The hum of conversation at this year’s ITC London conference was punctuated by a single, potent term that promises to redefine the entire insurance landscape: agentic AI. As this technology moves swiftly from an industry buzzword to an operational reality, it poses a central question about the future of the insurance professional. Senior technology and insurance executives gathered to debate whether this shift represents an existential threat or an unprecedented opportunity for brokers. The consensus that emerged was clear: while AI agents are set to fundamentally reshape workflows and compel a complete rethinking of operational models, human expertise will not only remain relevant but will become even more critical within these new business structures.
An Industry on the Brink of an AI Driven Transformation
The primary topic of discussion at ITC London centered on the tangible impact of agentic AI. The debate is no longer about if these autonomous systems will integrate into the insurance sector, but how they will transform it. For brokers, this transformation forces a re-evaluation of their core value proposition. As AI begins to handle the administrative and data-intensive aspects of the role, the question becomes what uniquely human skills will define the broker of the future. The prevailing view among industry leaders is that this shift is not a distant possibility but an imminent evolution that demands immediate attention and strategic planning.
This sense of urgency is driven by a shared understanding that the industry is approaching an inflection point. The current operational models, built around manual processes and human-centric data analysis, are becoming increasingly inefficient in a world of exponential data growth. The consensus from the conference is that a fundamental reshaping of insurance workflows is not just possible, but inevitable. This transition is expected to redistribute value across the insurance chain, moving it away from repetitive task execution and toward strategic insight and complex relationship management, placing the onus on firms to adapt or risk being left behind.
The Technological Shift Understanding the AI Evolution in Insurance
To understand the scope of this change, it is crucial to recognize the technological progression that has brought the industry to this point. Magdalena Ramada Sarasola, global insurtech innovation lead at WTW, outlined a three-phase evolution. The initial phase focused on automating repetitive processes, followed by a second phase dedicated to augmenting human capabilities with AI-powered tools. The industry is now entering the third and most disruptive phase: the era of autonomous systems. This signifies a monumental leap from tools that execute predefined tasks to intelligent agents capable of more independent, context-aware decision-making within specified domains.
Despite these rapid advancements, a dose of realism is necessary. Sarasola introduced the concept of an “80/20 reality” to describe the current state of AI capabilities. Today’s systems excel at handling the 80% of tasks that are data-intensive and repetitive, such as extracting information from submission documents or pre-populating underwriting files. However, they consistently struggle with the final 20% of cases that demand nuanced human judgment, deep contextual understanding of ambiguous risks, and complex decision-making, especially in specialized commercial lines. Fully autonomous decision-making remains a distant goal, with technical hurdles in abstraction and sensory processing likely taking more than a decade to overcome.
More Than Efficiency How AI Is Triggering a Business Model Revolution
The adoption of transformative technologies like AI typically occurs in two distinct phases, as explained by Juan de Castro, COO of Cytora. The first phase involves using new technology for incremental improvements—making existing processes faster or cheaper. For the past few years, the insurance industry has largely operated within this phase, applying AI for marginal gains without fundamentally altering core workflows that were designed around the constraints of older, human-driven systems.
The second, more profound phase of adoption occurs when the technology enables entirely new operating models that were previously inconceivable. De Castro offered a powerful analogy with Rolls-Royce, which first used sensor technology to make engine maintenance more efficient before completely reinventing its business to rent engines on a “power-by-the-hour” basis. This business model revolution was only possible because of the new technology. The insurance industry now stands at the cusp of its own Phase Two, with the potential to move beyond simple efficiencies and redefine core processes from the ground up.
Expert Perspectives on the Evolving Role of the Broker
A concrete example of this redefinition is found in broker placement workflows. De Castro illustrated how an AI agent can analyze a complex risk, instantly identify the most suitable carriers, and automate the time-consuming communication required to clarify information. This frees the human broker from administrative burdens, allowing a single individual to approach a much wider market with minimal additional effort. The result is not only greater efficiency but also more competitive and comprehensive outcomes for the client, shifting the broker’s role from a processor of information to a strategic advisor and market navigator.
Furthermore, the recent advancements in large language models (LLMs) are turning long-held industry ambitions into practical realities. Concepts like machine-readable policies and computable contracts, which once required months-long projects, can now be executed dynamically. Sarasola highlighted how this capability unlocks opportunities for deeper, real-time integration across pricing, claims, and reserving functions. This interconnectedness allows for a more holistic and accurate view of risk, enabling brokers to provide more sophisticated advice and carriers to develop more precise products.
Navigating the Transition A Framework for Future Proofing the Workforce
Despite the technological promise, the most significant barriers to AI adoption are not technical but human. Panelists at the conference consistently identified cultural resistance to change, persistent data quality issues, and a critical shortage of skills as the primary obstacles. Scott Sayce, chief innovation officer at DUAL Group, emphasized that a company’s culture and talent are the ultimate determinants of success. With a large segment of the experienced insurance workforce nearing retirement, there is an urgent need to capture their institutional knowledge before it is lost.
Successfully navigating this transition requires a strategic approach that positions AI as a “teammate,” not a replacement. This framing is essential for managing the change and retaining experienced professionals who may feel threatened by new technology. Firms must foster a culture of adaptation, invest heavily in upskilling their workforce, and clearly define the evolving responsibilities of their brokers. The most valuable skills in this new era will be those that AI cannot replicate: strategic risk advisory, complex negotiation, and the cultivation of deep, trust-based client relationships.
The discussions at ITC London painted a clear picture of the road ahead. The integration of agentic AI was not seen as the end of the insurance broker but as the dawn of a new, more strategic iteration of the role. The key takeaway was that the industry’s future success would depend less on the sophistication of its technology alone and more on its ability to cultivate a workforce capable of leveraging that technology to deliver unparalleled human insight and value. By embracing AI as a collaborative partner, the insurance industry had the opportunity to enhance, not supplant, the invaluable expertise that has long been its foundation.
