Brokers debate the role of AI in the future

Insurance brokers face an existential question as artificial intelligence reshapes the industry environment. Daniel Lloyd-John, chief executive and founder at HNW broker Broadway Insurance Partners, argues that while tools will evolve, the core craft of broking remains rooted in human interaction and judgment.

The role of human traits

Lloyd-John entered the insurance industry in 2010 with no formal risk experience, joining Aon Global in central London. He was tasked with building relationships with FTSE 100 organisations while mastering a new sector. His success relied on curiosity, hard work, teamwork, and empathy rather than technical knowledge alone. These traits, he believes, remain fundamental to successful broking today.

Professional knowledge and qualifications can be developed through examinations and real-world learning. This process builds confidence and momentum, which must be protected to sustain growth. Development is a shared responsibility between individuals and employers. Staff need to be curious, courageous, and coachable, while organisations must provide structure, coaching, and opportunities for responsibility.

AI as a culture shift

Artificial intelligence represents an important crossroads for the sector. Lloyd-John does not believe AI will replace the craft of broking, as the process is fundamentally a relationship business. Clients with complex risks still need people who understand their circumstances, handle decisions, and apply human judgment. The customer journey is rarely linear and requires empathy and trust—qualities that are not easily commoditised.

What will change is how brokers access information, analyse risk, and execute processes. AI should be viewed as a culture shift rather than just a technology upgrade. Organisations that benefit most will not necessarily be those buying the most tools, but those prepared to redesign their operating models around AI capabilities. This requires change from the top down, involving leadership questioning traditional structures, and from the bottom up, as individuals adapt to new workflows.

As greater leverage drives higher productivity, the gap between those adopting AI-enabled models and those resisting it could widen rapidly. AI can give emerging talent faster access to risk insight, shortening learning curves that previously took years. A young broker should be able to understand an industry and identify risks far faster than was possible when Lloyd-John started his career.

However, faster learning does not mean less talent is needed; it means talent requirements will shift. Broking organisations are expected to place increasing value on all-rounders—relationship-led, commercially minded, empathetic producers who are curious, adaptable, and comfortable using technology. Deep technical expertise remains important, but the ability to combine knowledge with judgment and relationships becomes even more valuable.

Three elements at the heart of broking will not be commoditised by AI: proprietary data, the marketplace, and community. Brokers possess vast information about clients, risks, and claims, operate in a marketplace built on insurer relationships, and benefit from professional networks. The opportunity lies in moving from static to dynamic insight using AI to unlock value across these areas.

Technology alone cannot deliver this transformation. Talent strategies must evolve alongside operating models, covering recruitment, training, coaching, and leadership. Organisations must also avoid removing the experiences through which future brokers develop judgment. If AI undertakes more groundwork, companies will need to create opportunities for staff to observe and understand complex situations.

Despite the technological disruption, the broker is not disappearing. If the industry evolves correctly, AI should make brokers better informed, more responsive, and more productive. This allows them to spend more time on what customers value: building relationships, solving problems, and exercising judgment.