Systems Thinker Modernising Insurance Leadership
Artem Gonchakov
CEO
Simplify
Systems Thinker Modernising Insurance Leadership
Artem Gonchakov
CEO
Simplify
For decades, insurance operations have been defined by documentation, manual review, and long processing cycles. Today, a new generation of AI systems is beginning to challenge that structure by shifting automation from isolated tools to intelligent agents capable of managing entire workflows. At the centre of this shift is Artem Gonchakov, CEO of Simplifai, who is working to build what he describes as the world’s first agentic insurance system.
Gonchakov’s approach is rooted in a career spent navigating the intersection of technology, finance, and large-scale operations. From leading transformation initiatives at WorkFusion to managing strategic regulatory programs at Deutsche Bank, he developed a systems-driven understanding of how complex institutions operate and where they break down. At Simplifai, he is applying those lessons to redesign how claims are processed and decisions are made. During an exclusive conversation with TradeFlock, Gonchakov shared his perspective on building AI systems that insurers can trust.
How has your engineering background shaped the way you approach complex AI and insurance challenges?
My engineering background trained me to think about systems before jumping to solutions. In computer science, you quickly learn that complex systems rarely fail at the edges. They fail at the interfaces where assumptions break and information moves between components. That perspective strongly shapes how I approach insurance operations today.
Claims processing is often treated as a single workflow problem, but in reality, it is a network of decisions, handoffs, data sources, and human judgment. Before introducing AI, the first step is to understand how the system behaves and identify where friction, delays, or errors occur.
Two lessons from engineering still guide my thinking. The first is that data quality determines outcomes. Even the best models fail on weak inputs. The second is designing for failure, building escalation paths and transparency so AI systems remain reliable even when conditions are imperfect.
How do you see autonomous AI agents transforming underwriting, claims, and customer trust in the coming years?
The most significant shift ahead is that AI will move from being a tool to becoming an active participant in operational workflows. Today, most systems analyse documents and present insights to human decision makers. In the coming years, AI will handle much larger portions of the process.
In claims, an AI system could review a case, identify missing information, request documentation, evaluate responses, and prepare recommendations before escalating complex situations to human experts. Claims professionals will increasingly supervise the process rather than execute every step manually.
This shift can significantly reduce operational timelines. Straightforward claims that currently take weeks could be resolved within hours, while fraud detection may occur earlier in the lifecycle. Ultimately, success will depend on trust, which means AI systems must remain transparent and explainable so customers understand how decisions are made.
What advice would you offer future business leaders building companies in AI?
My advice is to choose a specific problem and stay with it long enough to truly master it. The instinct for ambitious leaders is to expand quickly into multiple markets or products because breadth can feel like progress. In reality, the most successful AI companies achieve depth before scale.
Deep expertise in a single domain allows a company to understand complexities that outsiders often miss. It enables faster iteration, stronger products, and greater customer trust. Over time, each deployment teaches lessons that competitors cannot easily replicate.
That accumulated knowledge becomes a competitive advantage that compounds over the years. The real challenge is resisting the temptation to broaden too quickly. The companies that endure are usually the ones that remain focused on solving one problem better than anyone else.
How do you stay ahead of rapid technological change while maintaining focus on core priorities?
Technology evolves quickly, but not every advancement changes what a business can fundamentally accomplish. I try to filter new developments by asking a simple question: Does this expand what insurers can achieve with claims, or does it simply change how the technology is built?
Most innovations fall into the second category. They improve efficiency or implementation without transforming the customer outcome. Occasionally, however, a shift appears that genuinely expands what is possible. The emergence of agent-based AI systems is one example, because it allows AI to participate more actively in operational workflows rather than just analyse information.
Staying close to the product helps me recognise those moments. I spend time reviewing architecture decisions, participating in product discussions, and speaking directly with customers about where systems fail in real deployments. That proximity keeps strategy grounded in operational reality rather than industry narratives.
What personal discipline has helped you remain resilient in industries as fast-moving as AI and insurance?
One habit that has helped me consistently is writing before speaking. Writing forces clarity in a way that conversation often does not. When I am evaluating a strategic decision or thinking through a product direction, I write my thoughts down first. That process usually exposes gaps or assumptions that were not obvious at the beginning.
Another discipline is learning not to become attached to previous decisions. In fast-moving environments, defending an outdated position often costs more than adjusting course. When new information challenges a decision, I prefer to update my perspective rather than protect the earlier call.
Resilience often comes from separating your identity from your decisions. Leaders who feel they must always be right struggle to adapt. Remaining open to new evidence allows both individuals and organisations to keep evolving.
