AI is now impacting every industry and the electrical wholesaler sector is no different. Wayne Fraser, Chief Information & AI Officer at Klipboard, looks at how AI in electrical wholesale can power smarter trade decisions.

With the rapid acceleration of EV infrastructure, the growth of smart homes, and the increasing adoption of renewable technologies, the electrical wholesale sector is becoming more complex – and more central to the wider economy. Our industry is no longer just about supplying product; we’re enabling critical national infrastructure. And with that shift, the operational pressures have grown. Businesses now face tighter margins, higher customer expectations, and a growing demand for technical expertise. That’s where AI comes in. Not as a future promise, but as a present-day necessity.

From discussion to deployment 

Over the past 18 months, we’ve seen a fundamental shift in how wholesale distributors – particularly in the electrical space – are approaching AI. It’s moved beyond boardroom conversations and into real operational impact. Across the UK wholesale distribution market, nearly 50% of businesses now rank AI as a top investment priority. And for good reason: the challenges we face aren’t getting simpler. AI isn’t hype anymore, it’s how we start to solve long-standing problems at scale.

Tackling long-standing operational friction

Electrical wholesalers, more than most, have always had to deal with intense stock complexity. Whether it’s tracking reels of cable by the metre, handling variants of the same product line with minor but critical technical differences or managing customer-specific pricing agreements across thousands of SKUs, these are problems that don’t lend themselves to manual workarounds. Historically, many of these processes were either spreadsheet-based, or bolted onto ageing ERP systems. That’s not a sustainable approach for organisations that want to lead in today’s climate.

What we’re seeing now is the market turning to the next generation of software. Platforms where AI is built-in from the ground up. Take inventory management, for example. At Klipboard, the ERP One platform integrates natively with AI tools to support intelligent stock forecasting. By combining internal sales history with external data points – such as seasonal demand, project timelines, and even shifts in EV infrastructure investment – merchants are able to make smarter decisions about what to stock, when to reorder, and how much capital to commit. 

Rethinking logistics

The benefits don’t stop at the warehouse. Logistics and fleet operations are evolving too. In distribution, the cost of delivery has always been a delicate balance between efficiency and service. Kilpboard has integrated AI-led auto-routing into its Transport Management (VIGO) platform. By using live traffic data and historical delivery performance, Klipboard helps drivers complete more drops per shift, reduce fuel usage, and improve on-time performance, all while supporting the sustainability commitments that more of our customers now expect.

Supporting the frontline with smart tools

At the same time, we’re seeing AI enhance the customer experience, both online and at the trade counter. AI-powered assistants, like Klipboard Copilot, are helping branch staff and customer service teams to quickly answer common questions about stock availability, pricing, and delivery updates. These tools aren’t designed to replace people, they’re there to support them. By handling repetitive or routine requests, AI frees up teams to focus on what really matters: building customer relationships, solving more complex problems, and driving additional value through every interaction.

There’s a lot of noise about AI – but in many cases, it’s just old automation with a new label. What has changed is the processing power availability has grown year on year and also LLM’s capability and availability, thus enabling a much richer experience.

Scaling for the future

For electrical wholesalers, the stakes are high. The product catalogue is expanding. Customer demand is rising. And the old ways of working simply don’t scale. AI offers a clear path forward. It enables leaner operations, reduces overstock, improves fulfilment accuracy, and supports better service delivery – without the need to grow headcount.

Final thoughts

AI won’t transform the industry overnight. But the shift is already underway. It’s already transforming from what used to be just a buzzword, to now cementing itself as a business-critical function in the distribution sector across the board. The businesses that act now, and who invest not in buzzwords, but in capability, will be the ones that have the greatest chance of success in the future.

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In the face of growing concern surrounding the energy demands of Artificial Intelligence (AI), Ben Croxford, Managing Director at Eclipse Power Networks, explains how AI can help solve the challenge of its own power demands with information generated by smart meters and electric vehicle charging.

Artificial Intelligence (AI) is a central part of the UK government’s plan to boost growth across the UK. Through its AI Opportunities Action Plan, the government intends on using AI to deliver its wide-ranging Plan for Change, including commitments to make Britain a clean energy superpower by 2030. Elsewhere AI is being touted as a fix for everything from administrative overload in the Civil Service, to the UK’s one million-plus potholes.

But the energy demand of AI is notoriously high. In April, the International Energy Agency published a new report, projecting that consumption by data centres – where the bulk of AI processing takes place – will more than double by 2030. Globally, within the next two years, the AI industry could use as much energy as a country the size of Japan.

