1AI is everywhere. The results barely show.
In mid-2026, nearly nine in ten McKinsey respondents said their organizations used AI regularly in at least one area.1 Only 37% see any impact of it on operating profit in their results. And companies where AI delivers at least 5% of operating profit (EBIT) and significant value make up about 6%.1
People feel it: in a 2024 Gallup survey, 45% of American workers who use AI said it had made them more productive.2 But companies fully built on AI are still rare — the authors of All-in on AI (2023) put them at less than 1% of large companies.3
At the same time, analysis itself got cheaper the way few things in history ever have. In October 2024, querying a GPT-3.5-level model cost 7 cents per million tokens — in November 2022 it was $20. More than 280 times cheaper in under two years.4
Analysis got cheap. Decisions didn’t.
Today everyone has access to the same artificial intelligence. The same model can write a report for a corporation and for a two-person company from Kraków. If the tool is the same, the difference isn’t in the tool.
2In Poland, we are at the very beginning
In 2025, one in five companies in the European Union with at least 10 employees used AI. In Poland — 8.36%. That is one of the three lowest results in the EU.5 The smaller the company, the rarer it is: 55% of large companies in the EU use AI, but only 17% of small ones.5
Most are in no hurry. 77% of Polish companies that don’t use AI have no plans to adopt it “until it becomes necessary.”6 This is what the start typically looks like: a new technology is first taken up by the boldest, fewer than 5%, and together with the early adopters — 15–20%.7 Poland is exactly there. Whoever starts now starts ahead of the majority.
The most interesting part, though, is why. Among EU companies that considered AI but did not use it, the most common reason is not price, not technology and not regulation. It is a lack of relevant expertise — named by almost 71% of them.5
The problem isn’t access to AI. The problem is that the company doesn’t know what to give it and what to do with it.
3Where the problem really lies
In a small company, knowledge is everywhere and nowhere. Some of it sits in the owner’s head. Some in emails, in spreadsheets, in the CRM, in invoices, in meeting notes. None of these systems talks to the others. No one has the whole picture — except the owner, who has no time to look at it anyway.
So decisions get made the way they get made: fast, from memory, on gut feeling. A price “because competitors charge something similar.” A supplier “because they were first.” A tool “because someone recommended it.” And the constant feeling that you could do better — that you don’t understand something, that one bad decision could cost a lot, that somewhere there are levers you aren’t using.
We know this from our own experience. For 12 years, one of us worked in large corporations, where no important decision was made in the dark: there was data, there were procedures and there was someone who double-checked. Then we built our own companies together — ZANA Cosmetics, Superblends and ZU_O Creative Agency. Two people, no team, no analytics department. And suddenly every decision was ours.
It wasn’t one bad evening. It built up: prices, suppliers, campaigns, tools, clients. Each decision small on its own; together — a constant sense that we didn’t know something and that one mistake could cost a lot. We realized that in a small company the problem isn’t a lack of work. The problem is a lack of clarity.
Adding AI to this fixes nothing by itself. If you throw a chatbot a question without context, you get a confident answer without context.
4What’s missing: three things at once
First — connected company knowledge. What the owner knows and what already sits in the company’s tools and systems, gathered in one place where AI can use it. Without it, every analysis starts from zero. McKinsey estimates that as much as 70% of the work on an AI solution is cleaning up and connecting data.8 The good news: for a given use case, usually only about 10–15% of the data elements matter most.8 We start there.
Second — method. Good business decisions have a structure: where to start, what to check, what not to do. This knowledge exists — in the best books on strategy, finance, sales and management. But a small-company owner has no time to read them, let alone turn them into procedures. We do it for them: we turn the best knowledge from business books into methods, each one a single document and a single decision, and we keep them up to date.
Third — the skill to use AI. AI analyzes, remembers and proposes — and in tasks it knows well, it really helps. In a BCG experiment, consultants with AI did 12% more of these tasks, 25% faster and more than 40% better than without it.9 The weakest gained the most — but everyone gained.10 Yet on a task deliberately set beyond what AI can do, consultants with AI were right in 60–70% of cases, those without AI in 84%.9 AI doesn’t say when it is past its limit. People trust it then just as much as ever. That is why the tool alone isn’t enough: a person has to know when to trust AI, when to check it and when to decide on their own. That is what we teach.
None of these things is enough on its own. Knowledge without method is an archive. Method without knowledge is theory. AI without either is faster guessing.
5What we do
We connect a company’s knowledge — from the owner’s head, its tools and systems — with our frameworks and with AI that analyzes, remembers and proposes. We advise, implement and teach the firm to use it, so it makes clear decisions.
We call it simply: intelligence with AI. Not another dashboard. Not another chatbot. A company that knows what it knows — and can turn it into a decision.
We work in the tools the company already has. We start with the business, not the technology: first we understand how the company makes money and where it gets stuck, and only then do we choose the tool. For new companies, these are the foundations they can grow on. For companies that are stuck — a way out of where they stand.
We turn your plan into an advantage.
6Why this will only grow
AI gets cheaper every year. That is good news, but it has a flip side: when everyone has the same tool, the only advantage is what others don’t have — knowledge about your own company, about your own clients and about what worked and what didn’t.
Every decision recorded today is material for tomorrow’s analysis. A company that starts connecting its knowledge now decides faster a year from now. In three years — faster than anyone who started later. This advantage compounds. So does the gap.
7What we don’t do
Our values have a cost, so we say plainly what we turn down because of them:
- We don’t promise a return on investment before we’ve seen your company. We tell the truth — even when it doesn’t sell.
- We don’t hold your knowledge hostage. Everything we build stays yours. Nothing important stays in one head — ours included.
- We don’t sell AI as a way to lay people off. AI analyzes and proposes. A person decides.
- We don’t pretend to be bigger than we are.
8Where we are today — honestly
We are two people from Kraków: Maciej — 12 years in large corporations (processes, systems, teams, risk control, CAMS certification), Zuzanna — a designer and the founder of ZU_O Creative Agency. We run three companies of our own and test everything we offer on them first.
We built ourselves a Company Brain before we started selling it: the best knowledge from business books turned into our own methods (each one a single document) that we keep developing, all our companies’ data in one place and our own app for managing projects and clients, written with the help of AI in seven days.
Every month we write about how it is really going: what we built, what we sold, what didn’t work out. No faked momentum.