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The insurance industry has always been resilient in the face of change, but today's landscape demands more than resilience. It demands transformation.
The integration of AI and digital innovation is reshaping how we operate, drive efficiency, enhance customer experiences, and foster growth. At Genpact, we have spent years decoding how AI can redefine insurance, and my recent conversation with Robert Pick, CIO of Tokio Marine, further sharpened these insights. Our dialogue, fueled by the findings from Genpact and AWS's latest study, Harness the winds of change: How to scale AI and build trust in insurance, brought to light the incredible opportunities AI presents for our industry.
Here are my reflections on the key themes we explored and what they mean for insurers ready to lead this transformation.
Data is the bedrock of AI success
If there's one thing that stands out to me, it's this: AI's power is tied directly to your data. Without the right data foundation, even the most advanced AI solution is just wasted potential. Our research backs this up, showing that 69% of insurers have already adopted AI. But then you hit the roadblocks. Almost 37% of respondents cited poor data quality or availability as a core challenge. That's a big warning sign.
Reflecting on this, Bob shared a pointed observation during our talk. "The major challenges? Data engineering and auditability," he said simply, cutting to the chase. "For generative AI, 2023 was about prompt engineering, but 2024 is focusing on data integrity. The ability to show and validate your work, not just now, but years later, is nonnegotiable in a regulated industry like insurance."
It's a sentiment I couldn't agree with more. Decoding challenges like these starts with recognizing their foundational importance. Insurers can't afford to build on shaky ground. Addressing data readiness isn't just a tech initiative; it's the backbone of everything AI can achieve.
If foundational data issues aren't addressed, progress stalls. The industry risks falling into a cycle of patch-up jobs while leaving transformational gains out of reach.
Driving value across the insurance chain
AI is shifting from concept to action; it is driving real change in tangible ways across customer service, underwriting, and beyond. These are basics now.
AI is also streamlining more complex processes, like submission ingestion and extracting meaningful insights from dense underwriting guidelines. It's thrilling to see how these solutions save time, cut costs, and create room for innovation.
Bob put it well when he said, "Policyholder-facing solutions like chatbots and sentiment analysis are table stakes now." But he didn't stop there. He recognized how AI's power stretches far beyond what's visible on the surface. Whether it's automating steps in underwriting or capturing and preserving institutional knowledge digitally, the incremental improvements AI brings to different processes are reshaping the way we work.
Still, the pitfalls of AI are real. Bias in AI systems. Hallucinations in generative AI outputs. Regulatory headaches linked to auditability. These are real concerns.
But I've always believed that progress doesn't happen without friction. AI is evolving fast, and I'm optimistic about what's coming next. We're nearing solutions that will balance usability with the strict demands of compliance. One thing's for sure, though – AI itself isn't the endgame. What matters is what it enables. Better decisions. Faster insights. Stronger outcomes. That's where the focus needs to be.
Collaboration breeds success
One insight from our research jumped out at me because it echoed challenges I've seen firsthand. While 44% of AI strategies are owned by technical leadership, 85% of use cases sit with business units. That's a gap. And it's one that reinforced my belief that AI doesn't just thrive on aligned goals – it demands them.
As I see it, collaboration is nonnegotiable. Silos within organizations hurt progress more than any technical limitation. And the collaboration can't stop at internal teams either. It's about looking outward. Bob captured this perfectly when he said, "AI is still emergent. Open conversations and shared experiences are invaluable right now." His point resonated deeply. Some of the most groundbreaking advancements in AI come from industries well outside insurance. Learning from their ideas and overcoming the hesitation to step outside our bubble accelerates innovation.
AI, at its core, is a bridge – a way to connect different functions, perspectives, and priorities. It doesn't just live in IT or business units; it unites them. That's why meaningful partnerships inside and outside the organization are vital to scaling AI in impactful ways.
Lessons worth holding on to
Looking at where we are and where we're heading, a few guiding principles stick with me. These lessons, some learned the hard way, have proven their value:
- Don't just chase trends. Technology is exciting, but shiny objects can be distracting. True transformation means sticking to a thoughtful, long-term strategy
- Look beyond the insurance bubble. Inspiration doesn't have to come from within. AI advancements in other sectors can spark groundbreaking ideas in ours
- Collaborate without limits. When diverse perspectives intersect, that's where real breakthroughs happen. Collaboration isn't just valuable; it's essential
Bob offered a reminder during our talk that brings it all back to basics. "Don't make AI the mandate. Make the outcomes the mandate." It stuck with me because it's easy to get caught up in the tech and lose sight of why we're adopting it in the first place. AI isn't the destination. It's the tool we use to get there.
Read Genpact's latest research on how insurance companies can move from AI experimentation to scalable, trust-driven implementations that redefine how business gets done.
