GaiaLens, AI and data solutions specialist, has launched a new customisable proposition designed to help the UK’s electricity distribution network operators (DNOs) reduce the growing reporting and evidence burden demanded by ED3 – the next electricity distribution price control. DNOs’ business plans for ED3 are due in by December 2026 as the sector prepares reports associated with the next five-year control period running from 1st April 2028 to 31st March 2033.
The offer addresses issues that have become increasingly visible in public discourse associated with ED3 including complaints of ‘duplicated returns’; ‘increased evidence demands’ and higher risk that regulatory submissions stray from the way networks are actually being planned and delivered.
Ofgem itself has acknowledged in its ED3 methodology consultation that RIIO-ED2 cyber (security) reporting led to an unnecessary ‘double reporting’ requirement as the same data had to be filed with Ofgem for its RIIO-2/ED2 cyber report as well as with NIS for mandatory NIS-R (Network and Information Systems Regulations) compliance.
GaiaLens has turned its AI skill base to building an AI-enabled reporting architecture that is capable of gathering the right operational, planning, programme and evidence data from source systems; structuring this data in a governed way, with a view to injecting relevant data into ED3 reporting workflows more efficiently and consistently, thereby reducing manual effort by as much as a 50%.
Seb Kirk (pictured above), co-founder and CEO of GaiaLens explains, “Electricity distributors are being asked to evidence more, justify more and report more clearly, at exactly the point when network complexity is increasing. But the sector does not need ever larger reporting teams to keep up with this burden. Instead, it needs better data architecture, stronger traceability and much smarter automation.
“What many distributors are facing is not simply a reporting volume burden but a duplication problem. The same underlying information can end up being collected, reformatted, checked multiple times across different workflows, for different reports. When this happens, the cost is not just in time. It leads to slower decision-making, weaker alignment between teams and greater risk that the final submissions no longer reflect operational realities.”
GaiaLens says its customisable offer is designed to help DNOs create a common reporting data layer spanning planning assumptions, delivery milestones, resilience evidence, engineering data, asset information, programme status and cost data. That, in turn, would allow DNOs to assemble regulatory returns, supporting evidence packs and internal governance outputs from governed source data, rather than repeatedly stitching information together by hand.
Kirk added, “We believe AI has a very practical role to play here as a disciplined tool for gathering, validating, mapping and populating reporting outputs from verified and trusted source systems. Done properly, that can help reduce duplicated returns, improve consistency, support clearer reporting logic, and make it easier to show where every reported figure or statement has come from.”
The timing is significant as Ofgem’s ED3 framework decision and later methodology consultation made clear that the next distribution control is intended to support a pivotal investment period associated with delivering Clean Power 2030 goals.
GaiaLens says that distributors now have a limited window to improve their reporting architecture before ED3 begins in April 2028. The company is inviting DNOs and delivery partners to explore pilots focused on ED3 reporting readiness, including source-system mapping, workflow redesign, reporting data models, evidence automation and AI-assisted submission assembly.
