Between hype and reality: how Polish firms use AI

Artificial intelligence (AI) is increasingly supporting business, yet most companies are still at the implementation stage, and a real return on investment takes time. The key question is not whether AI works, but where and under what conditions it begins to generate value.

Employers are closely monitoring market trends and analyzing the potential of new technologies, gradually implementing them within organizational structures. However, this process remains at an early stage of development, which means that the return on investment in AI-based solutions is not yet widely felt.

Moreover, poorly executed implementations can generate costs that exceed the anticipated benefits. A significant challenge also lies in the insufficient skill preparedness of employees, which amplifies their concerns about technological change.

– Artificial intelligence is increasingly supporting creativity, teaching, problem-solving, and teamwork. This is changing the profile of the desired employee – from an expert in a single technology to someone who combines soft, digital, and business competencies – notes Paweł Łopatka of Experis.

So where is the “sweet spot”? This point is partially addressed in the report “AI in Companies: Applications, Limitations, and Skills Challenges,” prepared by Experis.

The return on AI takes time and organizational maturity

Experts at Experis emphasize that the level of return on investment (ROI) in artificial intelligence solutions is strongly dependent on an organization’s digital maturity, the scale of capital expenditure, and access to data. In the conditions of the Polish market, many companies are still at the pilot stage, which translates into limited visibility of short-term financial results.

– The return on investment in AI is not yet widely visible today because most companies are still in the implementation phase. In practice, tangible business benefits usually appear after 12–36 months. The first year is about experimentation, data integration, and teaching the organization how to work with artificial intelligence. The fastest ROI is seen where technology automates repetitive processes, and the slowest in areas requiring a profound shift in operating models. Many companies continue to bear the costs of transformation before they achieve economies of scale – says Adam Jakubowski, IT labor market manager and expert at Experis, in an interview with XYZ.

He notes that one of the key mistakes made by organizations is treating artificial intelligence solely as a technology project. Also critically assessed is the narrative focused mainly on cost and headcount reduction, as well as an insufficient level of managerial competence in implementing and managing transformation.

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Where do companies most often use AI?

According to respondents in Experis’ study, Polish companies most widely deploy artificial intelligence in areas related to idea generation and the support of creative processes. It also plays an important role in employee education and training, as well as in customer service and operational problem-solving.

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Aleksandra Żak, Head of Experis Academy Development and Partnerships, notes that the implementation of AI-based solutions in the workplace has the strongest impact on competencies related to information processing. This primarily concerns data analysis, idea generation, communication, and technical expertise.

In practice, this translates into a growing need to integrate domain-specific knowledge with the ability to effectively use AI tools. At the same time, the importance of conscious and critical use of technology is increasing, including the assessment of output quality and an understanding of its limitations.

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Initial expectations regarding the use of AI in recruitment, onboarding, and training have proven partly unrealistic, particularly in terms of technological autonomy. In practice, AI is not capable of independently running processes or reliably assessing candidates in areas that require context and soft skills.

Companies have also revised the assumption that AI would replace people. Some organizations have concluded that its real value lies in productivity gains, and that its effectiveness depends primarily on data quality and integration with existing processes. As a result, implementations are now seen as operational change rather than a workforce revolution.

The labor market increasingly rewards competencies that combine technology with business understanding, while moving away from overly optimistic narratives toward a more pragmatic approach.

Implementation challenges and employee concerns

“From the perspective of Experis Academy, our brand specializing in the development of future skills, this shows that the market is not aiming to replace people with AI, but rather to increase work efficiency by augmenting it,” notes Aleksandra Żak, as cited in the report.

At the same time, data indicate that the vast majority of companies in Poland are facing difficulties in implementing AI-based solutions. These issues affect as many as 93% of firms and stem mainly from concerns about data privacy and regulatory uncertainty. Only 7% of respondents declare that they face no barriers.

– In the short term, the development of artificial intelligence increases employee concerns. These are driven mainly by uncertainty, a lack of clear communication, and a narrative focused on human replacement by technology. In the long term, however, in organizations that manage change well, these concerns diminish. AI begins to be perceived as a support tool rather than a competitor – says Adam Jakubowski.

He acknowledges that employee concerns are partly justified.

– Some roles, especially those based on routine information processing, will be reduced or disappear. At the same time, new competencies and roles will emerge, related to AI oversight and decision-making responsibility. The problem is not the technology itself, but the pace of change, which is often faster than companies’ ability to reskill their workforce – adds Adam Jakubowski.

AI as an operational shift, not only a technological one

In the context of effective AI implementation, a process-oriented approach is crucial – not a purely technological one. This includes ensuring high-quality data, defining measurable performance indicators, and integrating AI tools into the day-to-day operations of teams. Without these elements, data-driven solutions remain at an experimental stage, failing to translate into real business value.

– A safe environment for employees is built through transparency and a practical approach. Clearly defining what AI is used for, training based on real-life cases, and involving employees in pilot programs significantly reduce resistance. Artificial intelligence should be presented as a decision-support tool, not a mechanism of control – emphasizes Adam Jakubowski.

Paweł Łopatka, in turn, notes that from the employee’s perspective, openness to using AI is becoming an important element of job security. This does not require an immediate overhaul of competencies, but rather a willingness to test tools, participate in training, and ask the right questions. A passive or negative attitude, however, may adversely affect both career development and the functioning of the organization.

Key Takeaways

1. The biggest challenges related to AI implementation concern regulatory issues, data privacy, and skills shortages. These problems are reported by as many as 93% of companies. At the same time, technological development is reshaping the employee profile. The importance of combining technical, business, and soft skills is increasing, along with the need for conscious and critical use of AI.
2. The implementation of artificial intelligence in Polish companies is still at an early stage, which limits short-term returns on investment. As Experis experts note, tangible business benefits typically emerge only after 12–36 months. The initial period is mainly devoted to experimentation, data integration, and learning how to work with the technology.
3. AI is most commonly used in areas that support creativity, training, customer service, and operational problem-solving. At the same time, initial expectations regarding its applications – particularly in recruitment – have been revised. The technology does not replace people but enhances their productivity and requires high-quality data as well as integration with business processes.