Some 88% of global companies already use artificial intelligence, but only some of them are able to implement it at scale, according to McKinsey & Company’s report “The State of AI 2025”. In Poland, EY indicates that the financial sector is the most advanced in this area. However, lack of appropriate skills, regulatory challenges and cybersecurity concerns continue to create barriers to AI implementation in organisations.
“The biggest barrier to implementing AI in financial organisations is primarily the lack of competencies, both internally and in the ecosystem of partners and components from the broadly understood IT environment. The second issue is the experimental approach, meaning the ability to test certain solutions available on the market, which cannot be transferred directly into a financial organisation due to various aspects, including regulatory ones. The third aspect is data and infrastructure management,” Bogdan Nowopolski, Vice President Intelligent Automation Solutions at Betacom, told Newseria.
According to McKinsey & Company’s global study “The State of AI 2025”, the share of companies using artificial intelligence increased over the year from 78% to 88%. However, two-thirds of them are still at the experimentation or pilot stage, while around one-third say they have already begun scaling their AI programmes.
EY’s report “How Polish Companies Implement AI” shows that in Poland the financial sector is the most advanced in this respect. Some 52% of surveyed companies from this industry have already completed their first implementations. By comparison, the figure is 22% in retail and 32% in industry.
McKinsey & Company’s analyses show that companies successfully implementing AI achieve clear business benefits, both in the form of operational savings and revenue growth. Some 64% of surveyed companies say AI enables them to be more innovative. Respondents also point to improved customer experience and stronger competitive advantage. Meanwhile, 39% declare a positive impact on profits.
“On the one hand, we have cost optimisation, and on the other, issues related to investment and potential revenue or profit optimisation, meaning, for example, reallocating resources elsewhere,” explains Bogdan Nowopolski.
Revenue growth resulting from the use of artificial intelligence is most often reported in areas such as marketing and sales, strategy and corporate finance, and the development of products and services.
“The business areas already supported by AI, and in my opinion this is a very promising direction, certainly include operational support, such as analysis of incoming documents and interaction across various channels — voice, email and contact centres,” says the Betacom representative.
According to the EY report, one of the most important barriers to implementing artificial intelligence on the Polish market is concern about security, mentioned by 39% of respondents across all sectors, including finance. For the financial sector, regulatory constraints are an even greater challenge.
Data from the European Commission’s Eurostat show that in 2025 companies in the EU most often used AI for analysing text and documents, as well as for generating content and processing language, both written and spoken. These solutions are also increasingly used to manage internal processes and analyse data, especially in organisations processing large volumes of information. The growing scale of applications increases demand for skills related to integrating AI with existing systems and managing data.
“From an IT perspective, the most important competencies are a certain level of seniority — experience, understanding of processes, data, systems and the entire environment in which we operate — and, on the other hand, the ability to weave AI into the operating model and build a completely new way for the organisation to function. We will need fewer typical technical competencies to build this, while a strong emphasis will be placed on security issues, both internal and in the context of external attacks,” argues Bogdan Nowopolski.
According to the Stanford Institute for Human-Centered AI report “AI Index 2025”, the use of generative AI tools in software development is increasing, including in programming and code testing. McKinsey & Company’s research also points to a change in the structure of IT teams, where the importance of model supervision, systems integration, and quality and security assurance is growing, while the share of simple development work is declining.
“We will need far fewer human resources, especially junior staff, for programming. I know companies that have essentially reduced their developer teams by 95% and shifted to generating code in an alternative way, using artificial intelligence. The next key issue will be ensuring the quality of this software, also from the perspective of the experience of the team creating it, architectural and quality guidelines, and testing it using AI-supported tools,” says the Vice President Intelligent Automation Solutions at Betacom.
