In the latest episode of the Vedd fel a versenyt! podcast, host Cserjés‑Kopándi Ildikó, a PwC Hungary expert on digital economy and commerce, spoke with Kolbert István and Kelemen Ákos about the current state, future and organisational challenges of artificial intelligence. The discussion referenced PwC’s 2026 domestic AI study: 90% of online shoppers recognise the concept of AI, and about 60% already use AI‑based tools consciously in everyday life.
Where and how is AI used in everyday life?
According to the survey, AI usage spans multiple areas: 66% of respondents use AI for answering private questions, 40% for translations, and 32% for work‑related queries. The last figure is particularly notable because it shows AI’s presence in corporate operations even where no formal organisational strategy exists.
The barrier is organisational, not primarily technical
Participants emphasised that corporate AI maturity often stalls for reasons other than technology — many required tools and services are already available. The real obstacles are existing routines, expectations, approval processes and organisational culture. A typical pattern is initial enthusiasm for a new AI tool that fades because workflows and day‑to‑day practices do not change to integrate the technology sustainably.
Differences between large companies and SMEs
In large enterprises, regulation and strict approval processes can slow adoption. By contrast, smaller companies and SMEs often experiment faster and deploy off‑the‑shelf solutions more quickly because they face fewer internal hurdles. However, SMEs typically operate with fewer resources: they may lack dedicated AI teams or enterprise‑grade infrastructure. For them, adaptation often depends less on building bespoke systems and more on smartly using existing market tools.
Speakers noted that scarcity can be an innovation driver: when budgets, people or time are limited, organisations must rethink problem solving.
Ban is not a substitute for governance
A key point was that banning AI usage is not a solution. If an organisation does not set internal, regulated frameworks for AI, the technology will still enter workflows informally and often unmonitored. In such cases, AI becomes embedded through individual solutions, which carries data security, operational and reputational risks.
Therefore the issue is not whether people use AI, but whether the organisation can provide safe, professional frameworks for its use.
Labour market effects and changing competencies
The labour market impact of AI is already apparent: entry‑level, routine roles are particularly exposed. This does not only mean headcount reductions; it also shifts how competencies are valued. Increasingly important will be the ability to understand, direct and audit complex processes — including those involving AI tools.
Tool or partner? The importance of mindset
Kolbert István summed it up: “Sometimes a tool, sometimes a partner.” The discussion argued that the label matters less than the fact that AI already appears at early stages of problem solving. When people turn first to an AI system rather than Google, or when their initial thought about a task is “how can AI help here?”, the technology has moved beyond a mere assistive device and has become part of the thinking process.
Invoking the Jarvis example from the Iron Man films, the experts suggested AI systems are increasingly able to handle tasks through conversational interfaces, connect information and perform background subtasks. That shift presents both opportunity and risk: the more we treat AI as a partner, the more important it becomes to define which data it can access and where human oversight must remain.
Practical implications for organisations
Using AI is rapidly ceasing to be a distinct skill and is becoming a new baseline for work. Competitive advantage will not come from being the first to try a new tool, but from converting spontaneous experiments into deliberate organisational capabilities: integrating AI into daily processes, decision‑making and workplace culture, identifying where it speeds tasks, where it reduces errors, and where human control remains essential.
The strategic question now is whether companies will steer the AI‑driven change, or simply react and try to catch up later.
