AI tool use is growing fast in most organizations, and agentic AI is a big part of where that growth is headed. According to Gartner, 40% of enterprise applications will feature task-specific AI agents by the end of 2026, up from less than 5% in 2025.*

Key Takeaways:

• Agentic AI uses the same generative AI technology as tools like ChatGPT and Copilot, but it’s built into a system that can carry out a process on its own.
• Generative AI tools respond to what you ask and stop. Agentic AI carries out a defined process without needing a person to direct each step.
• Building an AI agent starts with documenting how a process actually works, which also tells you whether an agent is the right tool for it.
• AI agents deliver expected benefits like time savings, consistency, and speed, along with less obvious ones like visibility and resilience when someone’s out or leaves.
• An AI agent needs ongoing documentation, review, and management to keep delivering value as your business changes.

What Makes an AI Agent Different

An AI agent uses the same generative AI technology behind tools like ChatGPT, Copilot, and Claude. The difference is how it’s used. A generative AI tool is the whole product. In an AI agent, that same technology becomes one part of a larger system built to carry out a process, with access to your tools, the ability to take action, and awareness of where it is in the process

That structural difference changes how each one behaves. A generative AI tool waits for a person to ask something, gives a response, and stops. The person decides what happens next, whether it’s a back-and-forth conversation or a sequence of prompts set up to run automatically.

An AI agent works differently. It’s given a process to follow and the tools it needs to carry that process out. Once it’s set up, it runs that process on its own. It still needs a person to step in when something falls outside what it’s been trained to handle, but it doesn’t need a person to direct each step along the way.

AI Agents Are Like Interns

Think of an AI agent like an intern you’ve trained on a specific process. You walk them through the steps and tell them what to do when something looks a certain way. From there, they run that process themselves, handling the routine judgment calls, and they come to you only when something doesn’t fit what you trained them on.

Consider how each tool can assist with invoice processing. A generative AI tool can help you design an invoice template, draft payment terms, or write the policy for how invoices get handled. An AI agent can receive an actual invoice, extract the data, match it against a purchase order, route it for approval, and update the accounting system, with no one at a keyboard moving it from step to step.

Process Documentation Comes First

Before you can build an agent to run a process, you have to document how that process actually works. That means the exceptions, the judgment calls experienced people make without second thoughts, and the institutional knowledge that lives in people’s heads and nowhere else. That documentation can also tell you whether an agent is the right tool at all.

Some processes are simpler than they seem and a generative AI tool handles them fine. Others have too much variation for an agent to handle reliably. Mapping the process answers the question before you invest in building anything.

Where AI Agents Deliver the Most Value

Agents work best where a process has a predictable pattern, involves multiple steps across systems or departments, and currently depends on someone manually moving work forward.

New hire onboarding is a good candidate for an AI agent. When someone joins the company, a series of tasks must happen across HR, IT, and management: accounts created, licenses assigned, equipment configured, access granted, notifications sent. A delay in any one step holds up everything else. An AI agent moves the process forward automatically and brings a person in only when a decision is needed.

Other potential opportunities for process automation with agentic AI include compliance reporting, data entry between systems, invoice processing, and routine status updates that currently require someone to compile and distribute manually.

Read a Use Case: AI-Powered Invoice Processing for a Growing Finance Team

Expected and Surprise Benefits of Agentic AI

Some of what agentic AI delivers is exactly what you’d expect.

Time back. Routine work runs without a person doing it manually, freeing your team for work that requires judgment, relationships, or creativity.

Consistency. An agent applies the same rules the same way every time. There’s no missed step from a busy day, and no variation in how a routine decision gets handled.

Speed. A process that depends on a person runs at the speed of that person’s schedule. A well-built agent runs as soon as the conditions are met, day or night.

Other benefits tend to surprise people once they’re actually running a process with an agent.

No single point of failure. When one person is the only one who knows how a process works, their vacation, sick day, or resignation becomes a problem for everyone else. An agent that runs the process doesn’t take time off and doesn’t walk out the door with the knowledge of how things get done. That holds true as long as someone keeps the agent’s setup current as your business changes.

Visibility you didn’t have before. A well-built agent can log what it does at each step, so you can see where things stand, where they slow down, and whether the process is running at all. Many manual processes never had that kind of visibility to begin with.

A clearer picture of your own operations. Defining an agent’s rules requires documenting how work actually gets done, often at a level of detail most businesses haven’t captured before. That documentation gives you a clearer picture of your own operations, separate from whatever the agent ends up doing.

Generative AI and Agentic AI Each Have Their Place

There’s a place for generative AI tools like ChatGPT, Copilot, and Claude, tools that respond to what you ask and stop. And there’s a place for agentic AI, tools that carry out a defined process on their own. Knowing which one fits the job in front of you is the first step.

Getting agentic AI right takes more than a successful deployment. As your business changes, the agent needs to change with it. That requires someone documenting what’s been built, reviewing it regularly, and managing it as part of your full IT environment, not as a standalone tool that gets set up and forgotten.

This is where a lot of businesses run into trouble. They either try to manage automation themselves without the expertise, or they bring in a separate automation vendor who doesn’t know their IT environment and isn’t responsible for the rest of it. Either way, the connections that should exist between systems don’t get made, and what should be one coordinated environment becomes a collection of disconnected tools.

XPERTECHS is a Managed Intelligence Provider. We handle IT management and security, understand how your business operates, and design, implement, and manage AI and automation as part of one coordinated environment.

To talk through where agentic AI fits in your business, contact us.

Source: Gartner August 2025