Neurons Lab and Projective Group brought 50 senior leaders together to look at AI from two sides: the systemic risk it creates for the sector, and the operating model each firm must now choose. The evening also saw the authors of Think Again launch their new paper on AI-era resilience.
LONDON, 28 September 2026
On 22 September 2026, 50 senior financial services, technology and transformation leaders gathered at Projective Group’s London office for AI at the Turning Point: From Systemic Risk to Your Operating Model, an invitation-only evening hosted by Neurons Lab and Projective Group. Registration closed at capacity. The premise was simple: AI is changing financial services faster than the sector’s risk models and operating models can keep up, and leaders need to deal with both at once.
The first panel took the systemic view, and gave its three speakers the stage to launch their new paper, Think Again: Why UK Financial Services Must Act Now on AI-era Resilience, written by Samantha Emery, financial services executive, non-executive director and Independent Director at ClearBank UK; Nadia Edwards-Dashti, Co-Founder and Chief Customer Officer of Harrington Starr Group; and Bill Oates, Cloud and AI Capability Lead at Projective Group.
The second panel took the firm’s view, with Alex Honchar, CTO and Co-Founder of Neurons Lab, joining Oates and Toby Pearson, UK Managing Partner at Projective Group to set out the operating model choices in front of every leadership team. Drinks and networking followed.
The systemic risk: is the sector is about to repeat 2008 at machine speed?
The first panel started with 2008. As Emery, Edwards-Dashti and Oates argue in Think Again, the crisis happened because similar people, trained the same way, checked the same assumptions with the same models, and nobody in the room was positioned to disagree. The authors call this cognitive monoculture.
Their warning is that AI now repeats the pattern at machine speed. When many firms run credit, risk and compliance decisions on the same few foundation models, trained on the same historical data, they share the same blind spots, and the sector takes on a concentration risk that nobody has priced.
The panel’s answer, and the paper’s, is diversity of thought: in who sits on the risk committee, in who designs and oversees the models, and in the technology choices firms make. Drawing on more than 650 recorded executive conversations over five years, the authors show that firms which keep diverse human judgement close to the algorithm catch errors earlier, serve more customers and hold their talent longer.
The authors frame this as a business and resilience case with a diversity dividend, not a compliance exercise. Their manifesto asks for a coordinated, government-backed AI transition plan for the sector, an FCA review of AI in hiring and promotion, executive pay linked to the progression and retention of underrepresented talent, and open access to capital for diverse founders.
The operating model: three ways to run AI, and how to pick yours
The second panel took the audience from risk to action. Honchar, Oates and Pearson set out three ways a firm can run AI today, with the trade-offs of each.
AI-Augmented gives teams copilots and prompt skills, but the process stays the same. It is quick and low risk, and the gains are small: shaving cost from one step of an AML check, for example. AI-Enabled rebuilds a whole workflow around agents that act inside the firm’s own systems, such as an end-to-end AML case handled from alert to decision with people reviewing exceptions. This is where the panel sees most mid-market firms heading in the next 12 months. AI-First redesigns the whole value chain around near-full autonomy. Today only startups run this way, and the panel was clear it is the wrong target for most established firms.
The panel’s message was that the choice is not one-size-fits-all. Operations-heavy work, such as servicing, onboarding and claims, suits deeper automation. Work built on human relationships, such as advice and complex sales, should keep people at the centre. The right answer is set workstream by workstream, and it should be framed as growth: the panel challenged CEOs to grow revenue 10% over three years with the same team, rather than treating AI as a headcount exercise. Speakers drew on implementation lessons from work with HSBC, AXA and Visa, and noted that the EU AI Act now requires firms to train staff before they deploy AI.
Quotes
“Most firms have bought the tools but have not changed the work. The firms pulling ahead will carefully pick a model, build agents on their own stack, and measure the result in revenue, not headcount,” said Alex Honchar, CTO and Co-Founder of Neurons Lab.
“The room was at very different stages, and that was the point. There is no blanket answer. Find out which mode you are really in now and which your firm should aspire too. AI-native is not right for every firm, but it doesn’t mean progress should stall,” said Euphemia Smith, CMO at Neurons Lab, who moderated the evening.
About Neurons Lab
Neurons Lab is a boutique, London-based AI engineering partner focused on mid-market Financial Services firms. With +100 clients in their portfolio, they help organizations adopt AI through custom agentic builds and AI adoption programs, from use case to complete production-grade systems in 12 weeks.
Financial institutions are not constrained by awareness, but by execution within daily workflows, governance, and risk. Neurons Lab closes that gap by enabling teams to apply AI in practice and building systems designed for production from day one — integrated into existing infrastructure, aligned with governance, and built to scale.
About Projective Group
Projective Group is a consultancy that works only in financial services. Founded in Belgium in 2006, it now has more than 1,000 practitioners in 10 offices across Europe, including London, Brussels, Amsterdam, Paris and Frankfurt, and serves more than 200 clients in banking and payments, insurance, capital markets and financial market infrastructure, asset and wealth management, and pensions.
Its services span strategy, transformation, data and AI, payments, legal, risk and compliance, managed services, staffing and training, delivered by practitioners with direct industry experience. Projective Group is recognised across the European industry for turning complex challenges and emerging themes into clear, practical solutions.