Within the energy sector, however, AI is emerging as a tool that not only lowers management overheads, but enables new ways of controlling generation, distribution and consumption. And by supporting the flexibility needed to accommodate increased levels of renewable generation, AI can more than offset the impact of its own power demands.

AI: the cause or cure of energy woes?

Already, across the energy sector, AI is used to optimise generation, transmission, distribution and consumption. It’s also a major instrument we’re using to help decarbonise the sector and make net zero a reality.

Energy companies use AI to connect, optimise, and control energy assets. This includes generation and storage facilities, but increasingly it extends to the major energy-consuming or storing devices owned by business or domestic customers. This list includes electric vehicles (EVs) and their chargers, but also battery storage; heat pumps; and heating, ventilation and air conditioning (HVAC) systems.

AI is being used for commercial and industrial developments to manage both generation and demand. As a tool, it helps optimise the use of distributed energy resources like batteries, solar and wind, to accommodate the peaks and troughs of grid demand.

Powered by AI, demand-side response (DSR) programmes allow suppliers to shift the load caused by electrical equipment, and balance the grid. This can be achieved by incentivising businesses and consumers to reduce their power use at peak times, but an increasing number of devices support direct control, allowing a quicker and more flexible response. For example, since December 2022 all EV chargers sold in the UK must be smart, supporting DSR and other energy management features. This allows customers on smart tariffs to benefit from ultra-low pricing, while energy companies can optimise overnight charging to match supply, and make the most of renewable power.

Platforms that enable demand response programmes, such as Octopus Energy’s KrakenFlex, use AI to determine what capacity is needed, when to call a DSR event, and what incentive to offer. With AI powering optimisation, organisations can increase the value of their energy assets by intelligently using them when the market conditions are right. In turn, this improves the return on their investment, and potentially boosts investment in new renewable assets.

Self-sustaining innovation

AI-driven programmes help optimise the use of generation resources, creating a better match between supply and demand. A vital benefit from this is that it helps the distribution system accommodate greater amounts of renewable energy. Electricity generated from wind and solar is inherently intermittent. Actively managing the demand for energy lets us compensate, for example by reducing demand when wind output falls, or stimulating it when energy is abundant.

AI offers further exciting potential to expand and improve renewable energy. For example, as a tool for scientific discovery, AI looks likely to accelerate the pace of innovation in key technologies such as photovoltaic (PV) solar modules or battery storage. Improvements here could improve efficiency or performance, lower the technologies’ cost, or provide other tangible benefits. AI is likely to emerge as a driving force for innovating cleaner energy, producing benefits that more than outweigh its own consumption.

AI isn’t just a way to improve generation and use – it can drive efficiency at the distribution level, too. That’s a key concern as the UK electricity grid struggles to adapt to fast-changing usage patterns and the growing demand for power. AI helps us take grid management to a new level. Algorithms that respond to voltage or frequency fluctuations in milliseconds will aid grid stability, enabling real-time load balancing and power-flow optimisation to reduce transmission losses.

At the planning stage, AI enables better demand forecasting and scenario modelling. AI supports accelerated connections to the grid, the smarter adoption of existing power networks, and predictive maintenance that minimises disruption and cost. And through data-led asset management, AI helps us move from reactive to preventative maintenance strategies, optimising service levels and return on investment.

But while the power industry can already point to successes, it’s not alone in facing a critical, UK-wide shortage of AI skills. These add to the challenge of adapting to shifting and growing energy use, driven in part by AI’s increased demands. By investing in skills, and by reframing AI as a strategic enabler across business functions, the power industry can continue to innovate in this area.

AI provides net benefits

AI thrives on data. The energy sector both generates and consumes enormous volumes of it. The information generated by smart meters, remote monitoring sensors, electric vehicle charging and other digital assets feeds into AI algorithms to empower smart grids and actively managed networks that benefit the electricity industry on multiple levels.

Despite some alarmism about AI’s energy consumption, it has the potential to more than compensate for its own energy demand. Indeed, as the IEA’s recent report finds, it could be instrumental in cutting costs, enhancing competitiveness and reducing emissions across the sector.

By using AI to optimise demand and generation, we don’t have to just add more generation and storage to keep abreast of peak demand. Intelligent AI-powered optimisation of smart grids and actively managed networks can provide lots of the capacity that the fast-evolving power market requires – going far beyond the additional demands created by AI data centres.

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