AI Adoption in Romania Is Lagging Behind. Companies Can No Longer Afford to Wait.
In 2025, only 5.2% of companies in Romania with at least 10 employees used AI technologies, compared with 20% across the European Union.
The figure is low enough to trigger two opposing reactions.
The first is: “AI is not yet relevant to our market. We will wait.”
The second, and strategically correct, is: “The market is not yet crowded. We can now build in a more structured way than the companies that will react too late.”
For many marketing managers and business owners, AI remains a subject filled with promises, new tools and the fear that the investment will be difficult to justify.
This hesitation is understandable.
But it often stems from an important misunderstanding: adopting AI in a company’s operations is not the same as preparing the company for an environment in which people search, compare and ask for recommendations through AI systems.
A company does not need to build its own AI model for its digital reputation to already be assessed by ChatGPT, Gemini, Perplexity, Google AI Overviews, Claude, Grok, and others.
The practical question is not whether the technology will become relevant.
It is already relevant to information search.
The question is whether the information about your company is clear, consistent and credible enough to be understood correctly when such questions arise.
What Will You Find in This Article?
1.What does the difference between 5.2% and 20% actually mean?
2.Why are AI adoption, AI Trust and AI Visibility three different things?
3.Why is the current period a window for preparation, rather than an argument for delay?4.What can a company do without turning AI into an endless technical project?
1. What Does the Difference Between 5.2% and 20% Mean?
The data presented at Romanian Digital Day in June 2026 refer to companies with at least 10 employees that used AI technologies in 2025.
The European comparison is relevant:
Romania is well below the EU average of 20% and far from the European target of 75% by 2030.
The European Commission's 2026 Digital Decade country report is part of the official package of national reports for all Member States.
For Romania, the conclusion is clear: the country has strong fixed connectivity infrastructure and has taken important steps in areas such as semiconductors and AI, but competitiveness is limited by low levels of basic digital skills, weak innovation among SMEs and start-ups, as well as low levels of technology adoption by companies.
The Commission also recommends using European Digital Innovation Hubs to increase companies' digital maturity.
This is the real issue.
Not the lack of an AI application installed in one department, but the risk that many companies treat transformation as a one-off purchase: a subscription, a chatbot or a few texts generated more quickly.
In reality, competitive advantage does not come from simply using a tool. It comes from the ability to make better decisions, make company information verifiable and build trust before the market becomes far more competitive.
More importantly, the European average is not a static benchmark. The overall State of the Digital Decade 2026 package shows that almost 20% of European companies use AI, and adoption grew by 48% in 2025 alone compared with the previous year.
The Commission describes the European challenge with an apt formulation:
the foundations are in place, but they need to be executed at scale.
For Romania, this means that today’s gap will not be closed by waiting.
The benchmark against which we measure ourselves continues to advance.
2. AI Adoption Is Not the Same as AI Visibility
A company may have a department that uses AI every day and still be almost invisible in AI-generated answers to questions that matter to its customers.
Likewise, a company may appear occasionally in an answer, but its description may be incomplete, unclear or even incorrect.
This is why it is useful to separate the three levels.
AI adoption means using AI technologies in internal operations: automation, analysis, content, customer support, specialised software or other processes.
AI Trust means the signals that allow a company to be assessed as a credible source: a clear identity, evidence of expertise, services explained accurately, identifiable authors and experts, case studies, relevant certifications, consistent information and independent confirmation.
The methodology through which these signals are built and measured is explained in the MirioDev guide to Digital Authority and AI Visibility.
AI Visibility measures the extent to which a brand appears, is described accurately, is cited or is recommended in answers generated for relevant questions in its field.
All three matter, but they do not have the same starting point.
For a manufacturer, distributor, construction company, B2B supplier or professional services brand, the first step is not necessarily to automate its entire activity with AI.
The first step may be to understand what information a system can verify about the company when a potential customer asks for a recommendation, compares two solutions or looks for a specialist.
This is why being cited by AI does not depend on a page “written for AI”.
It depends on the quality of the digital ecosystem that supports that page: the website, service and product pages, evidence of experience, external publications, the consistency of brand information and the way all these elements connect with one another.
