As of 2025, digital transformation in the utility sector is well underway. Most electric utilities have already initiated modernization projects, integrated distributed energy resources (DERs), and begun leveraging data to improve decision-making. What’s changed is the pace of expectations and the narrowing margin for experimentation.
Electric utilities are now required to operationalize digital strategies that deliver measurable results, whether in asset performance, reliability, customer integration, or resilience. Strategy and Innovation Leaders must shift focus from pilots to scaled, system-wide implementations. Doing so requires a coordinated approach to technology, data governance, talent, and cross-functional alignment.
This briefing outlines six technology trends that are shaping the trajectory of digital utilities in 2025. Each carries direct implications for planning, investment, and execution, and demands close scrutiny from strategic leadership.
1. Convergence of IT, OT, and IIoT
The integration of information technology (IT), operational technology (OT), and Industrial Internet of Things (IIoT) devices continues to advance as utilities seek a unified view of asset health, grid performance, and customer interaction.
Historically siloed systems are being connected through data platforms that enable interoperability across SCADA, asset management systems (AMS), geographic information systems (GIS), and enterprise IT applications. This convergence is essential for improving asset lifecycle management, enabling faster situational response, and supporting real-time optimization at the grid edge.
However, the challenge lies not in connectivity alone, but in governance. Strategy leaders must ensure that data flows securely, complies with standards, and is made accessible to the right teams. Without defined protocols and ownership models, digital convergence can lead to fragmentation rather than cohesion.
2. Condition-Based Maintenance as a Strategic Imperative
Time-based inspections are proving insufficient for managing increasingly complex, distributed, and high-value grid assets. In their place, Condition-Based Maintenance (CBM) strategies are gaining traction as a cost-effective, risk-mitigating alternative.
By using data from thermal, visual, electrical, and vibration sensors, utilities can move beyond fixed schedules and instead base maintenance on actual asset condition. This approach helps identify early signs of degradation, such as overheating, partial discharge, or mechanical stress, and enables prioritized interventions.
For Strategy & Innovation Leaders, CBM is no longer a tactical improvement, it’s a strategic necessity. Aging infrastructure, workforce constraints, and rising expectations for reliability mean that proactive asset management must be built into the utility’s core operational model. Integrating CBM with existing maintenance systems and regulatory reporting frameworks should be a top agenda item.
3. Predictive Analytics and AI in Operational Planning
Artificial intelligence (AI) and machine learning (ML) tools are transitioning from niche pilots to operational use cases in forecasting, diagnostics, and performance optimization. Specifically, predictive analytics is being used to model:
- Asset failure probability
- Transformer loading patterns
- BESS thermal risk profiles
- DER volatility and curtailment
Rather than acting solely as post-event diagnostic tools, these systems now inform capital planning, outage mitigation, and resource allocation.
Strategic teams must define where AI adds the most value and ensure alignment with measurable business outcomes. As data science capabilities expand, utilities risk overinvesting in analytics platforms that lack integration with core operational systems. Clear use cases, targeted deployments, and cross-department collaboration are critical to avoiding underutilization or data redundancy.
4. Edge Computing and Distributed Intelligence
The growth of edge computing is enabling faster, more autonomous decision-making at substations, vaults, and remote assets. Processing data locally at the device or network edge reduces latency, enhances situational responsiveness, and ensures continuity during connectivity disruptions.
Applications include fault detection, temperature threshold alarms, equipment condition imaging, and autonomous recloser or switchgear actions. Edge devices also reduce the burden on centralized systems by filtering and transmitting only actionable insights.
For innovation teams, edge computing should be evaluated not only for its technical performance but for its ability to scale securely across diverse environments. Solutions must be interoperable, maintainable, and able to integrate with cloud and enterprise platforms without increasing cybersecurity exposure.
5. Data as Critical Infrastructure
Data is now recognized as a core utility asset, equal in importance to physical infrastructure. But while most utilities generate extensive volumes of data, many still face challenges in governance, structure, and interoperability.
From grid telemetry to condition monitoring to customer analytics, the value of data is determined by its context, accessibility, and usability. Investment in data models, metadata standards, and role-based access is essential for scaling digital tools across the enterprise.
Strategic leadership must prioritize data as a long-term investment. This includes establishing enterprise-wide data strategies, aligning IT/OT teams, and ensuring compatibility with regulatory and cybersecurity frameworks. Without this foundation, even the most advanced technologies will fall short of their potential. The U.S. Department of Energy’s Grid Modernization Initiative highlights the national imperative to strengthen data architecture and operational flexibility across utilities.
6. Cybersecurity as a Foundational Requirement
The increasing digitization of utility infrastructure has expanded the cyber threat surface dramatically. IIoT devices, remote sensors, cloud integrations, and edge processors all represent potential points of vulnerability.
In 2025, cybersecurity must be embedded from the outset, governed by principles of zero-trust architecture, encrypted communication protocols, device authentication, and continuous monitoring. Regulatory bodies are also tightening compliance expectations, especially for critical infrastructure operators.
Innovation teams must work in parallel with cybersecurity units to validate vendor solutions, implement secure integration practices, and maintain incident readiness. Cybersecurity is not a discrete domain, it is a prerequisite for innovation at scale.
Recommendations for Strategy & Innovation Leaders
To operationalize digital utility goals in 2025 and beyond, consider the following priorities:
- Establish a cross-functional digital roadmap that aligns IT, OT, and operational business units with shared objectives and deployment timelines.
- Prioritize scalable, interoperable solutions over bespoke or isolated technologies that create long-term maintenance or integration burdens.
- Treat data strategy as a utility-wide initiative, with defined roles, access policies, and standards to ensure consistency across applications.
- Implement governance structures for emerging technologies, especially AI and edge computing, to ensure alignment with cybersecurity, compliance, and ROI expectations.
- Evaluate workforce capacity and training needs as new systems are deployed, addressing not just technical gaps but change management and interdepartmental coordination.
Electric utilities in 2025 are no longer exploring whether to digitize, but how to do so efficiently, securely, and at scale. For Strategy & Innovation Leaders, the task is not simply to adopt new technologies, but to embed them within the utility’s core operating model to deliver lasting value.