Agentic AI Use Cases in Utilities: How Field, IT, and HR Workforce Support Gets Done

Your workforce rarely has the luxury of sitting near a helpdesk. Field technicians, grid operators, and other dispersed employees need answers and support wherever the work takes them, often across systems that weren’t designed to work together. That makes workforce support a growing challenge as utilities modernize. 

Agentic AI can bring that support directly to employees, wherever they work. 

That means giving your workforce an easier way to get help with everyday IT and HR needs without tracking down the right person or system. We’ll go over four agentic AI use cases where this approach can make an immediate difference in utilities.

What is agentic AI for utilities?

Agentic AI can reason, plan, and act across enterprise systems to help resolve a request end to end, within defined guardrails, rather than simply generating text. It can understand what an employee is asking for and determine the steps involved before carrying them out across the systems needed to complete the request. 

That means an employee doesn’t have to stop at finding the right info. 

A field technician who needs access to an application, for example, could have an AI agent identify the required approvals, initiate the request, and confirm when access is available. 

AI agents are already moving into broader enterprise use: 79% of organizations are using AI agents, while 66% of adopters say they’re seeing measurable business value. 

For IT and HR teams in the utility industry, the appeal is straightforward: fewer manual steps between an employee asking for help and getting the work done.  

Agentic AI vs. generative AI and basic automation

AI and automation can all help with employee requests, but they don’t all take the same approach.

• Basic automation follows pre-defined rules or scripts to handle predictable tasks.
• Generative AI creates content, like a summary or answer, based on a prompt. 
• Agentic AI can understand a request, plan the necessary steps, and take action across systems to produce an outcome, within defined guardrails. 

Consider a field technician who needs access to an application. A chatbot might explain the process or route the request. But an agent can verify eligibility, trigger provisioning, and confirm when access is complete. 

The main difference is what happens after the request comes in: agentic AI can sense, plan, and execute across a multi-step workflow rather than stopping with a simple response. 

4 agentic AI use cases for the utilities workforce 

There’s more to supporting a utility workforce than keeping the grid running. Your IT and HR teams also need to help field technicians, operators, and other employees get answers and access as needed, often from miles away from a traditional helpdesk. 

The scale is hard to ignore. The U.S. energy sector alone employs 8.5 million people, including about 1.46 million in transmission, distribution, and storage roles. And power-sector job postings for core roles rose 20% from 2023 to 2025. 

With more people to support and fewer hours to spend on manual requests, the following four use cases show where agentic AI can help. 

Field technician IT support on mobile 

When a technician is miles from the office, a locked account or dropped VPN connection can quickly become a work stoppage. Calling the helpdesk isn’t always practical, especially when the technician needs to get back to the job. 

An AI agent can handle common IT issues from a smartphone in these situations, such as:

• Resetting credentials and restoring access without waiting for IT
• Troubleshooting VPN access and completing the steps needed to reconnect
• Guiding device setup based on the technician’s specific issue 

Every routine request that reaches the helpdesk takes time and money to resolve: a Tier 1 IT ticket averages about $22, compared with $70 for desktop support. When an AI agent can handle simple issues directly, those savings can add up across a large, distributed workforce. 

Seasonal workforce onboarding at scale 

A major storm can change your staffing needs in a matter of days. Through mutual aid networks, utilities can bring in crews from other areas and scale their workforce several times over to respond to a storm or wildfire. 

That also means a lot of onboarding needs to happen at once. 

IT and HR may need to get hundreds or even thousands of workers set up with the right accounts, training, and policies. 

Agentic AI can help take care of many of those steps automatically, like:

• Provisioning accounts based on each crew member’s role and access needs
• Assigning training required for the job
• Surfacing relevant policies based on role, location, and responsibilities 

Rather than working through each onboarding request one by one, your teams can let autonomous systems handle the routine steps while they focus on the people and issues that need their attention.

Real-time safety and compliance policy 

A crew member in the field may need to check a safety procedure before starting a job, not hours later after someone tracks down the right document. That’s critical in an industry with a high electrical fatality rate.

An AI agent can help connect employees with compliance guidance on demand, including:

• Retrieving OSHA procedures based on the task and employee's role
• Surfacing safety protocols that apply to the employee’s location and responsibilities 
• Guiding incident reporting through the required steps 

With permissions based on role and location, employees get info that’s relevant to their work without sorting through binders or searching multiple systems. They can find current guidance when they need it, rather than waiting for a callback from someone in the office. 

