Nearly all organizations surveyed by KPMG worldwide already have an AI strategy, and more than two-thirds say artificial intelligence is delivering measurable business value. At the same time, only 8% of companies have achieved a real return on investment, while just 11% can be considered AI leaders capable of scaling the technology effectively across the organization. According to KPMG International’s “Global AI Pulse Q1 2026” report, the main challenge is no longer access to AI tools, but the integration of technology with business processes, organizational structures and decision-making. Poland is no exception to this trend, with KPMG experts observing the same pattern among domestic clients.
The “Global AI Pulse Q1 2026” report launches KPMG International’s recurring study measuring the maturity of organizations in the use of artificial intelligence. The analysis highlights a divide between organizations that can turn AI investments into lasting business value and companies that, despite growing budgets, still fail to achieve scalable results.
Scale of deployment does not guarantee success
KPMG’s study shows that nearly four in ten organizations are already at the stage of broad AI deployment, yet most still do not achieve measurable business outcomes. The problem is not a lack of ambition or limited access to technology, but the way AI is implemented.
Companies most often add new solutions onto existing organizational structures instead of changing their operating model. By contrast, companies classified as AI leaders focus on building integrated systems that connect data, processes and decisions across the entire enterprise.
Data from the “Global AI Pulse Q1 2026” report shows that the number of pilots is not a measure of success. In Poland, interest in AI is growing rapidly. Companies are actively experimenting with generative AI, process automation and language assistants. Many of these initiatives deliver very good results at the level of individual processes. The challenge emerges when organizations attempt to scale them.
“In our advisory practice, we see the same pattern identified globally by the report: artificial intelligence is being added to existing structures rather than leading to their redesign. Organizations are trying to use AI to do the same things as before, only faster and cheaper. Real value, however, appears as a result of redesigning decision-making, improving coordination between departments and building a work model based on cooperation between people and AI. This requires changes in areas such as governance, incentive systems and the division of responsibility,” says Leszek Ortyński, Director and AI & Data Science Leader at KPMG in Poland.
Governance and security become prerequisites for scaling AI
The KPMG report also shows that three-quarters of surveyed executives identify security and risk issues as among the main barriers to further AI development. The most frequently cited challenges concern data privacy and cybersecurity, both indicated by 42% of respondents, followed by data quality at 34% and regulatory uncertainty at 31%.
Organizations with the highest AI maturity, however, do not treat governance as a constraint on innovation, but as a foundation that enables technology to scale. Companies that integrate risk management directly into the architecture of AI systems gain control over deployments more quickly and make better use of the potential of new solutions.
Polish companies have solid foundations: strong technological competence and a pragmatic approach to investment. At the same time, growing regulatory pressure in the European Union, particularly the AI Act and regulations such as DORA in the financial sector, is forcing companies to build governance alongside implementation.
As the report shows, creating governance structures makes it possible to clearly define rules of responsibility, control and supervision, thereby supporting the effective scaling of AI. The biggest challenge remains fragmented data and older, often dispersed IT systems, which make it harder to scale AI across the organization.
“The key recommendation is simple: AI success should be measured by its impact on business results, not by the number of tools implemented. It is equally important to understand that governance and employee skills are foundations, not add-ons. These are the areas that will determine lasting competitive advantage,” adds Leszek Ortyński.
Employee skills remain the weakest link
One of the most concerning findings from the report is the low level of employee readiness to operate in an AI-based environment. Only 22% of respondents express high confidence that their employees are able to meet the demands of an AI-driven workplace.
At the same time, companies that are confident in the readiness of their teams are almost four times more likely to achieve measurable business outcomes than organizations facing skills gaps.
Different sectors, different pace of AI maturity
The most advanced sector in terms of AI adoption remains TMT, covering technology, media and telecommunications. Organizations in this area are increasingly building AI-native architectures, integrating multi-agent systems with key business processes.
The financial sector is developing AI more cautiously due to high regulatory and compliance requirements, focusing on governance models that support implementation. Retail and consumer goods companies are concentrating mainly on the use of AI in sales, marketing and customer experience management, while the healthcare sector is primarily dealing with challenges related to trust, responsibility and clinical risk.
About the report
“Global AI Pulse Q1 2026” is the first edition of KPMG International’s recurring study on the level of advancement in the use of artificial intelligence in global business. The study is conducted quarterly and analyzes the transition of organizations from individual deployments to coordinated AI management at the enterprise level.
The survey was conducted online between February 19 and March 17, 2026. The sample included 2,110 executives and senior managers from organizations with annual revenues exceeding USD 100 million. Respondents represented 20 countries and eight sectors of the economy, including technology, financial services, manufacturing, retail and consumer goods, healthcare, energy, real estate and construction.
