Beyond Energy Community Meetup Edinburgh: Data, AI, and the future of energy 

Conversations at the intersection of technology and transition

Our most recent Beyond Energy community event in Edinburgh brought together practitioners, academics, and innovators from across the sector to explore how data and AI are reshaping the future of energy. Hosted by Adam Sroka, CEO of Hypercube, the evening’s panel discussion created a space for honest conversation, collaboration, and reflection on how technology, trust, and community will drive the next phase of the transition to net zero. 

Together, they shared insights on flexibility, optimisation, AI, and the skills the sector needs for the future. 

Flexibility at the heart of net zero 

Much of the discussion centred on the importance of flexibility. With renewables and electrification transforming the energy system, the ability to shift when and how energy is used is becoming the backbone of decarbonisation. 

Faraz Malik Awan of Zenobe highlighted how data from EV fleets – particularly telematics and charging patterns – can transform demand management. When dozens of buses plug in at once, the impact on the grid can be enormous. But with the right insights, charging can be shifted to align with periods of high renewable generation, turning what might be a strain into a valuable opportunity. 

Building on this, Lars Schewe from the University of Edinburgh stressed that the real challenge lies in decision-making under uncertainty. While deterministic optimisation is relatively straightforward, the reality of energy systems is far messier: weather conditions, consumer behaviour, and market prices are all unpredictable. Models that can capture and work with this uncertainty are critical to making smarter, more resilient decisions. 

From Steve Sinclair’s perspective at Flexitricity, the scale of the challenge is just as important as the complexity. The transition from a few centralised fossil fuel plants to thousands of smaller, distributed assets means that manual oversight is no longer feasible. Automation and AI will be essential to manage this scale effectively and keep the grid balanced. 

AI: Potential and responsibility 

The conversation inevitably turned to AI, and here the panel balanced optimism with caution. Rachel Hassell of SSE Energy Solutions highlighted the paradox that while AI offers huge potential for accelerating the transition, it also drives up demand. By 2050, UK data centre consumption could surpass four times Scotland’s current electricity use. The efficiency and responsibility with which AI is deployed will be as important as the innovations it enables. 

Across the panel, there was broad agreement that the way forward is through narrow, transparent applications of AI rather than opaque general systems. Trust will grow gradually as small, specific tools demonstrate value and safety. Embedding AI in critical infrastructure isn’t just a technical question, but one of governance, risk management, and public confidence. 

Rethinking optimisation 

Optimisation was another theme that provoked lively debate. Too often it is used as a catch-all buzzword, but the panel worked to unpack its complexity. Optimisation is not simply about turning assets off when prices spike; it is a sophisticated interplay of mathematics, physics, and economics. 

There was also recognition that it is not limited to new technologies. Legacy infrastructure, such as combined heat and power plants, can benefit enormously from smarter strategies, lowering both costs and emissions. But perhaps the most important insight was cultural: no matter how sophisticated models and AI are, optimisation depends on trust. Operators, and organisations and end-user customers must believe in the systems before they will hand over real decision-making authority. 

Skills for the future

The panel also reflected on what skills are needed to drive this transformation. Technical expertise remains fundamental, with tools such as Python, PySpark, Kafka, and cloud-based data lakes forming the backbone of modern energy data work. Yet there was an equally strong emphasis on critical thinking – the ability to distinguish between signal and noise in a world increasingly shaped by AI outputs. 

Domain expertise was also highlighted as a defining factor. What distinguishes an energy data scientist from a generalist is not just coding ability, but an understanding of how the grid operates, how markets function, and how assets behave. The most effective people in the field are those who can combine technical skill with judgment and deep sector knowledge. 

One line captured this sentiment perfectly: AI isn’t going to take your job – but someone who knows how to use AI might. 

Building a community around the transition

As the evening drew to a close, the spotlight returned to community. The energy transition is about more than deploying new technologies – it depends on trust, collaboration, and shared understanding to ensure those technologies succeed. No single organisation can solve the challenges of flexibility, optimisation, and responsible AI on its own. 

That’s why the Beyond Energy Community exists. The conversations don’t end when the event does; they continue through a growing community of energy professionals eager to collaborate, exchange ideas, and rethink what’s possible with data and innovation. Join the Beyond Energy Community to stay connected and be the first to hear about future events across the UK.