For entrepreneurs in Romania, the conversation about artificial intelligence has moved beyond fascination. The question is no longer whether AI will change how companies operate, but when and how. In 2024, only 3.07% of Romanian companies with more than 10 employees were using AI technologies, the lowest percentage in the European Union. The gap is not driven by lack of technology, but rather by lack of clarity: what AI means for a mid-market business, where to start, what is worth doing now and what is not, and how to evaluate an implementation partner. In this context, the decision to integrate AI is no longer optional. It is a strategic decision that defines a company’s competitiveness in the coming years.
Why 97% of Romanian companies are not using AI yet — and what is actually holding them back
Further details on AI integration in business processes were gathered through a discussion with Silviu Niculeci, AI Operations Consultant within Arggo, an IT company specialized in software development and business consulting, with more than 500 implemented digitalization projects.
„In discussions with entrepreneurs, two extremes consistently block AI adoption. On one side, the myth of magic: the belief that AI can simply be installed and everything solves itself. On the other side, the myth of impossibility: the idea that AI is only for tech giants, not for mid-market companies in Romania. The truth lies somewhere in between: AI is a highly capable tool when integrated into clear processes, supported by quality data, and used responsibly. It is neither miracle nor luxury. It is a means, not an end. And success is measured in problems solved, not in the number of models used.” – Silviu Niculeci, AI Operations Consultant, Arggo
Market reality confirms this balanced position. AI technology has become accessible through cloud services with costs at the level of a few cents per thousands of processed characters, integrable via API into almost any digital platform. The real barrier is no longer budget. It is the correct formulation of the problem to be solved. And here lies the difference between a license vendor and an implementation partner that understands the business.
The AI agent that handles routine steps: what it can do and where it stops
Over the past year, AI capabilities have evolved significantly. While a year ago discussions focused on isolated automation steps – receiving an email, processing it through an AI application, and returning structured data – today the focus is on AI agents capable of following entire procedures, making decisions within defined rules, acting on real-time data, and escalating exceptions to humans. The practical difference is substantial: an agent does not only classify a complaint email; it checks the customer’s history in the ERP system, formulates a response according to internal policy, and sends a draft for approval. Routine steps are removed from human responsibility. What remains are the decisions that matter.
To turn this technical capability into real value for entrepreneurs, Arggo has structured an AI offering organized as a natural journey: from education, to strategy, to implementation, to ongoing support. The entry point is the workshop program, AI Workshops, designed to directly address entrepreneurs’ need to understand what AI can and cannot do within their industry, without generic slides and without a large financial commitment.
„Many entrepreneurs purchase a Microsoft Copilot license and, after a few months, realize the team is using it just as little as before. Not because the technology does not work, but because no one has explained concretely how it applies to their specific workflows. This is the problem solved through workshops. The starting point is AI Foundations – a two-hour session where the team understands what an AI agent is, what prompts are, and how consistent results are obtained. For those who already have or plan to use a Copilot for Business license, the four-hour version also includes Copilot Agents – scenarios with agents, roles, and delegated tasks. The most applied format is AI Applied: there are no prepared slides. The session starts with a direct Discovery Call with the department team, identifying real workflows and daily bottlenecks, and only then building a live session. Participants leave with tested prompts and functional configurations applied to their own processes. There is also a Prompt-a-thon format – four hours in which each participant brings a real problem and leaves with a live-built solution. No generic training. Concrete value on the existing license.” – Silviu Niculeci, AI Operations Consultant, Arggo
For companies that decide to go further, the next stage is AI Discovery: a structured evaluation over two to four weeks in which company processes are systematically analyzed, AI opportunities are prioritized by impact and feasibility, and the deliverable is a concrete map with effort estimates and clear success criteria. Not a presentation of what AI could do in general, but a specific analysis for that business.