HR self-service for distributed employees 

An employee working a night shift or hundreds of miles from headquarters might have to wait until someone in HR is available to answer a question. They may just have a simple request, like how much PTO they have or how to better understand a policy while they’re already on the job. 

An AI agent in HR has the potential to provide that info without making the employee wait long. It can do that based on the employee’s role and permissions and may even take the next step when an action is needed, such as:

• Answering HR questions using the policies and benefits that apply to each employee 
• Competing HR transactions across connected systems, like submitting a request or updating info 
• Guiding employees through policies without sending them to another portal or HR team

Employees get consistent support regardless of where or when they work. HR teams spend less time handling routine requests and more time on the situations that require their expertise.

How a mobile-first architecture changes field support 

Field workers aren’t sitting at a desktop waiting for a support portal to load. They’re moving between sites, working with equipment, and responding to issues where the job takes them. If getting help requires a laptop, support can quickly become something they put off. 

A mobile-first approach puts IT, HR, and safety support where employees already are: on their phones. They can request access, ask an HR question, or look up safety procedures without switching devices or tracking down the right team. 

Employee expectations are changing, too, as AI becomes a bigger part of everyday work. Worker access to AI rose 50% in 2025. As employees get more accustomed to getting help from AI, they expect that same kind of quick, simple support at work. 

For field teams, mobile access makes that support available when and where they need it.

Evaluating agentic AI for utility workforce operations

Once you move from use cases to evaluating a platform, focus on how much of the work it can actually take on. A useful starting point is what happens after an employee makes a request: does the experience stop with an answer, or can the request move through the necessary steps to completion?

Look at a few practical capabilities:

• End-to-end resolution: Can the platform handle the IT or HR steps needed to finish a request? 
• Support across channels: Can employees get help through web, chat, and mobile, including when they’re working in the field?
• Connected systems: Can it take action across the tools your teams already use?

Then connect those capabilities to measurable results, like:

• Ticket deflection: Routine requests resolved without IT or HR involvement
• Mean time to resolution: How quickly employees get their issues resolved 
• Hours saved: Time returned to support teams from reducing repetitive work

These measures help connect the technology to what your workforce and support teams experience day to day.

Security, permissions, and human oversight 

A field technician may need one set of systems and access, while a control-room operator needs another. An AI agent in HR or IT supporting them has to follow those same boundaries. 

Role- and-location-based permissions help control what an agent can access and do, while audit trails show what happened along the way. 

Not every platform gives teams the same level of control. When comparing options, look at how they handle:

• Oversight: Can IT and HR review what an agent did for an employee?
• Escalation: Can system access, safety-related, or other higher-risk requests move to a person for review?
• Auditability: Can you trace what the agent accessed, changed, or completed?

For utility teams, those controls become more important as agents take on more workforce support. Routine requests can move ahead automatically, while higher-risk actions still have a clear path to human review. 

Integration with existing HRIS and ITSM systems 

A utility employee’s request doesn’t always fit neatly into one system. A field technician may need an access change and an HR update resolved before getting back to the job. 

Secure, permissioned integrations with Workday, SuccessFactors, ServiceNow, and identity providers give an AI agent the connections it needs to work across those systems while respecting existing access rules. 

The question is what happens once those systems are connected. 

Can the agent coordinate the steps and see the request through to completion? And can it do that without replacing your core systems or adding people to manage another layer?

That’s the difference between simply connecting systems and actually putting them to work together. For a distributed utility workforce, fewer handoffs can mean faster support and less work for HR and IT.

Building a workforce-ready utility with agentic AI 

When your workforce is spread across substations, control rooms, service territories, and offices, support can’t depend on everyone being at a desk. 

An aging workforce and ongoing hiring pressure add another challenge: experienced employees and lean support teams have less time for password resets, HR questions, and other routine requests. 

Agentic AI has the potential to give employees a way to get those requests handled in the flow of work. 

The Moveworks AI Assistant brings IT and HR support together in one front door, connecting to the systems you use already and giving employees a mobile-first way to get help without adding headcount. 

Here’s how agentic AI has made a difference for one of Michigan’s leading utility companies:

• Consumers Energy: Using Moveworks solutions has helped the energy provider resolve 35% of employee support requests in minutes and saved 16,000 hours of employee productivity in one year.

For utility teams, that’s less time spent tracking down answers and completing repetitive requests. Employees can get help in seconds or minutes from an AI agent, then get right back to work. 

See how Moveworks can simplify employee self-service across your workforce.