Almost all organisations surveyed by KPMG globally already have an AI strategy, and more than two-thirds say artificial intelligence is delivering measurable business value. Yet 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 organisation.
According to KPMG International’s report “Global AI Pulse Q1 2026”, the biggest challenge is no longer access to AI tools. The real barrier is integrating artificial intelligence with business processes, organisational structures and decision-making models. 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 regular study measuring organisational maturity in the use of artificial intelligence. The analysis highlights a growing divide between companies that are able to turn AI investments into lasting business value and those that, despite rising budgets, still fail to achieve scalable results.
Scale of Implementation Does Not Guarantee Success
The KPMG study shows that nearly four in ten organisations are already at the stage of broad AI implementation. However, most of them are still not achieving tangible business outcomes. The problem is not a lack of ambition or limited access to technology, but the way AI is being implemented.
Companies most often add new solutions to existing organisational structures instead of changing their operating model. By contrast, organisations identified 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, we are seeing rapid growth in interest in AI – 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 appears when companies try to scale them,” says Leszek Ortyński, Director and AI & Data Science Leader at KPMG in Poland.
“In advisory practice, we see the same pattern identified globally in the report: artificial intelligence is being added to existing structures instead of leading to their redesign. Organisations are trying to use AI to do the same things as before, only faster and cheaper. Meanwhile, real value appears as a result of redesigning decision-making, improving coordination of processes 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 responsibilities,” he adds.
Governance and Security Become Conditions 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 mentioned challenges are data privacy and cybersecurity, each indicated by 42% of respondents, followed by data quality at 34% and regulatory uncertainty at 31%.
However, the most mature AI organisations do not treat governance as a factor limiting innovation. Instead, they see it as a foundation that enables technology to scale. Companies that integrate risk management directly into the architecture of AI systems gain control over implementations faster and are better able to use the potential of new solutions.
“Polish companies have solid foundations: strong technological competences and a pragmatic approach to investment. In addition, growing regulatory pressure in the European Union – in particular the AI Act and regulations such as DORA in the financial sector – forces organisations to build governance in parallel with implementation. As the report shows, creating governance structures makes it possible to clearly define responsibility, control and oversight, and therefore supports effective AI scaling,” says Leszek Ortyński.
“The biggest challenge, however, remains data fragmentation and older, often dispersed IT systems, which make it difficult to scale AI across the organisation. 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 competences are foundations, not additions. These areas will determine lasting competitive advantage,” he adds.
Employee Skills Remain the Weakest Link
One of the most concerning conclusions from the report is the low level of employee readiness to operate in an AI-based environment. Only 22% of respondents express strong confidence that their employees are able to meet the requirements 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 effects than organisations with skills gaps.
Different Sectors, Different Pace of AI Maturity
The most advanced sector in terms of AI use remains TMT – technology, media and telecommunications. Organisations in this area are increasingly building AI-native architectures and integrating multi-agent systems with key business processes.
The financial sector is developing AI more cautiously because of strict regulatory and compliance requirements, focusing on governance models that support implementation. Retail and consumer goods companies are concentrating mainly on using AI in sales, marketing and customer experience management. The healthcare sector, meanwhile, is dealing primarily 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 regular study on the maturity of artificial intelligence use in global business. The quarterly survey analyses how organisations move from individual AI implementations to coordinated AI management at enterprise level.
The study was conducted online between 19 February and 17 March 2026. The sample included 2,110 executives and senior managers from organisations 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.
