2027 Event Agenda

When APS set out to modernize grid operations, the first challenge was not technology. It was knowing which capabilities to build, in what order, and why. As Arizona's largest electric utility serving 1.4 million customers, APS is navigating rapid population growth, unprecedented data center demand, and the integration of renewable generation and battery storage across one of the most complex energy markets in the country.

APS addressed this by building a digital transformation vision grounded in business outcomes rather than technology trends. Spanning Transmission and Distribution Operations and Resource Management, APS defined the capabilities required to improve reliability, operational efficiency, asset performance, and decision-making. The work surfaced gaps in data, processes, and technology that were limiting performance and gave APS a principled basis for sequencing investments by business impact. The result was a capability-based roadmap that told leadership not just where to invest, but why, and in what order.

From roadmap to implementation, APS stood up foundational data engineering, analytics, and AI capabilities to support a growing portfolio of operational solutions. Three prioritized capabilities are now live. Outage Intelligence gave APS a unified view of outage events, enabling teams to identify recurring patterns, improve root-cause analysis, and better understand customer impacts. Service Point-to-Transformer Analytics identified more than 100,000 misassigned or unassigned service points; APS has already bulk-corrected approximately 25,000 associations, improving transformer loading calculations and outage notifications while eliminating significant manual research effort. Substation Asset Monitoring integrated inspection, SCADA, and work management data into a unified view of asset health across all APS substations, reducing manual consolidation effort, accelerating identification of at-risk equipment, and establishing the foundation for predictive and condition-based maintenance.

The implementation journey reinforced lessons that matter for the broader industry. The most valuable use cases emerged through close collaboration with business stakeholders, ensuring investments were tied to real operational challenges. The capability roadmap became more than a prioritization tool; it became a repeatable framework for evaluating and sequencing future digital, analytics, and AI investments as the business evolves. Most importantly, advanced AI capabilities proved only as effective as the data foundation supporting them. Realizing value from AI required parallel investment in data engineering, governance, quality, and analytics. Data maturity and AI maturity must advance together to deliver sustainable business impact.

Attendees will leave with a practical framework for sequencing digital investments by business outcome, concrete examples of implemented AI and analytics solutions delivering operational value, and an honest account of what it takes to build the data foundation that makes AI work.