Knowledge · agent

Deploying an AI Agent in Your Company: How to Succeed with the Rollout

Introducing AI agents in your company: prepare the data foundation, choose a pilot use case, define approvals, bring the team along – step by step.

Deploying an AI agent in your company works best in four steps: first organize the data foundation, then start with a clearly defined pilot use case, properly define guidelines and approvals – and only then expand step by step. Companies that do it the other way around and start with grand ambitions on unstructured data mainly produce disappointment.

Step 1: The Data Foundation Comes Before the Agent

An agent is only as good as the context it can access. If contacts are in one tool, tasks in a second, and documents in a third, it can't establish connections. The first step of the rollout is therefore unspectacular: bring the relevant data into one place and structure it. The article Dissolving Data Silos explains why scattered systems are the core problem.

Step 2: Choose a Pilot Use Case

For the start, choose a task with three characteristics:

• Recurring: The benefit adds up with every run.
• Clearly defined: It's clear what a good result looks like.
• Low risk: Mistakes are annoying but not costly – so initially no tasks with direct external impact.

Proven candidates: checking documents for deadlines, creating regular summaries, preparing tasks from cases. The article AI Agents: 7 Examples provides concrete ideas.

Step 3: Define Guidelines and Approvals

Now the agent gets "set up" – in two senses:

• Guidelines: Describe not only what it should do, but under what conditions. Example: only create deadlines when date, obligation, and source are clearly documented; report uncertain cases instead of creating them.
• Approvals: Determine what the agent may do independently and where a human decides. As a principle, it has proven effective: anything with external impact – emails, calls, master data changes – goes through an approval.

In webRichtung agent, this is exactly the architecture: you activate automations individually, with adjustments like a minimum confidence level; whatever awaits your decision is collected in the inquiries section – you review the suggestion together with its context and approve or reject it.

Step 4: Bring the Team Along and Expand

The biggest hurdle is rarely the technology, but acceptance. Three things help:

1. Transparency: Show the team what the agent does and does not do – the approval principle makes it an assistant, not a replacement.
2. Evaluation: After four to six weeks, look at the pilot together: what did it handle, where did it go wrong, which guidelines are missing?
3. Gradual expansion: Only once the pilot holds up do further use cases get added – with the same rules.

Low Barrier to Entry

For the pilot, you don't need a project budget: at webRichtung, account and users cost €0, you only pay for actual usage via Credits (1 Credit = 1 Euro net). This lets you test the benefit of an AI agent in real operation before larger decisions are due – and the risk of the rollout stays as small as the pilot itself.

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