Three themes electric utilities are struggling with right now
Last month in San Diego, Bentley colleagues joined over 18,000 industry leaders, engineers, and utility providers at DTECH 2026, the premier event for electric transmission and distribution.
There’s unique energy at a show of this scale. It goes beyond the bright booth displays and technical sessions. It reflects an industry coming together to connect, learn, and shape its future
Our goal was simple: listen. We spent time in one‑on‑one conversations, small groups, and technical sessions to understand what utilities are grappling with right now. Across hundreds of conversations, three themes kept coming up:
- The journey to AI and digital twins is about data readiness
- Data integration is a core challenge blocking progress
- Grid resilience requires a tailored, not one-size-fits-all, approach
We’re sharing these insights to spark new conversations and help drive our industry forward.
AI readiness for electric utilities: Why data is the real bottleneck
At DTECH 2026, interest in AI and digital twins was high. But for electric utilities, AI readiness quickly became the real bottleneck.
Utilities and engineering firms understand the potential. AI could improve asset management, support better planning, and help maintain reliability across an increasingly complex grid. Yet many conversations revealed hesitation. As one person asked, “We want to be data-driven, but how do we even start?”
For many utility teams, AI is still a buzzword—not because the technology isn’t ready, but because their data infrastructure isn’t.
Digital twins were also a top topic. Organizations early in their digital transformation often spoke of digital twins, AI, and analytics as distant ambitions rather than near-term capabilities. However, seeing live demos and real use cases at our booth shifted these perceptions—especially among engineers. For them, seeing AI in action made the technology feel tangible and within reach.
Meanwhile, some utilities are already further along. They are pioneering AI adoption by moving beyond experimentation and assigning it clear executive ownership. Across these discussions, one theme became clear—I and digital twins only work when data is well connected across systems and teams.
Data integration for utilities: The hidden barrier to AI adoption
Data integration challenges kept coming up as the primary factor shaping a utility’s readiness for AI. As teams talked through next steps, data challenges often decided whether AI and digital twin initiatives could move beyond interest into action.
Utilities are drowning in data but can’t act on it
Utilities are collecting more data than ever before. At DTECH, we heard frequent references to LiDAR, satellite imagery, and other field capture technologies. Interest is high—but many conversations ended with the same question: what do we do next with all this data?
One story captured the problem clearly. A utility had mapped thousands of miles of distribution poles using LiDAR—a significant investment in data collection—but had no clear path to integrate that data into operations. It’s a pattern Bentley heard repeatedly: utilities are generating data faster than they can connect and act on it. Without integrated data workflows, even the best LiDAR data management process produces stranded assets.
We also heard repeated concerns about data accuracy and trust. One attendee noted that inaccurate data remains a major challenge, and teams are turning to new collection technologies simply to build confidence in what they see. In some cases, data exists in multiple systems maintained by different teams, with no clear way to reconcile differences.
Data silos go beyond technology; they’re an organizational problem
The gap isn’t just technical. It’s also organizational. In one session, a utility leader described how vegetation management and engineering teams rely on different tools and rarely share data—even though both groups are working toward system reliability. That separation limits insight for everyone.
These silos slow decision-making and make it harder to act with confidence. Attendees emphasized the need to bridge these organizational gaps. They want better interoperability so that teams can act with a shared understanding of assets, risks and priorities.
Why data integration matters for AI
These integration challenges directly affect AI adoption. AI depends on data that is consistent, connected, and trusted. When data is fragmented or siloed, AI struggles to deliver reliable insights.
DTECH made one point clear: AI readiness and data integration readiness are inseparable. For many teams, the fastest path to AI value starts with breaking down data silos and improving how information moves across departments. Without that foundation, AI remains an experiment. With it, AI becomes a practical tool that supports planning, asset management, and system reliability.
Grid resilience planning can’t be one-size-fits-all
Resilience was one of the most common themes at the event. It showed up everywhere—from technical sessions to exhibit hall signage and conversations in the Bentley booth. Much of that focus is driven by escalating extreme weather and growing pressure on system reliability. What stood out, however, wasn’t a single definition of resilience—but many. Utilities are approaching resilience in different ways, shaped by local geography, customer needs, and regulatory pressures. We saw examples ranging from community microgrids and backup batteries for vulnerable customers to a renewed emphasis on vegetation management in drought-prone regions.
This diversity matters. It shows that resilience can’t be reduced to a single program or tool. Instead, it is built through many connected decisions—how risk is assessed, how work is prioritized, and how information is shared across teams.
Building a connected grid starts with an integrated data environment
DTECH 2026 underscored that the industry is at an inflection point. Utilities, engineering firms, and solution providers like Bentley agree on the importance of AI, digital twins, and grid resilience. Now, it’s time for focused execution.
When information is scattered across systems, even the most advanced tools struggle. That’s why Bentley focuses on an open, integrated data environment, making sure the right people have the[MD3.1][MC3.2] right data when they need it. With a shared source of trusted information, teams can collaborate more easily, reuse what they already know, and carry insight forward across projects and assets. At a time when electric utilities are under real pressure to deliver safer, more resilient infrastructure, connected data is what helps turn insight into action.
Your grid’s future starts with connected data. Explore Bentley’s electric transmission and distribution software to see how an open, integrated data environment supports smarter design, more resilient operations, and long-term grid performance.
