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Our second Data & AI Symposium brought together industry leaders from across Financial Services and Energy to focus on practical AI adoption, risk management, and how to maximise business value, providing delegates with invaluable insights to bring back to their organisations. The discussions emphasised the growing urgency for businesses to adopt AI-driven solutions as innovation accelerates, while speakers also highlighted strategies to unlock AI’s true potential and drive measurable outcomes.
In their opening remarks, Director of Energy & Utilities James Houlton and Director of Financial Services Andre Nedelcoux emphasised that AI adoption among customers is expanding rapidly, and its impact is accelerating. They noted that this increasing urgency reflects the significant role AI now plays in driving business transformation. For industries like energy, AI is poised to play a vital role in enhancing efficiency, forecasting, and decision-making.
AWS’ David Elliott captured the pace of technological change by describing today as "the slowest day of the rest of your life," underscoring how fast innovation is moving. This sentiment reinforced the importance of helping businesses understand AI’s value and encouraging adoption among those who remain sceptical about its benefits.
Here are the key takeaways from each of the day’s sessions.
The session explored the growing role of Agentic AI, emphasising the balance between autonomy and control. While Agentic AI enables powerful autonomous decision-making, clear oversight mechanisms are essential to ensure systems align with business goals and risk appetite. The panel defined agentic AI as a multi-modal system that can overcome obstacles, explain its actions, and adapt to evolving challenges.
Speakers highlighted the transformational potential of Agentic AI systems that can self-correct and respond dynamically. Icebreaker One CEO Gavin Starks shared insights on using agentic AI to reduce the risk of green lending by integrating smart meter data with banks to provide trusted insights, while David Elliott described how AWS saved 10,000 man-hours through technical automation. Panelists stressed that starting with smaller, well-defined use cases is crucial to successful adoption.
Trust emerged as a key theme, with panelists noting its importance in building AI-enabled systems. Creating trust requires strong governance, senior support, and cross-functional collaboration. Lloyds Banking Group’s Head of Intelligent Automation, Huw Jones, emphasised that understanding customer intent is a core requirement for effective Agentic AI, ensuring solutions align with business objectives and deliver meaningful outcomes.
AI’s potential extends far beyond improving efficiency. While automation offers immediate gains, businesses that focus solely on cost savings risk missing out on AI’s broader impact. Samuel Young from the Energy Systems Catapult had five key takeaways to unlock real value, covering how organisations should prioritise AI initiatives that align with long-term business objectives and drive strategic outcomes.
By shifting the focus from efficiency alone to innovation and strategic outcomes, businesses can harness AI’s full potential to drive long-term growth and impact.
Head of Architecture, Data & Analytics Oli Bage shared that combining data, analytics, and AI controls early ensures both security and business continuity for the London Stock Exchange Group (LSEG).
Discussing how to actively manage risk around AI and analytics, Oli told of his experience creating cloud data management controls. He told the story of cross-industry collaboration to understand governance controls, summarising multiple controls into one for hybrid cloud data management, and taking these learnings to build an AI data and analytics control framework.
An industry working group, drawing from existing frameworks definitions and regulatory requirements, defined capabilities and the necessary controls across data analytics and AI. They now have the ability to catalogue and measure quality controls and reproduce results with more detail if necessary based on the expertise of LSEG’s financial analytical and AI modelling products and other industry experts.
"We believe technology is critical for the success of our business, drive operational efficiency and differentiation."
Richard Bruckshaw shared that Schroders’ journey relies on a clear focus on outcomes and educating people along the way. There are clear challenges to get from personal productivity to more commercially impactful use cases and building AI into the end to end workflow of different processes.
Richard shared the Schroders journey of taking AI from idea generation to production, following a structured path through experimentation, proof of concepts, desk solutions, and ultimately enterprise-scale solutions. Each stage presented its own challenges and opportunities, with key blockers including data quality issues, stakeholder buy-in, and integration complexities.
Schroders showcased several successful AI applications, including Custom GPTs used by investment analysts for data analysis, Context AI for qualitative ESG analysis now in production, and Investment Copilot, which is currently scaling up.
These examples highlighted the importance of combining technical innovation with practical business integration to deliver real value. In the long term, Richard raised the impact these new technologies and opportunities will have on the sort of people Schroders and similar enterprises will want to hire.
Dr Roya Ahmadi discussed how NESO’s Volta Programme is looking to leverage AI to help Great Britain’s electricity control room manage grid stability and help enable the clean energy transition.
There is a pressing need to enhance the transparency of decisions made in the control room, especially within a complex and diverse energy mix. Volta aims to address this by utilising smart, adaptive models powered by machine learning and innovative optimisation techniques. These models will improve the effectiveness of the balancing mechanism at a lower cost in an increasingly complex system that incorporates more renewables and distributed energy resources. Furthermore, by embedding explainability into the system, Volta will empower operators with enhanced situational awareness and automated support. This approach enables continuous learning and performance improvement over time, ensuring operators can make more informed decisions.
There have been a number of key drivers for this innovation - situational awareness of the control room, helping operators handle increasingly complex and uncertain scenarios, and reducing system costs chiefly among them.
In the long-term, Roya envisions AI playing a proactive role in assisting control room operators by developing and recommending scenarios. With a fundamental understanding of the system, these AI models can analyse thousands of potential scenarios and suggest the most likely ones. This capability can significantly enhance decision-making processes and operational efficiency.
Our final session heard insights from Northern Trust’s Jez Davies, Schroders’ Peter Jackson, EnBW’s Dean Eaves and Convex’s Steve Perry on the growing importance of data strategy. They shared how the key to a successful data strategy lies in aligning initiatives with business goals and focusing on value creation over technical complexity. Clear metrics are essential to demonstrate impact.
Data's growing strategic importance has elevated data leaders to decision-making roles, expanding their remit to include product and communications teams. Strong data literacy is vital, ensuring teams can leverage insights effectively.
To succeed:
With rising boardroom demand for data insights, there’s an opportunity to revitalise data strategies and achieve lasting impact. Remember: Bad data in, disaster out – data quality is crucial.
The Data & AI Symposium 2025 highlighted key strategies for unlocking AI and data’s potential, with a focus on practical adoption, business alignment, and risk management. Key takeaways included:
By combining technical innovation with practical business integration, organisations can harness AI and data to improve efficiency, drive growth, and remain competitive in rapidly evolving industries.
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