AI in the Control Room: Improving Grid Operations Without Losing NERC Compliance

If you work in or around a utility control room, you know the grid is getting more complicated.

Every day, control room operators make thousands of decisions to keep power flowing safely and reliably. Add in renewable generation, distributed energy resources, and new load types, and those decisions only get harder. The tools you rely on have to keep up.

Artificial intelligence (AI) is emerging as a powerful way to help manage the modern control room. It can help operators sort through massive amounts of data, spot patterns faster, and focus on what really matters.

But, as utilities know, when you’re dealing with critical infrastructure, innovation can’t come at the expense of compliance. NERC reliability and CIP requirements still come first.

So how can utilities take advantage of AI to improve operations without creating new compliance risks?

Why AI Is Gaining Traction in Control Rooms

AI isn’t about replacing operators. It’s about supporting them.

Control rooms generate a massive amount of data across SCADA, EMS, outage management, and historical systems. AI is good at processing large data sets quickly and pulling out useful insights. Operators can then focus on judgment-based decisions.

Some of the most practical use cases already being explored include:

Smarter Alarm Management

Anyone who has dealt with alarms knows how quickly they can overwhelm even experienced operators. AI can analyze thousands of SCADA alarms, identify patterns, and highlight the ones that truly need attention. Less noise means better focus and faster response.

Digital Twins and “What-If” Scenarios

Digital twins allow operators to run “what if” scenarios using virtual models of the grid. They can see how different events may play out before they happen, which is valuable for planning, training, and restoration strategies.

Faster Access to the Right Data

Instead of jumping between multiple systems, operators can ask questions in plain language and get immediate answers. For example:

• “Show voltage trends on Bus 14.”
• “What’s driving this frequency deviation?”

Better Coordination Across Systems

AI can connect real-time and historical data, so operators see the bigger picture and act more confidently during fast-moving events.

Used the right way, AI becomes another tool in the toolbox. It supports human expertise rather than replacing it.

The NERC Compliance/AI Reality Check

Adding AI into the control room isn’t just a technical decision. It’s also a compliance decision.

Current NERC CIP standards were not written with self-learning or frequently updating AI systems in mind. That means utilities must think carefully about governance, accountability, and cybersecurity from the start.

Key questions utilities should ask include:

• Who approves and certifies AI models used in operations?
• How is model accuracy validated against system physics and reliability standards?
• How are updates tracked, tested, and approved?

Several CIP standards are especially relevant:

CIP-010: Configuration and Change Management

AI models evolve over time. Each change must be documented, tested, reviewed, and approved just like any other system change.

CIP-013: Supply Chain Risk Management

Utilities need confidence that AI vendors can demonstrate secure, traceable, and accurate updates. Transparency matters.

CIP-005 and CIP-006: Access Controls

Access to AI systems must be tightly controlled. Any third-party access for maintenance or data handling needs to be limited, monitored, and well documented.

CIP-011: Information Protection

AI systems process large volumes of operational data. That data must be protected from unauthorized use or disclosure.

CIP-008 and CIP-007: Incident Response and Vulnerability Management

AI-related failures or vulnerabilities should be included in incident response planning and vulnerability assessments, just like any other critical system.

The takeaway? AI should be treated like any other critical system in the control room. Govern it, secure it, and document it.

How Utilities Can Start Using AI Without Taking Big Risks

Utilities don’t need to jump in headfirst. A slow, deliberate approach works best.

1. Start offline
   Many utilities start by testing AI tools using historical or simulated data. Alarm analysis, trend detection, and outage planning are all good starting points that don’t affect live operations.
2. Keep security front and center
   Because many commercial AI tools are cloud-based, they can be difficult to integrate into control networks. Some utilities look at on-premises AI environments or partnerships (such as with NREL) to let them use their own data securely.
3. Move online carefully
   Once an AI model proves reliable, it can be connected to live systems in read-only or advisory mode. Operators can review recommendations without giving up control.
4. Update policies and training
   AI should be reflected in compliance documentation, cybersecurity procedures, and operator training. Think of it as a new team member that needs oversight and regular evaluation.
5. Learn from others
   Sharing lessons learned and best practices helps the entire industry move forward safely and consistently.

What the Next Few Years Will Bring

Over the next several years, AI is expected to become more common in control rooms. We’re likely to see:

• Dashboards that summarize data and suggest operator actions
• Digital twins used for real-time simulation and restoration training
• Updated NERC guidance addressing AI governance
• Better coordination between transmission and distribution systems
• Predictive tools that spot issues before alarms even trigger

Regulations will continue to evolve, but reliability and compliance will remain the foundation.

Final Thoughts: Balance Between AI and Compliance Is the Key

AI can’t replace the people who run the grid.

What it can do is help operators make faster, better-informed decisions while keeping systems safe and reliable. The key is balance.

Embrace innovation. Protect compliance. Train your people.

Start small and build trust in the technology. Keep reliability front and center in every decision.

That’s how AI becomes a useful partner in the control room.