AI agents are everywhere right now.
Every week there’s a new demo showing an agent researching markets, summarizing documents, or automating entire workflows. The promise is exciting. The reality is a little messier.
The biggest mistake teams make with AI agents isn’t technical—it’s strategic. They try to build one before figuring out whether they actually need it.
That’s why learning how to identify the right AI agent use case is essential. When you understand which workflows actually benefit from an agent—and which don’t—you can avoid wasted effort and focus on opportunities where AI genuinely helps.
Why identifying the right AI agent use case matters
AI agents are designed to complete multi-step tasks, make decisions within defined rules, and interact with systems over time. In the right situation, they can streamline processes and reduce manual work.
But not every workflow needs that level of automation.
In many cases, a simpler AI tool—like a prompt-based assistant or a basic automation—can solve the problem more easily. Trying to force an AI agent into the wrong situation often leads to complexity without meaningful value.
That’s why identifying the right AI agent use case is such an important early step.
Before thinking about implementing an AI agent, teams need to ask questions like:
- Is the workflow repeatable and structured?
- Are there clear goals and measurable outcomes?
- Does the process involve decision points an AI system could reasonably support?
- Would automation actually improve speed, accuracy, or efficiency?
Answering these questions helps teams separate exciting AI ideas from practical opportunities.
In other words, a strong AI project usually starts with a well-defined use case—not the technology itself.
What you’ll learn in an AI agent workshop
One of the fastest ways to understand how AI agents fit into real work is to analyze workflows directly.
In our workshop, AI Agent Discovery: Find the Right Use Case, participants follow a structured process for evaluating whether an AI agent approach makes sense.
During this three-hour, hands-on workshop, you’ll learn how to:
- Evaluate whether a workflow is a strong AI agent use case
- Break down processes into steps, decisions, and outcomes
- Define goals and constraints before technical development begins
- Communicate a clear, defensible use case to stakeholders or technical teams
The goal isn’t to build an AI agent during the session. Instead, the focus is on developing the strategic thinking needed to identify where agents can realistically help (and where they’re a waste of time).
Because in many organizations, the biggest challenge isn’t building AI systems. It’s figuring out where they add the most value.
What makes a live, hands-on workshop different from self-guided learning?
You can read dozens of articles about AI agents and still feel unsure how they apply to your own work—because most examples focus on finished tools, not the decision process behind them.
Our hands-on workshop taught by a real-world pro approaches the problem differently.
Instead of learning about AI agents in theory, you:
- Analyze real workflows step by step
- Identify friction points and decision boundaries
- Evaluate whether automation actually improves the process
- Develop a clear AI agent use case grounded in real work
Working through this process with guidance helps the concepts click much faster than reading about them in isolation.
It also helps you avoid one of the most common mistakes in AI adoption: starting with the build instead of the problem.
Who should learn how to identify an AI agent use case?
You don’t need a technical background to evaluate whether an AI agent makes sense.
In fact, many of the people best positioned to identify strong AI opportunities are the ones closest to day-to-day workflows.
This type of workshop is especially helpful for:
- Professionals hearing more about AI agents but unsure where they fit
- Nontechnical teams evaluating AI ideas before involving engineering
- Operators, strategists, or product leaders analyzing workflow efficiency
- Teams exploring automation opportunities within existing processes
- Anyone curious about how AI agents apply to real business tasks
If your role involves improving processes, evaluating tools, or shaping strategy, understanding how to identify a strong AI agent use case can quickly become a valuable skill.
Sometimes the most useful AI insight isn’t how to build something. It’s recognizing whether it should be built in the first place.
A simple example of evaluating an AI agent use case
Imagine a team responsible for reviewing customer support tickets.
Every day, new messages arrive describing issues, questions, or feature requests. Team members read the tickets, categorize them, and escalate certain cases to the right department.
At first glance, this might sound like a good candidate for an AI agent.
But before jumping to automation, the team needs to examine the workflow.
Are the tickets structured enough for an AI system to interpret consistently? Are the decision rules clear? Are there defined outcomes—like routing tickets or summarizing issues—that an agent could perform reliably?
If the answers are yes, the workflow might represent a strong AI agent use case.
But if the process requires frequent judgment, ambiguous interpretation, or constantly changing criteria, a simpler AI assistant might be more effective.
This type of evaluation helps teams focus on realistic opportunities instead of chasing trends.
Start identifying AI agent use cases in your workflow
If you’re curious about how AI agents might fit into your work, learning how to evaluate workflows is a powerful first step.
Our AI Agent Discovery: Find the Right Use Case workshop walks through this process step by step. Participants analyze real workflows, define clear goals, and assess whether an agent-based approach makes sense—without needing to design or build anything.
In just a few hours, you can go from vague AI ideas to a clearly defined AI agent use case grounded in real workflows.
And if exploring AI strategy sparks your interest, this workshop is also a starting point for our AI Fundamentals pathway, where you can build a deeper understanding of how AI systems, automation, and agents fit into real business workflows. Many successful AI initiatives start with people who know how to identify the right opportunities before technology enters the conversation.
Because the smartest AI projects don’t start with code. They start with the right problem.
Frequently asked questions
Do I need technical experience to take this workshop?
No. The workshop is designed for nontechnical professionals who want to understand where AI agents can realistically support work.
What tools will I use during the workshop?
Participants use free large language models such as ChatGPT or Gemini to explore workflows and evaluate potential use cases.
Will I build an AI agent during the workshop?
No. The focus is on identifying and defining a strong AI agent use case, not building or deploying a technical system.
What kinds of workflows work best for AI agents?
Workflows that are structured, repeatable, and have clear goals and decision rules tend to be stronger candidates for AI agent support.