AI Act Compliance for B2B Companies Before 2026
A lawyer received an email asking about the AI Act three months ago. Still waiting for a reply from IT. Meanwhile, the marketing team launched another lead scoring tool, and the marketing automation platform has been running for six months without any documentation. This is not a future scenario, it's the daily reality of most B2B companies in Poland in 2026. Compliance deadlines do not wait for internal sign-off, and fines are calculated on global turnover, not on the local scale of operations.
Which deadlines are already in force, and why risk classification hits tools nobody suspected
The EU AI Act timeline isn't a single deadline. Prohibitions on certain categories of systems came into effect before most boards had appointed anyone responsible for oversight. According to ITwiz data, 58% of Polish companies have begun adapting to AI Act regulations, but as many as 16% of organisations that started implementing the relevant procedures have since abandoned those efforts. For AI compliance in Poland, that is a bad sign, particularly when deadlines are getting closer, not further away.
Risk classification covers more tools than companies assume. Lead scoring systems, automated B2B customer qualification, offer personalisation and product recommendations may all require documentation and conformity assessment, not only HR or credit systems, as most legal departments incorrectly assume. If a marketing automation platform makes or supports decisions about which lead reaches a sales rep and which drops out of the funnel, it is worth asking whether that decision falls under the regulation.
AI in B2B lead generation falls within the new obligations more broadly than most leaders expect. Sales chatbots, conversational agents handling quote requests, recommendation systems in B2B e-commerce, each of these requires disclosure mechanisms for end users. Retroactive governance implementation is more expensive and slower than building it from the start. Fines calculated on global turnover mean that for companies with foreign ownership or operating in EU markets, the financial exposure is many times greater than the local scale of operations would suggest. Counterintuitively, it's precisely the smaller Polish subsidiaries of international groups that are most exposed here, because local management often has no full visibility into which AI systems are running in the company and who bears responsibility for them at group level.
The EU AI Act requires the designation of a person responsible for AI system oversight. The absence of that structure is a signal to enterprise partners and public institutions that the company has not reached the operational maturity required when working with data.
The AI systems register as a board decision, not an IT project
Inventorying the technology stack, meaning marketing platforms, sales automation tools, recommendation systems powering programmatic advertising and growth marketing, is a strategic decision. Its output is an AI systems register that simultaneously becomes a risk map and a due diligence asset during a funding round or acquisition. Boards that hand this topic exclusively to lawyers without involving system architects and business leaders will pay twice: once for compliance done reactively, and again for ground lost to competitors who built regulation-compliant AI infrastructure and are using it as a market argument.
According to a home.pl report, Polish companies are characterised by a phenomenon known as digital leapfrogging, rapidly adopting new technologies but often without the appropriate procedural infrastructure. In the context of the EU AI Act 2026, that gap is precisely where the greatest risk lies.
This is the core of it. Companies that achieve compliance before the required deadlines gain a concrete sales argument with enterprise clients and public institutions, for whom supplier AI compliance is becoming a selection criterion, particularly in the financial, healthcare and industrial sectors. AI integration carried out with regulatory requirements in mind stops being purely an operational cost and becomes part of a competitive offer.
The right approach treats the AI Act as a forced audit of the entire AI infrastructure. It surfaces tools deployed without board knowledge, duplicated licences and systems processing customer data without an adequate legal basis, which in the area of personal data processing also carries obligations towards the Personal Data Protection Office (UODO). This applies directly to marketing and sales departments, where adoption of AI tools in B2B, from scoring to full-funnel automation and performance marketing campaigns, is advancing faster than any approval procedure.
A question worth asking before the next board meeting: can anyone in the organisation point today to every place where an algorithm makes or co-creates a commercial decision that affects a customer?