As global energy demand surges and renewable generation reshapes power systems, utilities are facing a level of complexity not seen since the grid was first built. In response, the industry is investing at historic levels—more than $2.2 trillion globally in 2025 alone—to modernize infrastructure, expand clean energy, build the intelligent energy platforms of tomorrow, and strengthen grid resilience.
The message from utility executives is clear: AI is no longer optional. According to the IBM Institute for Business Value (IBV), 94% of utility leaders expect AI to contribute significantly to revenue growth within three years, and 88% believe it will deliver measurable competitive advantage.
The challenge, however, is no longer whether to invest in AI. The question of the moment is how to how to operationalize it at scale, safely, and fast enough to keep pace with accelerating change.
The Grid Is Becoming a Data Platform
For more than a century, power grids were designed primarily for reliability. Today, they must do far more: integrate variable renewables, support EVs and data centers, manage two-way energy flows, and deliver flexibility to increasingly empowered customers.
AI is the catalyst making this evolution possible.
The IBM IBV research shows utilities rapidly embedding AI across the value chain, from field workforce optimization and predictive maintenance to outage management and demand-side optimization. Adoption is accelerating sharply: AI-driven grid monitoring and optimization is expected to rise from 26% in 2025 to 92% by 2028.
This shift reframes the grid as a dynamic, data-driven platform that continuously senses, predicts, and responds in real time.
AI Is Moving Utilities from Reactive to Predictive (and Largely Autonomous)
AI has already moved beyond pilots. Utilities report tangible gains, including:
- ~11% improvement in grid uptime
- ~10% increase in service reliability
- ~10% improvement in energy efficiency
- Faster incident response and reduced technical and non-technical losses
These outcomes are powered by predictive models that analyze historical usage, weather, and real-time sensor data to forecast demand, anticipate failures, and optimize storage and dispatch.
The next leap forward is agentic AI systems capable of acting autonomously. Utilities are already piloting intelligent agents for automated outage response, smart home ecosystem control, virtual power plants, and field service automation.
As these capabilities mature, utilities are positioned to move from predictive operations to increasingly self-optimizing, resilient systems.
New Energy Business Models Are Emerging
Efficiency gains are only part of the story. AI is also unlocking entirely new revenue opportunities.
More than half of utility executives expect AI to enable business model innovation, including:
- AI-managed subscription energy services
- Storage-as-a-service offerings
- DER orchestration and virtual power plants
- AI-powered energy trading, projected to grow from 7% adoption in 2025 to 87% by 2028
Executives already attribute ~11% of current revenue to AI-driven initiatives, with projections rising to nearly 15% by 2028. This marks a material shift in how utilities create and capture value as AI-enabled intelligent energy platforms become the new baseline.
Data Is the Constraint Holding AI Back
Despite strong momentum, IBM IBV is clear: data readiness is the gating factor for AI success.
Utilities face persistent challenges:
- Fragmented IT/OT systems
- Siloed operational, meter, and customer data
- Inconsistent governance and lineage
- Legacy infrastructure not built for real-time analytics
Without unified, governed, and intelligent data platforms, AI initiatives struggle to scale, trust erodes, and monetization stalls. As grids become more complex, these constraints only intensify.
Hybrid Cloud Is the Backbone of the AI-Ready Utility
To support real-time decision-making, edge analytics, and enterprise-scale AI, infrastructure matters.
IBM IBV highlights hybrid cloud by design as foundational:
- 71% of IT leaders say full digital transformation is impossible without hybrid cloud
- Yet only 35% of mission-critical workloads currently run in the cloud
Hybrid architectures allow utilities to process data where it performs best while meeting regulatory, latency, and resilience requirements. This affinity makes it a natural architectural choice when building and scaling intelligent energy platforms.
What Utility Leaders Should Do in 2026
The vision is clear. Execution is the differentiator. To turn AI ambition into impact, utilities should focus on pragmatic, high-leverage actions:
- Build a Unified, AI-Ready Data Foundation. Break down silos across grid, operations, customer, and market systems. Embed governance, lineage, and security from day one.
- Operationalize AI (Not Just Pilot It). Tie AI initiatives directly to KPIs like SAIDI/SAIFI, outage response time, renewable integration, and cost-to-serve.
- Design for Hybrid Cloud from the Start. Modernize IT/OT platforms to support real-time analytics, edge intelligence, and scalable AI without compromising compliance.
- Invest in People and Process. Upskill teams, capture institutional knowledge, and embrace automation and agentic AI as force multipliers instead of replacements.
Why Hakkōda Is the Right Partner for Building the Intelligent Energy Platforms of Tomorrow
Modernizing utilities for the AI era requires more than technology. It demands deep industry understanding, modern data architecture expertise, and disciplined execution.
Hakkoda works with utilities to turn data and AI strategy into operational reality, whether that’s building scalable data platforms, enabling predictive and agentic AI use cases, or designing hybrid architectures for resilience, compliance, and growth.
As the IBM Institute for Business Value makes clear, the utilities industry is still early in this transformation. The leaders of 2026 will be those who move decisively and ground their bold ambitions in execution excellence.
Ready to see what AI-powered utilities transformation could look like for your organization? Let’s talk.
