Last week, Neurotrack CEO Vitalii Miniailo spoke at Brave CFO Gathering 2026, an event for CFOs, CEOs and business owners where the conversation is about concrete numbers, not technology hype. His talk and a separate hands-on workshop were titled “AI in the finance function: where CFOs really lose money, time and competitiveness.”
The format was candid: no glossy presentations about “the future belongs to AI” — instead, a breakdown of real cases, numbers and the mistakes Ukrainian companies make when bringing AI solutions into finance.
What the workshop covered
Together with the Neurotrack team, participants worked through:
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- how to build AI-driven budgeting that actually saves the finance team time instead of creating more work;
- automated plan-vs-actual analysis — and where it genuinely shortens the reporting cycle;
- how to calculate ROI before a project starts, instead of justifying the costs after the fact;
- the typical reasons business automation stalls in the finance function — from the lack of a process owner to unrealistic expectations about timelines.
“Today it’s hard to find a business process where AI couldn’t deliver results — the only question is how precisely you can pinpoint where to look for that impact. The finance function is no exception: almost any routine process can be made faster or cheaper if you approach it as a specific problem to solve rather than an abstract technology rollout.” — Vitalii Miniailo, CEO of Neurotrack
Why this isn’t “just another event”
The CFOs and business owners we talk to run into the same problem with surprising regularity: the finance team is drowning in routine work — consolidating reports, chasing approvals, manual plan-vs-actual — instead of focusing on strategy. Optimizing the business through targeted automation of these processes frees up exactly the resource that is always in short supply: the time of the people who should be making decisions, not assembling spreadsheets.
Neurotrack applies this approach not only in finance but in other areas of the business too. A few examples of what it looks like in practice:
- Fora retail chain — document workflow automation built on Vchasno, which took some of the manual approvals off the team’s plate.
- Sheriff — an AI voice agent that handles routine calls, leaving people the more complex tasks that need their judgment.
- Podorozhnik pharmacy chain — an AI agent that helps pharmacists navigate a huge range of medicines and find alternatives for customers faster.
Different industries, different tasks — but one shared principle: AI solutions for business work when they solve a specific, measurable problem, not when they’re rolled out “because everyone else is doing it.”
Our take
For several years now, Neurotrack has been working where business meets technology — with pharma, retail, agriculture and construction. We deliberately don’t open a conversation with a client with the words “artificial intelligence.” We start with a question: where exactly is the company losing money or time, and will the implementation justify the resources invested? Technology is the second step.
Thank you to the organizers of Brave CFO Gathering 2026 for the invitation, and to the participants for sharp questions, real cases and a willingness to talk openly about what works in AI projects and what doesn’t. Conversations like these are the best sign that the market is maturing: Ukrainian companies don’t want a technology demo — they want results they can measure.
If your company is considering AI solutions for its finance function or other processes, the Neurotrack team is open to a conversation about concrete numbers for your business.
