Chris Lane, Managing Director, of SystemsLink – the UK’s industry-leading utilities, carbon and analytics management software provider.
In case you couldn’t make it in person to SystemsLink’s Roadshows, this year’s theme was “Energy Management and Artificial Intelligence” – which truly resonated with organisers and attendees alike.
At these Roadshows the SystemsLink team premiered something we have been working very hard on: The next generation of our flagship energy management software “daisy” (the clue is in the name!).
What’s more debuting daisy allowed SystemsLink to introduce our audiences to the concepts of generative, agentic and predictive AI. Crucially, we could showcase that these types of solutions can only work well if humans and machines can communicate easily. Therefore, these should be powered by a domain-trained Large Language Model (LLM).
But what do I mean by trained? Well-established LLMs ensure Generative AI such as Chat GPT and Gemini are wholly intuitive in their use of natural languages like English. However, to meet the very particular demands of energy and sustainability managers, those LLMs need to know a lot more about our industry.
This is why SystemsLink is fine-tuning our proprietary “energy management software” LLM with enormous volumes of data on weather and climate change, carbon factors, published tariffs, historical consumption patterns and so forth. We are training our AI tools to make sense of all this and help us spot issues, track performance and predict the future.
Ultimately, our clients will be able to harness these capabilities – combined with their own segregated supply contract, estate, consumption and capital improvement project data – to predict, respond and accomplish the day-to-day cost management and long-term carbon reduction demands more efficiently.
Like our energy management software, the all new, cloud-native “daisy” is highly resilient and the data within it highly secure. However, in the era where AI has become mainstream, additional guardrails are essential.
This means we progressively develop a “human-in-the-loop” autonomous decision-making capability for “daisy”; For example, how and when to contact a supplier about an invalid invoice. We will determine the parameters governing what the AI may and may not do in collaboration with our clients.
This is exciting time for energy and sustainability managers – if only we could manage our climate as intelligently as “daisy” manages data!
This article appeared in the Jan/Feb 2026 issue of Energy Manager magazine. Subscribe here.