AI and Utility Modernization: Turning Grid Data, Technology and Talent Into Execution TL;DR
Utilities are facing growing electricity demand at the same time they are modernizing aging systems, connecting more data sources and evaluating AI. The opportunity is significant, but AI alone will not solve the underlying execution challenges.
Utilities need reliable data, connected operational and enterprise systems, specialized engineering and technology expertise, clear governance and a defined business outcome. The organizations that make the most progress will be the ones that treat AI as part of a broader modernization strategy rather than as a standalone technology initiative.
The Utility AI Conversation Is Getting More Complicated
Artificial intelligence is affecting utilities in two very different ways.
On one side, AI infrastructure is contributing to increased electricity demand. On the other side, AI is giving utilities new tools to help analyze increasingly complex systems, improve planning and potentially make faster, better-informed operational decisions.
That dynamic is developing quickly. The U.S. Energy Information Administration expects electricity sales to reach 4,135 billion kilowatthours in 2026 and 4,211 billion kilowatthours in 2027, with data center development and increased manufacturing activity driving much of the growth.
NERC is seeing the same pressure from a reliability perspective. Its 2025 Long-Term Reliability Assessment identifies rapid growth from data centers and other large loads as an increasingly important consideration for resource adequacy and system planning.
For utility leaders, this makes the AI discussion bigger than deciding whether to invest in a new technology.
The more useful question is: What needs to be in place across our data, systems, workforce and operating model for new technology to improve an actual utility outcome?
That is fundamentally a modernization question.
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AI Can Help the Grid, but It Needs a Strong Foundation
AI has potential applications across several areas of utility operations. The Department of Energy has identified grid planning, permitting, operations and reliability, and resilience as near-term areas where AI may contribute value. More recent DOE initiatives are also focused on using AI and integrated data to speed grid planning, interconnection and operational decision-making.
The technology may be new, but one of the biggest barriers is familiar: the information it depends on is rarely contained in one system.
Utility data can span advanced metering infrastructure, GIS, distributed energy resources, outage management, SCADA, work management, customer systems, billing applications and field technology. Those systems may have been developed at different times, for different functions and with different data structures.
An AI model cannot make those underlying conditions disappear.
If the information is fragmented, unreliable or difficult to access, the first phase of an AI initiative may actually be a data integration or modernization initiative.
That is why utility leaders should resist starting with the question, “Where can we use AI?” A stronger starting point is to define the operating problem, understand the data and systems that support it, and then determine whether AI improves the outcome.
This is consistent with the broader approach BCforward has advocated for enterprise AI: start with the business problem, not the tool.
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Connected Data Is Becoming a Utility Capability
Grid modernization increasingly depends on how effectively information moves between systems and teams.
GIS data used to map infrastructure may also support field operations, engineering and asset management. AMI data can affect customer programs, analytics and grid applications. Distributed energy resource information may touch planning, interconnection workflows and regulatory reporting.
The real modernization challenge is not simply implementing each application. It is creating an environment in which the data can support the decisions and workflows that matter.
BCforward and TSR have direct experience working within this type of interconnected utility environment.
At Con Edison, TSR consultants support initiatives involving advanced metering infrastructure, clean-energy data and analytics, enterprise GIS and EV programs. Additional assignments span work-management modernization, mobility, billing, testing, SCADA and outage-management applications.
That breadth is significant because modern utility initiatives rarely remain within a single technology environment. Grid, customer, field and enterprise systems increasingly intersect.
The question is no longer simply whether a utility has data. It is whether that data can be connected, trusted and used effectively enough to support increasingly sophisticated operational decisions.
Resiliency Still Depends on Operational Execution
AI may attract the attention, but utilities still have to keep the system operating.
That means supporting mission-critical technologies such as SCADA, outage-management applications, feeder-management systems, control centers and gas technology while simultaneously modernizing enterprise and field systems. BCforward’s Utilities capabilities also span work management, field mobility, billing and payments, finance, supply chain and fleet applications.
This matters because modernization cannot happen at the expense of continuity.
New capabilities have to fit into environments where reliability, safety, security, compliance and customer service remain essential. Utilities therefore need people who understand not only the technology but also the conditions under which that technology has to operate.
That same requirement extends into engineering and infrastructure programs.
We’ve supported and advise our clients on GIS mapping, electrical engineering, drafting, estimating and project controls, along with energy-efficiency program management, net-metering application coordination, environmental compliance and critical-facilities operations.
