Every year, the Tech Vision report offers a compelling lens into the future of technology, and for its 25th anniversary, the insights are more relevant than ever—especially for those of us in insurance. This year’s theme, AI: A Declaration of Autonomy, captures a world in transition, shaped by artificial intelligence that’s becoming more integrated, more embodied, and more personal.
Among the four key trends outlined—The Binary Big Bang, Your Face in the Future, When LLMs Get Their Bodies, and The New Learning Loop—it’s the last one that truly stands out for the insurance industry. The New Learning Loop explores how AI can be harnessed to create a dynamic, virtuous cycle of learning, leading, and co-creating. For insurers, this isn’t just a nice idea—it’s a blueprint for real, sustainable innovation.
Trust as the Engine of AI Adoption in Insurance
Trust is not a buzzword in insurance. It’s the product.
Insurance is a promise—a contract to support people during their most vulnerable moments. Customers don’t just buy coverage; they buy certainty. They buy peace of mind. They buy trust. That emotional transaction is most obvious at the moment of truth—when a claim is filed. If the claim is handled with care, speed, and fairness, trust is reinforced. If it isn’t, the relationship fractures, and reputational damage follows.
Now, as generative AI moves into underwriting, claims processing, and customer service, we have to re-earn that trust—this time inside our organizations. Our employees must believe in AI as a trusted partner. Otherwise, adoption stalls, innovation flatlines, and competitive advantage evaporates.
In our experience at DOXA, this is why AI programs must be built with people at the center. According to industry-wide research, 74% of insurance executives believe that only by building trust with employees will organizations fully unlock the value of automation powered by generative AI. We couldn’t agree more.
This trust leads to a virtuous cycle: the more employees trust and use AI, the better the technology becomes. As the technology improves, adoption grows. And with more widespread adoption, innovation accelerates. It’s a feedback loop that transforms how we work, what we offer, and how we win.
From “Human in the Loop” to “Human on the Loop”
For AI to thrive in insurance, it must start as a collaboration—not a replacement.
That’s why we’re seeing a shift from “human in the loop” to “human on the loop.” In the early stages of AI adoption, humans need to be deeply embedded in the process: auditing results, fine-tuning models, and identifying ethical risks. But as the systems mature and trust grows, the role of the human shifts to one of oversight and orchestration.
This evolution doesn’t replace people—it empowers them. With AI handling repetitive or low-value tasks, employees can focus on judgment-based decisions, customer relationships, and strategic growth initiatives. In fact, 99% of insurance executives expect their employees’ tasks to shift significantly toward innovation in the next three years.
At DOXA, we’ve already seen this transition begin. Claims adjusters using AI for triage don’t just get faster decisions—they get more time to focus on complex cases where empathy and nuance matter. Underwriters using AI-generated insights aren’t being replaced; they’re being augmented, enabling better risk assessment and faster quote generation. AI becomes the co-pilot, not the pilot.
The Bottom-Up Revolution: Tapping into Employee Excitement
Here’s a truth the industry needs to hear: you don’t need to convince your employees that AI is useful.
They already know.
Outside of work, they’re using AI to help their kids with homework, create digital art, and streamline everyday tasks. There’s excitement in the air. The popularity of AI action figures and AI-generated music isn’t trivial—it’s a cultural signal. People are ready to experiment, eager to play, and open to learning.
So instead of pushing AI from the top down, insurers should empower grassroots exploration. Give your teams the tools, training, and permission to experiment. Don’t just hand them a platform—show them the possibilities.
This kind of bottom-up adoption builds real proficiency and long-term engagement. People don’t want to be told why AI is important—they want to discover it for themselves. We’ve seen this firsthand at DOXA. When we enable underwriters, brokers, and claims specialists to explore AI tools like summarization, image recognition, or predictive analytics in sandbox environments, they come back not just more skilled—but more confident and more innovative.
Reinvention Starts With a Learning Loop
At DOXA, we believe that AI is not just a technology shift—it’s a mindset shift. And that shift starts with a culture of continuous learning.
That’s why The New Learning Loop resonates so strongly. It captures the essence of what we aim to build: a cycle where trust, learning, and innovation feed each other endlessly.
It begins with trust—in the technology and in our people. That trust opens the door to experimentation. With every experiment comes a lesson, and every lesson builds capability. As those capabilities grow, so does our ability to innovate. And when innovation becomes the norm, we build stronger relationships with our clients and deliver better outcomes for all.
It’s not just a loop—it’s a flywheel. And once it’s turning, it doesn’t stop.
What’s Next?
At DOXA, we’re already putting The New Learning Loop into action.
We’re embedding AI into every layer of our operations—from underwriting tools that accelerate broker response times to claims workflows that prioritize empathy and speed. We’re investing in training programs that empower employees to co-create with AI rather than compete against it. And we’re fostering a culture where experimentation isn’t just accepted—it’s celebrated.
This isn’t about hype. It’s about building something real. Something responsible. Something that lasts.
If you’re in the insurance industry and looking to explore what AI can do—for your employees, your clients, and your future—let’s talk. At DOXA, we’re not just observing the trends. We’re shaping them.
