UK workers generate 22 million AI prompts daily, driving energy demand

British employees generate an estimated 22 million AI prompts every working day, creating a substantial and growing electricity demand. While individual queries require minimal power, the sheer volume of corporate adoption is turning generative AI into a significant component of the UK's digital energy footprint.

According to research from Uswitch Business Energy, UK employees consume approximately 5.28 MWh of electricity daily through AI usage. On an annual basis, this totals roughly 1.37 GWh—enough energy to power 508 British homes. The scale of this consumption is driven by the ubiquity of tools like Gemini and ChatGPT for routine tasks such as data analysis and email drafting. For context, a single Gemini text prompt is estimated to use 0.24 watt-hours (Wh) of energy.

Sector-led adoption

The energy demand is not evenly distributed across the economy. IT and telecoms workers are the heaviest users of the technology, averaging 35 prompts per team per day. Finance professionals follow closely, with an average of 29 prompts per team daily.

This shift in usage reflects a broader transition in how AI consumes power. While the initial training of a cutting-edge model is energy-intensive, the focus has shifted to the "inference" phase—the stage where the model generates a response to a user's query. With global platforms handling billions of queries daily, the cumulative energy required for these responses now rivals or exceeds the cost of the original training.

Corporate implications

Although this electricity is consumed in remote data centers rather than on-site at corporate offices, the environmental and financial implications remain significant for businesses. As AI becomes embedded in standard operations, it becomes a primary contributor to a company's overall carbon and energy footprint.

Ben Gallizzi, an energy expert at Uswitch, noted that as more organizations adopt AI for administration, customer service, and content creation, the cumulative energy demand will continue to grow. This trend suggests that businesses may need to begin tracking their digital energy usage more rigorously to manage costs and meet sustainability goals.

The path forward

Industry analysts suggest that the next phase of AI integration will require more sensible credit usage and monitoring to avoid escalating environmental impacts. While the current data provides a baseline for the UK, the total footprint remains a moving target as models evolve and adoption rates climb. Companies are now being encouraged to audit their digital habits to understand the hidden power bill behind their AI productivity gains.