Sona's chief operating officer on why AI adoption is about people, not technology
James Potter joined Sona as chief operating officer when the brokerage had only a handful of clients. Three years later, it has grown to roughly two thousand clients and generates millions in gross written premium across two locations. His role in that growth has meant steering the company through AI adoption, digital product development, and a shifting claims environment-while maintaining a core principle: people matter more than the technology.
Potter did not plan a career in insurance. A family member suggested the sector after his education, and he stayed for its variety. Over 18 years, he has worked on both sides of the market: as a broker handling specialist high-net-worth motor schemes and wealthy private clients at Lockton and Marsh, and later in underwriting at Hiscox before roles at Towergate, NFU Mutual, and Gallagher.
Future-proofing a traditional broker
At Sona, Potter describes the company's digital strategy without sentiment. It is simply "future proofing the business." That strategy has two tracks: internal AI adoption and digital products for customers.
The firm remains a conventional manual broker built around phone calls, emails, and personal client contact. But it is also developing specialist products that customers can buy online without routine human intervention.
The case for internal AI was practical. Potter says the goal was to eliminate "manual, lengthy processes" that consumed time without adding value to client relationships. One example: repetitive "to whom it may concern" letters that could take an hour and a half to produce without meaningfully improving outcomes.
Sona adopted ChatGPT with an enterprise subscription for all staff, following initial discussions through the Willis network of independent brokers.
Compliance came first
For a regulated intermediary, AI implementation quickly becomes a question of control. Potter says compliance was Sona's "first hurdle." The company adapted a risk-management framework with Willis's help, using a pragmatic test: compare the consistency of machine output against the notional human error rate, while keeping a human final check in place.
Data handling remains cautious. Sona uses AI in a relatively manual way and does not input personal data into systems. Staff are instructed to use the company's approved enterprise subscription rather than personal tools and never to submit personal information. The reasoning is direct: enterprise plans may promise not to use customer data for model training, but the broader behavior of such systems remains insufficiently understood for a broker handling sensitive client material to be relaxed about it.
AI as an inclusion tool
Potter frames AI not just as an efficiency tool but as an inclusion tool. For staff with dyslexia or ADHD, AI can provide immediate support with rereading, checking, grammar, and common errors. This reduces reliance on colleagues and helps them operate "on a level playing field."
That matters in an industry facing a demographic problem. Insurance faces repeated warnings about retirement-led attrition over the coming decade. Potter argues that AI may help widen the available talent pool by making more roles accessible to people with strong interpersonal or analytical strengths who might otherwise be disadvantaged by conventional written processes.
Sona's message to staff was clear: this was "an investment in you guys," not a precursor to redundancy. Younger employees were often quick adopters. Others needed more persuasion, but the honest pitch mattered. Refusing to engage with such tools would leave them behind in the next phase of work.
Infrastructure as constraint
Like much of the broking market, Sona depends on Acturis, which Potter calls the dominant platform in the sector. It offers the best e-trade facilities and the stability that comes from being the established choice. But it also acts as a brake on change. Broking will move materially faster only when AI functionality is embedded in the core system itself.
Sona's answer is not to wait. The company has pushed innovation into adjacent areas, particularly through niche digital products.
Specialist products: ComicSure and probate
The most developed product is ComicSure, a collectors' insurance proposition for comic books. Sona's chief executive, Rob Thacker, is a serious collector, but beneath the origin story sits solid underwriting logic. Comic books are specialist assets whose value is not easily captured by standard household insurance. A product built on knowledgeable valuations rather than generic receipts makes commercial sense.
Sona spent roughly 12 months developing ComicSure, drawing heavily on the University of Essex business community-local marketing firms, data specialists, AI companies, and Insurtech contacts. Potter credits the surrounding network with helping leadership understand change.
A second initiative is earlier in development: an unoccupied-property probate product. The target customer is the executor or solicitor managing a property after a death, when insurance is usually one more distressing administrative burden. Sona began work six weeks before Potter's interview and hopes to launch this year.
Sona is not attempting to become a mass-market digital insurer. It is looking for specialist spaces where expertise, service, and narrow product design combine into something commercially useful.
Leadership must understand change
Potter is skeptical of grand transformation rhetoric and equally skeptical of leaders who sponsor change they do not understand. Digital transformation "can only really take place when the leadership understands it." Senior teams have to go first: learn it, use it, and explain it. Otherwise, change programmes stall in the gap between aspiration and comprehension.
That argument will resonate in the commercial insurance market, where many firms remain caught between top-down innovation language and bottom-up practical constraints. Transformation succeeds only when it is translated into how people actually work.
Claims as the next test
Potter is especially interested in the rise of AI agents in claims. His concern is not that they are impossible, but that the claims journey often depends on interpretation, context, and specialist advice rather than simple task execution. He wonders whether insurers will confine AI to first notification of loss or push it deeper into the process, and whether that may strengthen the broker value proposition for clients who do not want to argue a complex interruption or coverage issue with a machine.
For all the emphasis on automation, Potter's instincts remain brokerish. Technology may alter workflows, improve consistency, and generate niche products. But his underlying thesis is straightforward: when risk becomes messy, clients still want somebody in their corner.
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