A single artificial intelligence scan identified more than 8,200 low-income households that had slipped through traditional eligibility screening for energy assistance programmes—a finding that will anchor discussions when energy retailers gather in London next month.
Bidgely, the California-based energy analytics firm serving over 50 million homes globally, hosts its EmPOWER AI conference in London from 10th to 12th June. The three-day forum marks the European leg of an international tour that has already stopped in Toronto and New York.
The 8,200 figure emerged from Bidgely’s Analytics Workbench, which one undisclosed energy provider used to scan customer data for vulnerable households missing from standard support rolls. That same provider converted 2.3 percent of those newly identified customers through a single marketing contact—then doubled its home energy audit capacity to handle the surge in eligible participants seeking efficiency rebates.
It’s the kind of result that has energy retailers paying attention. Especially in Britain, where the gap between soaring energy costs and household budgets has left millions struggling.
A new joint report with energy research firm LCP Delta will debut alongside the conference. Titled “Home Asset Identification,” the analysis benchmarks how well different approaches—AI-powered data analytics, statistical approximations, hardware monitoring—actually identify assets like heat pumps, electric vehicles, and solar panels in customer homes.
David Trevithick, head of customer insight at LCP Delta, will present findings from the firm’s behavioural demand response research during the London sessions.
“As home asset uptake increases, household demand profiles become more distinctive and variable-unlocking greater opportunities for retailers to identify assets, target smart tariffs and flexibility propositions more effectively, improve demand forecasting and boost customer retention,” added Trevithick.
The report’s conclusions matter because utilities need to know what’s plugged in where. A home with an electric vehicle and a heat pump has radically different demand patterns than one with gas heating and no EV. Miss those distinctions, and grid planning becomes guesswork.
Bidgely built its business on disaggregating meter data—essentially reverse-engineering what appliances and systems are running based on consumption patterns. The company holds 19 foundational patents in the space. Fast Company ranked it among the top 10 most innovative applied AI companies.
But patents and rankings don’t pack conference rooms. Results do.
One case study on the agenda: an energy provider that targeted high-peak users for electric vehicle programmes and achieved a three-times increase in kilowatt reduction per vehicle compared to the average EV population. Another provider slashed peak load by more than 70 percent among high-consumption customers by refining variable pricing programmes with AI-driven targeting.
Call centre metrics tell a similar story. By integrating Bidgely’s insights into resolution workflows, one utility logged a seven percent jump in customer satisfaction, trimmed average handle time by three percent, and improved first-call resolution by three percent. Customer service representatives reported confidence ratings between 85 and 95 percent when using the tools.
Attendees will also see Bidgely’s new Interactive Voice Response integrations with PolyAI, Genesys, and NiCE. The conversational AI systems resolve complex energy queries in real time—cutting wait times whilst handling questions that typically require human intervention.
The workshops break into four tracks: accelerating electrification, modernising call centres, optimising load flexibility, and driving energy affordability. Each session pairs the LCP Delta research with case studies drawn from utilities that have deployed AI analytics at scale.
For the electrification workshop, participants will examine how AI identifies high-impact EV customers and uncovers load growth hotspots—intelligence that lets retailers recruit strategically rather than broadly. The load flexibility session digs into peak shaping and shifting, showing how granular customer targeting outperforms blanket time-of-use appeals.
The call centre workshop demonstrates how AI insights get embedded into existing ecosystems—the unglamorous but essential work of making sure the technology actually gets used by the people answering phones at 9am on a Monday.
And the affordability track returns to those 8,200 hidden customers, walking through the methodology that surfaced them and the outreach strategies that converted them into programme participants.
“EmPOWER AI London isn’t just a look at the future of energy-it’s where we actively build it,” said Abhay Gupta, CEO of Bidgely. “The grid transition requires bold action and intelligent data. We invite forward-thinking leaders from across the globe to join us, challenge the status quo, and unlock the true art of what’s possible when AI meets human ingenuity.”
The timing isn’t accidental. Britain faces aggressive heat pump installation targets, accelerating EV adoption, and a grid that needs billions in upgrades to handle the shift from gas to electricity. Energy retailers are caught between government decarbonisation mandates, customer affordability crises, and infrastructure constraints.
Traditional utility planning tools—spreadsheet models, historical averages, broad demographic assumptions—struggle with the variability that electrification introduces. A neighbourhood might have three heat pumps this year and thirty next year. Demand forecasts built on last year’s data become obsolete faster than the ink dries.
That’s where granular, premises-level intelligence matters. Knowing which specific homes have heat pumps, solar panels, and EVs lets utilities predict load curves, design targeted tariffs, and plan infrastructure upgrades with precision rather than rough estimates.
Bidgely’s platform integrates with broader AI ecosystems including Microsoft Copilot and AWS, positioning the analytics as components within larger utility technology stacks rather than standalone systems. The company operates from its Los Altos headquarters in California but has expanded globally as utilities worldwide confront similar electrification pressures.
The London conference follows a format Bidgely has refined through previous stops: custom workshops, peer-to-peer dialogue sessions, and case study presentations designed to move beyond vendor pitches into operational detail. How did that utility actually achieve the 70 percent peak reduction? What barriers did they hit? What would they do differently?
For energy retailers, the calculus is straightforward. Electrification is happening whether utilities are ready or not. Government policy, automaker commitments, and climate targets have locked in the trajectory. The question isn’t whether the grid needs to handle millions of heat pumps and EVs—it’s whether utilities will manage that transition intelligently or chaotically.
Registration details and the full agenda are available at empower.bidgely.com/london-2026. Whether the conference delivers on its promise to “actively build” the future remains to be seen. But the case studies suggest at least some utilities have moved past presentations and into measurable results.
