Apollo AI is developing and demonstrating an Artificial Intelligence (AI)-enabled Asset Portfolio Planning (APP) capability that enables data-driven investment planning, scenario analysis, reporting, optimisation and improved decision-making across planning, operations and electricity distribution assets. This is built upon a unified, agentic representation of the electricity distribution network. 

Benefits

Apollo AI is expected to deliver network benefits by replacing fragmented, manual APP processes with a unified, data-driven planning capability. By linking asset, financial, delivery and operational information, together with powerful AI optimisation, the project will support better cross-portfolio optimisation, faster scenario analysis and more responsive re-planning as asset condition data points, delivery constraints and investment priorities change. This is expected to improve transparency, reduce unnecessary interventions and enable better cost, risk and resilience outcomes across the network. 
Customers will benefit from improved reliability and resilience, with Apollo AI enabling network operators to reassess interventions using powerful AI-driven scenario assessments. Based on previous UK Power Networks analytics work on cable optimisation, the method, if successful, is expected to reduce customer interruptions. For example, planned interruptions may be reduced by identifying work packages that can be bundled into a single visit, meaning that the network only has to be touched once, rather than on multiple occasions. This would provide wider societal value by reducing disruption to homes and businesses, including customers who are more dependent on continuous electricity supply. 
The total quantified benefit is based on conservative assumptions across four benefit streams. We expect to save money in the following ways: 
 
Cross-Portfolio Optimisation 
We plan how we invest money by grouping together similar pieces of work into collections of activities we call portfolios, then make investment decisions and prioritise work within those groups. For example, all the work involving replacing old equipment might be one portfolio, and maintaining existing equipment might be another. Typically, the work being carried out, and the investment decisions being made for one portfolio of work, do not impact those within another portfolio. 
This benefit stream arises by using AI to inform our decisions on how investment should be shared across these different work programmes.  For example, the data AI analyses might reveal that instead of spending money on maintaining a certain type of equipment, it may be more cost-effective and make the network more resilient to spend the money replacing the equipment sooner than planned.  Ultimately, this is expected to lead to lower costs and fewer interruptions for customers than would have been the case if decisions were made for each portfolio separately. 
 
Faster Replanning and Scenario Analysis 
We expect that Apollo AI will allow us to think about how things might change in the future, and gain a better understanding of how these changes could affect investment decisions, costs and network performance.  This would allow us to plan for those scenarios in advance to support better investment decisions.  When circumstances do change, we will be able to save costs by quickly updating investment plans rather than having to build new ones, manually, from scratch. For customers, this means that we could act more quickly to make improvements, and reduce costs through the resource efficiencies created by making planning and analysis.   
 
Improved Asset Risk and Resilience Management 
This is about making the distribution network even more reliable.  We expect Apollo AI to be able to combine many different pieces of information we have about our network, such as fault frequency data, and use it to tell us, more accurately, which pieces of equipment are more likely to fail.  For customers, this means that we can prioritise work on the identified equipment to reduce disruptions. 
 
Optimised Reporting, Workforce, Supply Chain and Materials Planning 
This benefit comes from improving planning and forecasting so that the right people, equipment and materials are available at the right time.  This reduces the costs from delays. It also means reducing administrative effort and provides improving reporting.  These efficiencies are expected to result in lower costs to customers.