Those capabilities illustrate an important part of the utility modernization challenge: technology and engineering increasingly have to work together.
The Workforce Behind Modernization Is Changing Too
As utilities add AI, connected data and new digital capabilities, the required workforce is changing alongside the technology.
Traditional engineering expertise remains critical, but modernization programs may also require data specialists, application developers, business analysts, integration specialists, project managers and people who understand both enterprise technology and utility operations.
AI introduces another layer.
Employees and consultants may need to understand how an AI-enabled workflow changes their work, where human judgment remains necessary, what data can be trusted and who owns the final outcome.
That makes AI a workforce issue as much as a technology issue.
AI + Workforce Strategy: What Leaders Need to Know
For utility leaders, the goal should not simply be to add AI skills to an existing team. It should be to understand the combination of capabilities required to execute the initiative successfully.
In some cases that may mean adding specialized talent to an existing team. In others it may mean assembling a project team around a defined workstream or outcome.
The distinction matters because modernization initiatives eventually have to move beyond capacity and into delivery.
Four Questions to Ask Before Scaling AI in a Utility Environment
BCforward’s broader AI guidance translates particularly well to the utility environment. Before expanding an AI initiative, leaders should be able to answer four practical questions.
What utility outcome are we trying to improve? The answer should be specific enough to measure. That could include faster planning, improved data quality, shorter interconnection cycle time, reduced manual work, better asset visibility or improved operational decision-making.
What data and systems does the outcome depend on? Leaders should understand the role of GIS, AMI, operational technology, enterprise systems, customer data and other information before assuming AI can work across them.
How will the technology fit into the operating environment? Utilities should define where technology supports a decision, where people remain accountable and how the new capability will interact with existing processes, controls and regulatory requirements.
Who owns execution? Someone has to be accountable for moving the initiative from concept into the operating environment. That requires clarity around technical delivery, engineering, program management, governance, adoption and measurement.
These questions help separate an interesting AI experiment from a modernization initiative that has a realistic path to business value.
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Utility Modernization Is Becoming an Execution Challenge
The utility sector does not lack ideas for modernization.
The more difficult question is how to execute those priorities while demand is growing, infrastructure is changing and operational continuity still has to be maintained.
AI will become part of that equation, but it is unlikely to operate as a separate transformation. Its value will increasingly depend on the quality of the data around it, the systems it connects to, the expertise implementing it and the business processes it is expected to improve.
That is why the strongest modernization strategies will connect technology, engineering, data and people rather than treating each as an independent initiative.
For utility leaders, the goal should not be to introduce AI everywhere.
It should be to determine where modernization can improve a meaningful outcome, establish the foundation needed to support it, and then execute the work with enough discipline to make the change sustainable.
That is where AI begins to move from experimentation to utility capability.
Frequently Asked Questions
AI is being evaluated for utility applications including grid planning, forecasting, operations, reliability, resilience and analysis of increasingly complex system data. Its effectiveness depends on the quality of the underlying data, how well systems are connected and how the technology fits into existing utility workflows. DOE has identified planning, permitting, operations and reliability, and resilience as near-term areas of opportunity.
U.S. electricity demand is growing as data centers, manufacturing and other large loads place new demands on the power system. At the same time, utilities are managing distributed energy resources, aging infrastructure and increasingly interconnected grid and customer technologies. EIA expects U.S. electricity consumption to reach record levels in 2026 and grow again in 2027.
The answer depends on the use case. Utility AI initiatives may draw from GIS, AMI, distributed energy resource data, outage and SCADA systems, work-management platforms, customer systems or other enterprise and operational sources. Before implementing AI, utilities should evaluate whether the required information is accurate, accessible, governed and connected to the workflow the initiative is intended to improve.
Modernization can require a combination of utility engineering, GIS, data and analytics, application development, systems integration, testing, project controls, program management and business-analysis expertise. The right mix depends on the systems involved and the operational outcome being pursued. BCforward’s documented utility experience includes many of these areas across Con Edison and PSEG.
Start with the business or operational problem. Define the measurable outcome, identify the necessary data and systems, understand how the workflow will change, determine where human oversight is required and assign clear ownership for implementation and measurement. This prevents AI from becoming a technology experiment without a clear path to value.
Move Your Utility Modernization Priorities Forward
BCforward supports utility organizations across grid modernization, connected data, operational systems, engineering and program execution. Whether the need is specialized expertise to strengthen an existing team or delivery support around a defined initiative, we help connect strategy to the people and capabilities required to execute it.
