A recruitment agency uses AI to rank applications. An industrial SME experiments with a document assistant. A retailer installs a chatbot. Behind these uses, the same questions arise: who controls the system, what data flows through it, and what records must be kept to demonstrate compliance? With the AI Act, these questions are shaping a market for European entrepreneurs. Provided they sell something other than a regulatory binder or fear-driven training.
This analysis looks ahead to September 2026, drawing on the adopted regulation and known developments. The deadlines discussed reflect the legislation’s original timetable, subject to any subsequent amendments. The commercial prospects are hypothetical, not a quantified assessment of the market at that date.
A market born of a shift in responsibility
The European Union’s artificial intelligence regulation, which entered into force on 1 August 2024, sets out obligations according to risk levels and the roles of the actors involved. Certain prohibitions and the obligation to take measures to ensure sufficient AI literacy have applied since February 2025. The original timetable provides for most of the legislation to apply from August 2026, with provisions covering certain high-risk systems embedded in regulated products applying from August 2027.
For an SME, the difficulty begins before any procedure: understanding its role. Is it simply a user, described as a “deployer” under the regulation, or a provider of a system marketed under its own name? Has it substantially modified a tool? Does its use qualify as high-risk? Software that screens applications and a writing assistant are not automatically treated in the same way. Classification requires an examination of the system’s actual function.
This is where demand emerges. Small businesses rarely have a team combining legal experts, data specialists and technical managers. They may purchase one-off expertise, followed by ongoing support. But a commercial misconception must be avoided: the AI Act does not require the same documentation from every business using AI. A good service provider starts by defining the scope of the obligations, not by maximising the bill.
First opportunity: making documentation usable
Documentation may seem unremarkable. Yet it offers a practical starting point. Taking stock of systems, identifying those responsible for them, retaining providers’ instructions, describing their purposes and organising incident reporting: this work turns a collection of software subscriptions into a manageable portfolio of tools.
For high-risk systems, the requirements are more extensive and differ between providers and deployers. Technical documentation, risk management, human oversight and log retention are not responsibilities that fall equally on every actor. A compliance firm can help allocate these responsibilities and gather the relevant evidence, without claiming to replace the assessments required under the regulation.
A useful product is not a PDF generator
A credible offering connects documentation to the system’s lifecycle. When a model changes, a new data source enters the process or a use case expands into recruitment, the documentation must be reviewed. Tools that combine an inventory, internal approval and a change history could therefore offer greater value than static libraries of templates.
The business model could combine an initial assessment with a subscription. Its value, however, depends on the time actually saved. An SME does not need a sprawling platform for three simple use cases. Sector-specific offerings designed for HR consultancies or industrial software vendors would have an advantage: speaking the industry’s language and reusing tailored procedures.
Second opportunity: providing training without selling a bogus licence
AI literacy offers another entry point. The regulation requires providers and deployers to take measures to ensure a sufficient level of knowledge among the people concerned, taking account of their experience, the context and the groups affected. This creates room for training providers, but does not establish a mandatory universal certificate.
The differentiator will be workplace scenarios. A recruiter must understand the limitations of automated rankings and the risks of discrimination. A salesperson must know which confidential information must not be copied into an external service. A manager must recognise when human approval is needed. A general presentation on large language models is not enough to meet these needs.
For an entrepreneur, the strongest offering would combine short workshops, job-specific exercises and follow-up on working practices. It must be possible to explain what was taught, to whom and why. Training then becomes a tool for reducing errors, rather than merely a certificate filed away.
Third opportunity: governing data
Data is the least visible area of work and often the most enduring. Who can access the documents used by an internal assistant? Is their reuse authorised? Do they contain personal information or trade secrets? Are they suitable for the intended use? Here, the AI Act intersects with the GDPR, cybersecurity and contractual rules, without replacing them.
The specific data governance requirements for high-risk systems should not be presented as an identical obligation for every chatbot. But the associated methods — traceability, quality control and access management — can benefit many businesses. A service provider can therefore sell an operational improvement of which compliance is one component.
This market favours teams capable of working within existing systems. Identifying sensitive files or correcting permissions requires more than a legal recommendation. Combining consulting, data engineering and security could become a differentiating factor.
A real opportunity, not a guaranteed revenue stream
Competition will come from consultancies, lawyers, training providers and governance software vendors. AI providers may also build more documentation and controls into their products. Public resources and shared tools, meanwhile, will reduce the value of generic services.
Entrepreneurs will therefore have to demonstrate their usefulness: speeding up procurement approval, clarifying responsibilities or preventing an unsuitable deployment. They will also need to protect the data their audits give them access to and distinguish between support, legal advice and formal assessment. A promise of automatic compliance would be a red flag, particularly if it ignores actual use cases.
The strongest positioning could be that of a specialist partner: a team that knows a sector, works with transparent pricing and leaves behind processes that the SME can realistically maintain.
What next? If the timetable and implementation arrangements confirm this trajectory, AI Act compliance could become a lasting market, extending beyond the initial assessment. For European entrepreneurs, the challenge will be to turn a regulatory constraint into a management capability. The winners will not necessarily be those producing the most documents, but those making AI use understandable, controllable and useful.
