David Novák (Kogi CON): How AI helped salespeople grow by 30%

In this episode of the no-holds-barred Kogi podcast, Pavel Kuhn and David Novák look back on their own experience using artificial intelligence in consulting work. Over the past year, they went through a phase of enthusiasm, experiments, and dead ends. One of the first major realizations was that AI isn't just another tech trend — it's an accelerator of change that can dramatically widen the gap between people who actively use new tools and those who ignore them.

The first genuine breakthrough came in data analysis and synthesis. Transcripts of interviews and workshops, which used to take hours or days to process, could be turned into structured output within minutes. Automating internal processes had a similar effect. David, for example, used ChatGPT to build a tool that automated preparing outputs from corporate culture surveys, replacing work that used to take several days.

Alongside the successes came important lessons too. Kogi, for instance, tried automatically transcribing and processing every internal meeting. The technology worked perfectly, but the practical impact was the opposite of what they wanted. People got more emails, more notes, more information. Instead of higher efficiency, it created more informational noise. That's exactly where the team realized that automation on its own doesn't create value.

The biggest success eventually came in sales. Based on transcripts of sales meetings, they built the AI Sales Coach, which gives salespeople instant feedback on their meetings. What mattered wasn't the technology itself, but how it was rolled out. Instead of a blanket deployment, work started with a handful of volunteers who helped co-create the tool. That let them overcome resistance to change and build a solution that delivers measurable results today.

A strong theme in the podcast is also the fact that most companies don't start with the right question. Instead of looking for specific problems, they often think about everything that could be done with AI. According to David, the right approach runs the opposite way. First, you need to find activities that are repetitive, time-consuming, and low in added value. Only then does it make sense to look for a technological solution.

Kogi's whole experience confirms that AI adoption isn't primarily a technology project. It's a change in how work gets done, requiring the same principles as any other transformation — a clear owner, an understanding of people's needs, and enough room for gradually adopting new habits. Technology can be a very powerful lever, but on its own, it won't guarantee the change.

What else will you find answered in the podcast?

• What were the first genuinely functional AI use cases in consulting work?
• Why can automating every meeting have the opposite effect?
• How did the AI Sales Coach come about, and why start with volunteers?
• Why do most companies start with the wrong question when adopting AI?
• How do you correctly identify activities suited for automation?
• Why is AI adoption an organizational project, not a technological one?

If you want to get real value out of AI, don't start by hunting for new technologies or complex integrations. Start with the problems that currently cost your people time, energy, and attention. Only once AI helps solve something employees genuinely need does it stop being an interesting toy and start becoming a tool that changes how the company works — and its results.