The implementation of AI has become a necessity in business processes, particularly in order to make customer service efficient and sustainable. AI agents in particular are becoming increasingly popular as a fully-fledged automation option for complex processes.

But with the seemingly endless possibilities for using AI agents such as chatbots and voicebots and defining specific use cases, many executives face a challenge: where to start? It's easy to get excited about the technology, but the real art lies in identifying and prioritizing an actual initiative that delivers real business value and has a realistic chance of success.

This is exactly where we want to help and show you how to proceed systematically to successfully define and evaluate your AI agent use case.

In our interactive Use Case Check, you can also find out how mature your use case already is and how you should proceed.

The search for the right use case often begins with a pain point analysis. An agent is useful when a task requires cognitive flexibility but is still repetitive.

The critical point here is validating the necessity: Is AI really the best solution, or is there a simpler, more cost-effective alternative that solves the problem just as well?

Take the time to precisely define the type of interaction (e.g., pure self-service, support for human agents, or a mixture) to ensure that the initiative is optimally tailored to the company's requirements. This is the only way to avoid developing a complex AI solution for a simple problem.

To build the agent, we need to understand who it works for and what the goal is. A classic user story helps to focus on user value.

This format forces a clear focus on benefits and prevents the project from getting bogged down in trial-and-error mode. It ensures that every AI function is directly aligned with a measurable advantage. 

By writing these stories, you create a shared, easily understandable vision that brings everyone involved in the project together. In doing so, you not only define what the agent should do, but above all, for whom and why it is important.

AI projects often fail because the financial or strategic benefits remain unclear. Therefore, defining an AI agent use case is only sustainable if a clear return on investment (ROI) can be demonstrated. Identifying the relevant key performance indicators (KPIs) and establishing a baseline are crucial for measuring the actual business value added by the AI initiative.

In order to assess success, it is necessary to setting a baseline is essential. Document the current status of your KPIs before implementing the AI agent ("Where are we today?"). 

Only by directly comparing the metrics before and after implementation can you validatethe actual benefits of the AI agent use case implementation in retrospect .

You can use our ROI calculator to calculate the return on investment of your AI agent project in advance.

An agent who can do "everything" usually can't do anything properly. Define clear guardrails to minimize risk and increase accuracy.

• Channels: Through which channels should the AI agent be accessible? (Phone, chat, email) And where should it be embedded? (Website, service hotline, intranet)

• Input sources: What data should the agent have access to? (e.g., only PDFs from folder X).

• Tool access: Is the agent permitted to send emails directly or only save drafts? (Human-in-the-loop).

• Out-of-scope: What should the agent explicitly not do? (e.g., not negotiate prices).

Examples of areas of application: 

The areas of application extend far beyond simple chatbots and affect almost all areas with high, recurring communication or data management needs.

In customer service and CX:

In other areas of the company:

Choosing the right application area for the AI agent depends heavily on where the highest implementation feasibility (existing data and systems) meets the highest expected ROI.

Successful implementation often requires integrating the agent with existing internal systems (CRM, ticketing, knowledge databases) in order to equip it with all necessary actions.

At BOTfriends, we know that defining an AI agent use case is just the beginning. Success depends on a strategic approach tailored to the company. 

Use four-dimensional evaluation:

Before you start with broad implementation, each AI agent use case must be systematically evaluated. Based on Quiq's blueprint "How to Identify + Evaluate Agentic AI Use Cases," we recommend evaluating along four key dimensions to obtain a balanced picture:

• Implementation feasibility: Are the systems, data, and team technically ready for implementation?
• Expected ROI: Are the financial or operational benefits clear and significant?
• Customer impact: Is a relevant customer problem solved and the experience significantly improved?
• Strategic alignment: Does the use case fit with the company's long-term goals and is it scalable for future innovations?

Questions about each dimension are rated on a scale of 1-5. An overall score then determines the best course of action.This structured AI agent use case assessment reduces the risk of misinvestment and ensures that you focus on the use cases with the highest potential.

Our tip – start with a targeted pilot project:

Even a promising use case requires caution. A focused pilot project is the right way to test feasibility and validate viability before rolling out the project for broad implementation.

BOTfriends as your strategic partner:
Defining your use case is just the beginning of your AI automation journey. With our flexible AI Agent Platform , we offer you not only market-leading technology, but also accompanying expertise.

BOTfriends combines the power of an enterprise AI platform with maximum independence by securely automating complex voice, chat, and email processes through reliable orchestration all the way to the backend. Thanks to our no-code architecture and guided sovereignty approach , you retain full process control and achieve fast results without relying on expensive integrators or high operational overheads.

Even if your use case received a low rating in the interactive check or you are still facing a "black box," we invite you to contact us. Together, we will analyze your initial situation and develop a roadmap that combines technological feasibility with real business value.