How Duke Energy’s Digital Transformation Powers America’s Energy Future

From IT Veteran to Digital Transformation Leader

After nearly twenty-five years with Duke Energy, Richard Donaldson brings deep institutional knowledge to his role as Chief Information Officer. In his first nine months leading digital strategy, he’s steering one of America’s largest energy companies through unprecedented technological change. Duke Energy’s massive footprint spans generation, transmission, and distribution across multiple states, with 55 gigawatts of generation capacity and 11 nuclear reactors. For Donaldson, maintaining reliability isn’t just a goal—it’s the fundamental requirement for serving millions of customers and keeping the grid operational.

From IT Veteran to Digital Transformation Leader
The Complex Technology Ecosystem of a Modern Utility
Meeting Unprecedented Energy Demand
Transforming Customer Experience Through Transparency
Practical AI Implementation with Guardrails
Building Organizational AI Capability
The Dual Impact of Data Center Growth
Strategic Principles for Sustainable Transformation

The Complex Technology Ecosystem of a Modern Utility

Donaldson oversees a sprawling technology environment that includes approximately 1,400 business applications, with 10-15% developed in-house. The infrastructure ranges from fiber networks and radio towers to hybrid cloud data centers and on-premises systems. His organizational structure mirrors Duke’s business operations, with specialized leaders focusing on generation and renewables, distribution and transmission, and traditional IT operations.

“Our job is simple in concept but difficult in execution,” Donaldson explained. “We have to make sure every system, every application, every data stream is there when our business partners need it to keep the lights on.”

Meeting Unprecedented Energy Demand

The utility industry is experiencing growth not seen in decades, driven by population increases in the Southeast and the explosion of data centers. Donaldson notes that a single hyperscale data facility can consume a gigawatt of power—equivalent to the output of one nuclear reactor. This demand requires both building new generation capacity and optimizing existing assets through data analytics and modeling.

“If we can squeeze one percent more efficiency out of a plant or a line, that’s a win,” he said. “It’s not free, but it’s a lot cheaper than building new generation.”, according to further reading

Transforming Customer Experience Through Transparency

Around 2015, Duke Energy fundamentally reimagined its approach to customer service. The company discovered that customers value transparency even more than restoration speed during outages. This insight prompted a shift toward benchmarking against companies like Amazon and banking apps rather than traditional utility competitors.

“Our customers don’t compare us to the power company across the street,” Donaldson emphasized. “They compare us to Amazon and their bank app. We have to ‘act like we know them,’ use data responsibly and create an experience that feels personal and modern.”

Practical AI Implementation with Guardrails

Duke’s AI journey began in 2017 with predictive models for detecting slow meters and potential energy theft. When generative AI gained prominence, the company took a measured approach, establishing clear guidelines for tool approval, human oversight, and prevention of model drift.

Today, Duke has more than 50 generative AI use cases across field operations, customer service, and IT. Donaldson stresses that AI isn’t a magic solution but requires proper data, process design, and governance to deliver value.

“We went slow to earn the right to go fast,” he noted, highlighting the importance of building solid foundations before scaling AI applications.

Building Organizational AI Capability

Introducing AI across a large organization requires addressing both understanding and fear. Duke’s approach focuses on solving business problems rather than pushing technology for its own sake. The company gave all IT employees early access to generative AI tools and conducted workshops to help business units identify opportunities.

The strategy has yielded two categories of use cases: individual productivity tools that help employees work more efficiently, and departmental or cross-functional applications that solve larger business challenges., as detailed analysis

The Dual Impact of Data Center Growth

The AI revolution is transforming both technology operations and energy markets simultaneously. Donaldson describes the current environment as “like catching lightning in a bottle”—the same technological wave that’s changing Duke’s operations is also transforming the energy market it serves.

The data center boom is driving discussions about building dedicated generation, restarting nuclear plants, and massive fiber expansion. The critical question remains whether industry appetite will match practical reality in the coming years.

Strategic Principles for Sustainable Transformation

Donaldson’s approach centers on three key principles that ensure technology investments deliver measurable value while maintaining grid reliability. The transformation at Duke Energy represents a sequence of coordinated steps rather than a single leap forward.

“We’re not chasing shiny objects,” he concluded. “We’re building capacity for tomorrow while keeping the lights on today.” After nearly a quarter century with the company, his motivation remains clear: delivering energy safely and reliably while preparing for a fundamentally different energy future.

For organizations undertaking similar digital transformations, resources like the Forum on World Class IT provide valuable frameworks and best practices that can help guide strategic technology investments.