If the Discovery phase justifies continuation, the next step is the Proof of Concept, a functional solution built on the client’s real data and a real process, over two to four weeks. Not a demo, but a working prototype with success criteria defined from the start. At the end of the PoC, the decision to move toward full implementation is based on measured results, not promises. Only then does the process enter the Implementation phase – full development, integration with existing systems, testing, production deployment, and end-user training. After go-live, AI Support ensures the solution does not degrade over time as processes and platforms evolve.
Workshop, Discovery, PoC: what an AI project that actually reaches production looks like
This structured approach – Workshop, Discovery, PoC, Implementation, Support – is not bureaucracy. It is the mechanism through which entrepreneurs avoid paying for an AI solution that works perfectly in presentations but delivers nothing in reality. It is also the answer to one of the most common pitfalls seen in companies entering AI without a partner: buying before understanding what is being solved, resulting in pilot projects that never reach production.
„There is a simple question used in every Discovery discussion: can a human do this? If the answer is yes – if a person can follow that procedure, process that data, and make that decision – then AI can likely do the same, faster and at scale. If the answer is no, AI will not solve it either. Then three practical criteria come in: the cost of human work versus AI cost for that task, the frequency and consequences of errors, and how predictable the task is. AI works extremely well on large volumes and clear structures. It performs poorly on exceptions. The predictable part is automated, and exceptions remain with humans. Where mistakes cost more than the savings achieved, human validation is not optional – this is the Human-in-the-loop principle. It is also part of the EU AI Act requirements, which are gradually coming into force.” – Silviu Niculeci, AI Operations Consultant, Arggo
However, there is an area rarely discussed publicly by providers, yet it defines whether an AI project lasts or collapses within six months: data, processes, governance, confidentiality, and support. AI output quality depends entirely on input data; no technology compensates for a chaotic foundation. AI cannot automate what is not understood; if workflows exist only in the heads of key people, the first step is documentation, not automation. Any AI output used in operational decisions or client deliverables must be validated and owned by a human within the organization. Client data does not enter public model versions, and any serious provider must clearly explain where data is processed and how it is isolated. Finally, deployed AI systems degrade without ongoing support as processes and platforms evolve.
Here is where the experience of Arggo becomes relevant. With more than 500 projects implemented across industries such as healthcare, banking, manufacturing, retail, distribution, agriculture, and construction, and through its own platform Timeqode, Arggo brings a real understanding of the business logic behind ERP systems and operational workflows. The end-to-end Microsoft stack – Azure AI Foundry, Copilot Studio, Microsoft 365 Copilot, Dynamics 365 – enables extension of an existing ecosystem rather than introducing a new vendor. For clients using Timeqode, AI capabilities integrate natively, without additional integration costs.
„At Arggo, this AI direction was first built internally. Internal processes were used for testing, what works and what does not was documented, the methodology was built step by step and refined before being offered to clients. The Innovation Award for Artificial Intelligence in Business Solutions received recently is not viewed as a final result, but as recognition of a serious approach: strategy, methodology, and assumed responsibility. For Romanian entrepreneurs evaluating whether to invest in AI solutions, the message is simple: do not start by buying technology, start with a conversation. Together with a partner who understands the business, identify a process where a human currently performs repetitive and predictable work. From there, the build begins.” – Silviu Niculeci, AI Operations Consultant, Arggo
For entrepreneurs observing the market, the current period represents an open window. The Romanian mid-market and enterprise segment is still in the early stages of AI adoption. Companies acting now build expertise, validate approaches, and gain reference advantage. In 12 to 18 months, adoption costs are expected to rise and experienced implementation partners will be less available. This is not artificial urgency, but the natural dynamic of an early-stage market.
Ultimately, AI integration is not about licenses or models. It is about direction: how a company builds its ability to make decisions faster, reduce errors in repetitive tasks, and free people for work that matters, such as customer relationships or strategic decisions. Microsoft 365 Copilot, Azure AI Foundry, Copilot Studio, and BPM platforms such as Timeqode provide the technical infrastructure. Workshops, Discovery, and structured implementation methodology provide clarity. And the choice of the right partner can determine the difference between a pilot project that remains a demo and a business genuinely transformed by artificial intelligence.
