excellence in Insurance event, and I left with a fundamentally shifted perspective on how artificial intelligence (AI) is reshaping our industry. What struck me most wasn’t the technology itself, it was the palpable sense of urgency and opportunity that filled every conversation, panel discussion, and hallway exchange. 

The Excel Moment Has Arrived 

During the AI Revolution Roundtable, someone made a comparison that perfectly captured what we’re experiencing: AI tools like ChatGPT are having the same democratizing effect on business that Excel had decades ago. Back then, suddenly everyone could create reports and analyze data without waiting for IT. Today, AI is putting sophisticated analytical and creative capabilities directly into the hands of insurance professionals. 

But here’s the critical difference: unlike Excel, which many organizations simply deployed without strategy, the insurance leaders I spoke with are approaching AI more thoughtfully. They’re not asking whether to adopt AI—that question has been answered. Instead, they’re wrestling with how to do it strategically, safely, and at scale. 

Beyond the Hype: Real Use Cases Delivering Real Value 

The most compelling moments at the conference came when people shared tangible results. One implementation partner described a client who budgeted a million dollars and a year to relaunch a product. With the right platform, they accomplished it in 60 days and saved $750,000, including the license fee. After successfully repeating this three more times, the client committed to replatforming their entire product suite. 

Another presenter discussed reducing policy audit processes from 4-6 hours to less than 30 minutes through intelligent automation. These aren’t hypothetical benefits or pilot projects – they’re production systems delivering measurable ROI today. 

What became clear across multiple sessions is that AI’s value in insurance isn’t primarily about replacing humans. It’s about augmenting our capabilities in three key areas: 

• Operational Efficiency: Automating repetitive, manual processes that consume valuable time – policy checking, submission intake, compliance document generation – freeing professionals to focus on judgment-based work that truly requires human expertise. 
• Data Intelligence: Extracting insights from the massive volumes of unstructured data trapped in documents, emails, and legacy systems. As one panelist noted, insurance is fundamentally a “paper pushing” industry, and AI excels at making sense of documents. 
• Error Reduction and Risk Mitigation: One striking example involved an AI platform that identified a $190 million annual error in a major pension plan’s calculations, which was an error that had persisted for over a decade. When applied to compliance-heavy processes like claims denial letters, AI systems are demonstrating higher compliance rates than traditional human-driven approaches. 

The Governance Imperative 

Perhaps the most mature conversation throughout the event centered on governance. There was universal recognition that simply deploying ChatGPT or Copilot across an organization isn’t a strategy—it’s a recipe for chaos. 

The smartest approach I heard came from several organizations following a similar playbook: 

1. Enable broadly but govern tightly: Provide AI tools to employees while implementing clear guardrails around data security and appropriate use 
2. Create innovation spaces: Establish “champion” programs or incubator teams where controlled experimentation can happen 
3. Identify high-value use cases: Focus AI implementation on specific pain points with measurable business impact 
4. Build for the ecosystem: Ensure AI solutions integrate seamlessly with existing platforms and workflows 

One participant’s million-dollar AI budget breakdown resonated with many in the room: invest in licenses and access, establish data governance frameworks, fund training and education, and create innovation teams. Notably absent from that list was a multi-year IT project. The consensus was that the traditional approach of lengthy requirements gathering and development cycles doesn’t match the pace of AI advancement. 

The Agentic Future 

The most forward-looking discussions centered on agentic AI—systems that can autonomously execute complex, multi-step workflows. While we’re still in early stages, the potential applications in insurance are vast: 

• Continuous monitoring of market trends and competitor activities 
• Automated policy checking and underwriting guideline validation 
• End-to-end claims processing with human oversight only for exceptions 
• Compliance checking where AI agents verify the work of other AI systems 

One panelist posed a provocative question: “Will agents be transacting insurance, and how soon?” The room’s response was telling. A year ago, this would have seemed far-fetched. Today, with the rapid pace of model improvements, many attendees believed we could see agent-to-agent transactions within a few years. 

The Human Element Remains Central 

Despite all the AI enthusiasm, every session reinforced that humans remain essential—just in evolved roles. The legal and ethical considerations are too complex for pure automation. As insurance professionals, we need to ensure AI systems don’t inadvertently discriminate or create unintended consequences. 

The most successful implementations I heard about all maintained “humans in the loop” at critical decision points. But those humans are increasingly supported by AI that handles the heavy lifting of data processing, analysis, and initial recommendations. 

Getting Started: Practical Takeaways 

For organizations wondering where to begin with AI, the event provided clear guidance: 

• Start with foundations: Ensure your data is clean, accessible, and properly governed. AI is only as good as the data it works with. 
• Train your people: Don’t assume everyone understands how to prompt AI systems effectively or recognizes their limitations. Invest in education. 
• Think vertically: Identify specific bottlenecks in your operations and apply AI to solve those problems. Don’t try to boil the ocean. 
• Measure relentlessly: Establish clear baselines and KPIs so you can demonstrate actual value, not just theoretical benefits. 
• Partner strategically: The insurance tech ecosystem is rich with specialized solutions. You don’t need to build everything yourself. 

Looking Ahead 

What I found most energizing about the Excellence in Insurance event was the collaborative spirit. Yes, we’re competitors in many ways, but everyone recognized that AI represents such a fundamental shift that sharing insights benefits the entire industry. 

The winners in this AI revolution won’t necessarily be those with the biggest budgets or the earliest starts. They’ll be the organizations that move quickly but thoughtfully, that embrace experimentation while maintaining appropriate controls, and that keep their focus squarely on delivering value to customers. 

As I reflect on everything I heard and learned, one thing is certain: AI isn’t coming to insurance—it’s already here. The question isn’t whether to engage with it, but how quickly and effectively we can harness its potential while managing its risks. 

The conversations I had at this event will inform my approach for months to come. If you couldn’t make it this year, I highly recommend attending next time. And in the meantime, don’t wait. Start your own AI experiments today. The learning curve is steep, but the opportunity cost of waiting is steeper still. 

What’s your organization doing with AI? I’d love to hear about your experiences and challenges. Let’s continue the conversation.