Internal AI Champion: Who to Appoint Inside the Company and What to Ask Them

Every founder thinking about AI quickly hits the same question: who will do this in our company? Hiring an external consultant is expensive, and sending the whole team to training is risky if you don't know where to start. This is where the internal AI champion comes in — not a machine learning expert with a diploma, but an employee who understands business processes and can translate them into the language of AI agents. Their job isn't to write code, but to decide which tasks are worth automating first and to verify that the solution works on real data. Such a person shortens the path from idea to first working automation by weeks, because there's no need to explain to a consultant how your sales or accounting department operates.

What Skills an AI Champion Really Needs

Technical depth isn't the priority here. The champion doesn't need to understand model parameters or write Python scripts. They need to:

• Clearly describe a business task in words: where the bottleneck is, which routine eats up time, where errors happen due to human factors.
• Distinguish what can be standardized and what requires human judgment.
• Know how to work with test data: if the task is about expense tracking, take a sample of monthly invoices and show where the target aligns.
• Set success criteria: how will we know the automation works? For example, "time spent preparing proposals dropped from 2 hours to 15 minutes" or "data entry errors decreased by 80%."

Such a person often comes from warehouses, sales, or accounting — exactly where there are many repetitive actions. For example, a sales manager who prepares commercial proposals every week can quickly grasp how to describe a template for an AI agent: "if the client asks for product A with volume B, add the standard calculation for timeline and cost."

What to Expect from an AI Champion in the First Month

Don't expect them to build a complex ERP integration in a week. The first month is about learning and the first win. The champion should:

• Take one of the three priority tasks chosen together with the founder (e.g., analysis of off-site meetings by geolocation or a commercial proposal generator).
• Launch their first micro-automation in the browser by the second session of the intensive — this could be a simple script that pulls data from a table and formulates a client email.
• By the end of the intensive, have a working automation that executes the agreed-upon scenario on real or test company data.
• Get access to the recorded video course and technical assignment templates so they can train colleagues.

If after a month there isn't a single working solution — that's a signal that either the task was chosen incorrectly (too abstract), or the person doesn't understand how to translate business logic into words for AI. In that case, consider replacing the champion or simplifying the task.

How to Interview a Candidate

Don't ask about technical details. Focus on business understanding and the ability to learn new tools. Example questions:

• "Describe the last routine that ate more than three hours of your week. How would you automate it?"
• "How do you gather information for your monthly report? Where do you see an opportunity to reduce manual work?"
• "How would you verify that a new tool works correctly? What data would you use for testing?"
• "Have you ever tried working with chatbots or tools like Make, Zapier? What worked, what didn't?"

Answers should show the person analyzes the process, not just follows instructions. If they say "I'd hire a developer," that's a red flag. The champion should try it themselves, even if the first attempt isn't perfect.

How this works on our side: In our corporate program, each participant describes business logic in words, and AI writes the code. Every participant launches their first micro-automation in the browser already on the second session. After the intensive, the company gets at least 3 working automations on priority tasks, with a money-back guarantee. https://course.aiadvisoryboard.me/corporate?utm_source=blog&utm_medium=article_body&utm_campaign=corporate

When You Need More Than One Champion

In companies with over 20 people, one champion can become a bottleneck. Then it makes sense to create a small group — 3–5 people from different departments. This gives you:

• Coverage of key business areas (sales, operations, finance).
• Ability to work in parallel on different tasks.
• Internal training: champions train their teams without waiting for external instructors.

The group works most effectively when each member has a clearly defined zone of responsibility. For example, one handles reporting automation, another processes requests, the third supports customers. This avoids duplication of work and allows faster scaling of successful solutions.

Conclusion

An internal AI champion isn't about technology — it's about who understands your business and can translate it into the language of AI. Appoint such a person from a department with many repetitive tasks, give them one clear task to start, and check the result in a month — is there a working automation? If yes, expand the group. If not, change the task or the person, but don't stop.

Tomorrow, take the first step: pick one employee who complains about routine, ask them how they'd automate their least favorite task, and propose trying it themselves next week.