Defining High Impact Use Cases When Deploying AI Agents

How organizations can move from experimentation to measurable business value.

AI agents are rapidly transforming how work gets done, and, as highlighted in Deloitte’s Prompting for action: How AI agents are reshaping the future of work (2024)—forward thinking organizations are already deploying agentic systems across a wide range of high value use cases. The leaders in this space aren’t just experimenting; they’re moving with intent, identifying the right opportunities, and scaling AI agents to deliver tangible impact.

But that impact doesn’t happen by accident. Organizations need a deliberate roadmap that focuses on the use cases where agentic AI can deliver the greatest value and directly support broader business objectives. At Cegeka, we see this every day: companies that define clear, high value use cases achieve faster adoption, higher employee enthusiasm, and dramatically better outcomes.

In this blog, you’ll learn exactly how to do that.
We’ll walk through what makes a use case “high impact,” how to score and prioritize them, how to align agent design with KPIs and human oversight, how to validate data readiness, and which categories consistently deliver the strongest ROI. By the end, you’ll know how to select use cases that not only work, but scale, so you can unlock real, measurable business value with AI agents.

Start With a Clear Business Problem, Not a Technology

A high impact use case always begins with a specific pain point, inefficiency, or opportunity. This step should answer a simple question: “Where can an AI agent measurably improve how people work?

Typical triggers include:

• Repetitive manual tasks
• Slow data retrieval across multiple systems
• Complex workflows with many steps
• High error rates
• Limited workforce capacity

Score and Prioritize Use Cases With a Structured Framework

Not every idea becomes a viable AI agent. Organizations need a repeatable scoring model that evaluates:

Figure 1: Use Case Scoring Model

Evaluating whether a use case is truly suited for an AI agent requires a structured assessment across four dimensions: business value, feasibility, risk, and strategic alignment. Organizations start by estimating the potential impact, how much time can be saved, where accuracy can improve, and which tasks can be meaningfully automated. Next, they examine feasibility: Is the data accessible and reliable? How complex is the system landscape? Is integration realistic?

Risk is assessed by looking at compliance sensitivity, automation risks, and the need for human supervision. Finally, the use case is evaluated against organizational priorities to ensure it contributes directly to strategic goals rather than becoming an isolated experiment. This structured evaluation helps teams separate high value opportunities from low impact ideas and ensures AI agents are deployed where they can make a measurable difference.

For teams that want to kickstart their use case prioritization, Cegeka offers AI Discovery Workshops. A guided, end-to-end process where our experts help you identify high impact opportunities, assess feasibility, engage stakeholders, and define a clear adoption roadmap.