In just a few months, Agentic AI has become one of the most talked-about developments in insurance technology. Once seen as a distant concept, it’s now driving real conversations about how insurers work, decide, and deliver value. Unlike traditional automation, which executes predefined steps, Agentic AI introduces systems capable of reasoning, adapting, and taking the next best action autonomously. A shift from following rules to understanding intent.
This was the core theme of a recent InsTech webinar, “Agentic AI: Friend, Not Foe,” sponsored by OIP Insurtech. The panel – Mladen Subašić (Chief Product Officer, OIP Insurtech/Bound AI), Christina Lucas (Global Insurance Market Leader, Google), and Ulf König (Head of Innovation & Strategy, HDI Global) – unpacked the hype, the practical realities, and the road ahead.
Their shared message was clear: Agentic AI isn’t about replacing people but augmenting human capability. Underwriters, claims handlers, and brokers will get intelligent assistants that understand the context, act autonomously within guardrails, and free up experts to focus on what really matters.
AI agents don’t just analyze. They act. That’s the real leap forward. – Mladen Subašić, OIP Insurtech
The conversation marked a turning point in how the industry defines efficiency. Not by how fast tasks are automated, but by how seamlessly humans and AI can collaborate to make better decisions, faster.
Where Agentic AI Is Already Delivering Value
For years, insurance automation was largely about removing manual steps, extracting data, routing submissions, and populating systems. But Agentic AI goes further. It processes information, understands context, and takes the next step in a workflow, creating a bridge between human decision-making and autonomous execution.
As Christina Lucas of Google explained during the webinar, early AI applications focused on prediction, risk forecasting, fraud identification, and loss estimation. Agentic AI, however, is action-oriented. It moves from “what might happen” to “what should happen next,” enabling insurers to handle complex, dynamic tasks that once required constant human oversight.
That shift is already visible in several high-impact areas:
- Fraud and claims analysis: AI agents can process multimodal data — voice, video, documents — to detect anomalies, cross-reference networks, and flag potential fraud in real time.
- Underwriting intelligence: By combining first-party loss history with property, weather, and third-party datasets, agents surface insights faster and more accurately than legacy systems ever could.
- Submission management: As Mladen Subašić noted, autonomous agents can now ingest submissions, identify missing documents, trigger requests to brokers, and even compare quotes across markets, all without expanding headcount.
At HDI Global, Ulf König described why underwriting was their first focus. It’s where the highest labor intensity and the most potential for ROI reside. Starting there allowed HDI to test Agentic AI in measurable, high-value scenarios before scaling.
The result? A growing body of proof that Agentic AI isn’t theoretical. It’s already cutting processing times from days to hours, improving risk selection, and freeing specialists to focus on higher-value analysis. What was once “automation” is evolving into intelligent collaboration, with machines and humans moving in sync.
From Pilots to Scale: Making AI Work in the Real World
Most insurers today aren’t struggling to start with AI but to scale with it.
The InsTech panelists agreed: moving from a handful of successful pilots to enterprise-wide adoption requires more than enthusiasm. It demands data discipline, governance, and the right partnerships.
As Ulf König from HDI Global put it, no insurer should try to build everything in-house. True impact comes from combining the technical depth of hyperscalers like Google with the domain expertise of specialized partners who understand insurance workflows. These collaborations help ensure that AI tools are not just powerful but also compliant, explainable, and aligned with business realities.
Christina Lucas emphasized the importance of grounding data, training AI on verified, trustworthy sources to avoid “hallucinations” and ensure reliability. Without a solid data foundation and human oversight, scaling Agentic AI responsibly becomes nearly impossible.
Meanwhile, Mladen Subašić highlighted a critical but often overlooked point: insurers must own their context. The models may come from vendors, but the workflows, data logic, and decision frameworks must remain internal. That’s the real competitive moat, not the technology itself, but how it’s applied to a carrier’s unique way of doing business.
Ultimately, scaling Agentic AI isn’t about bigger models or flashier tools. It means building maturity and creating systems that can evolve, adapt, and integrate into everyday operations without disrupting trust, governance, or human control.
Humans in the Loop: The Real Competitive Edge
Despite its autonomy, Agentic AI isn’t designed to replace people but to amplify them. All three panelists reinforced that the success of AI in insurance depends less on algorithms and more on how humans and agents learn to work together.
As Ulf König pointed out, introducing Agentic AI isn’t a tech rollout but a change management challenge. When 5,000 employees must adapt to new workflows, communication styles, and interfaces, the human factor becomes five times more important than the IT investment itself. “You can’t underestimate the cultural shift,” he noted. “People need to trust the agents they’re working with.”
That trust begins with transparency. Agents need to explain their actions, provide auditable trails, and invite human validation where judgment matters most – in risk selection, claims resolution, and customer interactions.
Mladen Subašić added that progress depends on balance: start small, equip “productivity champions,” and scale from proven use cases. The goal isn’t to create one all-knowing system. Still, a network of reliable digital co-workers that handle repetitive tasks, surface insights, and empower people to focus on decisions that require expertise and empathy.
As Christina Lucas summarized, the future of insurance isn’t about man versus machine but about shared intelligence. The real transformation happens when AI and human teams operate as one, each complementing the other’s strengths.
A New Blueprint for Insurance Operations
The InsTech session made one thing clear: Agentic AI is a new operating model for insurance.
In the near future, underwriters, claims specialists, and brokers won’t spend their days transferring data between systems. Instead, they’ll collaborate with digital agents that anticipate needs, act across applications, and maintain full auditability. Efficiency will no longer mean faster clicks. It will mean fewer clicks altogether.
As Mladen Subašić emphasized, this evolution is less about technology and more about redefining workflows. Insurers that focus on business outcomes – accuracy, transparency, customer trust – will pull ahead of those chasing the next shiny tool. Agentic AI enables that shift from process execution to strategic enablement, giving human teams more time for analysis, creativity, and client relationships.
At OIP Insurtech, this transformation is already underway. From underwriting to operations, our teams are deploying intelligent agents that learn from real insurance data and adapt to each client’s unique process. The goal is to build a foundation for autonomous collaboration, where technology quietly handles the repetitive tasks and humans lead with expertise.
Agentic AI may still be young, but its direction is unmistakable. The insurers who embrace it responsibly, with transparency, data governance, and human partnership, won’t just keep pace with change.
They’ll define what “smart insurance” means in the decade ahead.
