Generative artificial intelligence has shifted in the past three to four years from a technological curiosity to a tool present in corporate routines. Filó Angéla Katalin, founder of AI‑Mentor, says many Hungarian companies are experimenting with AI but deep business integration remains rare: pilot projects are common, and only a few organisations have turned experiments into established processes.
How did her engagement with AI begin?
Filó does not come from an IT background; she encountered generative AI as an economist, marketer and manager. Her initial reaction was fear — she worried the tool could replace parts of her work and that younger graduates might arrive with confidence in using such tools. That concern pushed her to learn: she studied prompt engineering, handling hallucinations, data security and how different AI tools operate. That deliberate learning process eventually led to founding AI‑Mentor.
What market gap did AI‑Mentor address?
She found plenty of theoretical knowledge in Hungary but little practical assistance. Executives are not interested in the technical distinctions between machine learning and deep learning; they want to know which systems to subscribe to and what business outcomes to expect. AI‑Mentor starts with audits: they map existing workflows and build strategies on top of them. Filó emphasises that AI should not be treated as an isolated technology project but as a means to automate and optimise workflows — for example, preparing an offer is a multi‑step process of research, pricing, document creation and correspondence, not a single task.
Where does AI deliver the fastest ROI today?
Marketing shows the most immediate returns: video content, campaign analysis and personalisation yield quick, visible results. Customer service, administration and sales are also areas where AI can produce large time savings because much of the work involves searching for documents, emails and information.
Which sectors are moving fastest, and which lag behind?
The financial and telecommunications sectors, the pharmaceutical industry and manufacturing tend to advance quicker because they have many repetitive, rule‑based processes suitable for automation. Marketing, customer service and IT also progress rapidly. Traditional manufacturing and smaller family businesses move more slowly, but paradoxically they can achieve fast wins because a single decision in a small firm can enable a rapid rollout.
What hinders SMEs most?
Filó identifies distrust as the main barrier: concerns about data and system reliability. She points out that today even small companies can access capabilities that were once available only to large enterprises.
Are employees fearful or curious about AI?
Fear exists, but curiosity is generally stronger. Most people do not fear AI taking their jobs; they fear not being able to use it effectively. Practical training with everyday examples quickly reduces uncertainty, and mastering prompt engineering becomes a key skill.
The risk of templatisation and the value of human contribution
AI produces standard solutions well, but true value lies with people: ideas, creativity, critical thinking and unique perspectives. Lexical knowledge alone will be less valuable over time; connecting dots and inventing new solutions will matter more.
Advice for leaders and professionals
Short‑term reliance on external experts is possible, but in the long term those who learn the basics themselves will be advantaged. Filó’s message to managers is that AI is not a future technology but a current competitive edge. Conscious adoption — subscriptions, training and leadership support — will develop both company performance and employees’ skills. Within a few years the difference will show up not as a technical gap but as a business advantage or disadvantage.
(Interviewee: Filó Angéla Katalin, founder of AI‑Mentor.)