3. The Current Window Should Not Be Mistaken for a Lack of Urgency
In a market with low adoption, organisations can clarify responsibilities, evidence and internal rules before the use of AI becomes difficult to control.
This is a strategic interpretation, not an official conclusion, but it accurately reflects the cost of delay:
it is easier to bring order to information, processes and responsibilities before they multiply.
For companies that do not develop their own AI systems, the equivalent is just as concrete.
They can now correct outdated information, insufficient pages, contradictory commercial messages and authority gaps before every competitor begins mechanically publishing something new.
The European Commission report also highlights an important reality for trust:
64% of Romanian respondents believe that AI development must be carefully regulated to ensure safety, even if this may limit developers.
The concern does not disappear if a company avoids the subject.
On the contrary, the public will look more closely for evidence of who the company is, what it knows how to do and how safe it is to work with it.
In this context, trust is not a campaign message.
It is the result of the evidence the company can demonstrate and that other sources can confirm.
4. What Companies That Choose to Wait Lose
Waiting until “everyone uses AI” may seem prudent, but in digital environments, passive caution often ends up costing more than early preparation.
First, the competition for credible sources will intensify.
As more companies review their websites, publish case studies, consolidate their brand in external sources and structure their information, the difference between a mature ecosystem and a neglected one becomes more visible.
Second, brand problems become more expensive when they are discovered too late.
A website with outdated pages, vaguely described services or products, contradictory information or a lack of evidence is not merely an SEO issue.
It can also contribute to the incomplete way a company is understood by customers, journalists, partners and AI systems.
I explained in detail why AI can describe a company incorrectly and why the mere existence of a website does not guarantee that it will become a cited source.
Third, companies lose the time needed to build authority.
There is no command that can turn a brand into a reference overnight.
Digital authority is built through useful content, verifiable information, demonstrated experience, relevant mentions and logical connections between a company’s own pages.
These elements need consistency, not haste.
5. Where a Company Can Start, Without Unnecessary Projects
A serious initiative does not begin with the promise that “we will appear in all AI answers”.
That would be an unrealistic promise, because answers differ depending on the question, platform, context and the sources each system can use.
It begins with an honest audit of digital reality.
a.Assessing how the company is understood today.
Relevant non-branded questions are formulated for real customers, then the brand’s presence, how it is described and the sources that support that presence are observed. This approach differs from simply searching for the company name.
b.Repairing pages with commercial value.
Service, product, expertise, reference and contact pages must answer customers’ questions concretely. A generic page, without specifications, examples, responsibilities or evidence, does not help either people or systems trying to extract useful information.
c.Building evidence, not just content volume.
Case studies, documented projects, identifiable authors, verifiable certifications, explained methodologies and clear answers to difficult questions matter more than a series of articles without substance.
d.Strengthening external signals.
A company cannot validate its own reputation on its own. Relevant publications, editorial appearances, portals and professional associations, partnerships and independent sources all contribute to the context in which a brand is assessed. Their selection must be based on field, audience and objective, not only on an authority metric.
e.Periodic measurement.
AI Visibility must be monitored through consistent questions, relevant platforms and indicators that separate brand appearance from description accuracy, citation and recommendation. Otherwise, any isolated result can be mistaken for real progress.
This is also the principle behind how some companies come to appear in AI answers: it is not about a trick, but about the consistent accumulation of the signals a brand makes available to the digital market.
The practical application of this methodology can also be followed in MirioDev case studies.
6. The Useful Decision Is Not “AI or No AI”
For a marketing manager or business owner, the choice should not be framed as “do we invest or not in a technology we do not yet fully understand?”.
The real choice is simpler: do we remain with a digital ecosystem built for traditional search, partially updated and difficult to verify, or do we prepare it for a digital market in which information is increasingly synthesised, compared and recommended through AI systems?
Not all companies need the same project. Some first need a clearer website.
Others need case studies, expert content or external sources to confirm what they claim.
Some need to resolve brand inconsistencies accumulated over the years. However, almost every company needs to understand its starting point.
Romania is not lagging behind because companies have not purchased enough AI tools.
It is lagging behind when technical potential does not translate into adoption, capability, trust and economic results.
This is precisely why the current period is valuable: companies that are now building their digital authority and trust signals do not wait for the market to explain why it was necessary.
They are preparing their position before the market becomes too crowded.
