14%
35%
34%
17%
Download the report and see how CEE organisations can move from AI ambition to AI impact
Key findings
0%
of organisations in CEE already have an AI strategy or are actively building one.
0%
report they fully realised the value expected from their AI initiatives.
0%
have a fully coherent, enterprise-wide AI governance model in place.
The defining challenge: using AI vs scaling AI
Having an AI strategy has become mainstream, and only 14% don’t plan to have it within the next 12 months. But companies now have to put these strategies into practice.
"The harder work starts now. Putting AI on the agenda isn’t the same as letting it shape how the business runs."
Right now, half of organisations report partial benefits from AI, and over a third report most of expected outcomes, but full realisation is rare.Not many pilots become use cases that are scaled across functions and business units. The result is a growing execution gap between AI ambition and AI impact.
Does your company have a defined strategy (for the next 3–5 years) for the use of AI and advanced data analytics?
To what extent has your organisation realised the expected benefits from AI and advanced analytics initiatives?
11%
50%
35%
5%
"We are moving from individual AI use cases toward reusable capabilities and human-and-agent delivery models that can be applied across services and markets. The same principle applies to our clients: prioritise the workflows that matter, build production-grade foundations once, and scale proven capabilities rather than restart with every pilot.”
Where the value is and what holds it back
AI’s benefits concentrate in IT and operations, where data is structured and processes repeat. Companies mainly report gains in data quality and lower operating costs. Fewer have extended the value into customer experience, shortening time to market for new products, or new revenue streams.
"The first wave of AI benefits is emerging most visibly in IT and operations. Those functions have structured data and processes built for measurement. The early wins are better data quality and lower operating costs. But these efficiency gains have a ceiling. The bigger prize sits in new revenue, new products, sharper competitive positioning. Most CEE organisations haven’t crossed that line yet."
Cost is one of the most consistent constraints across the region. Budget constraints and high implementation expenses show up as top concerns across CEE.
Cybersecurity and data privacy are also high in the ranking. Together with technical barriers, there are also organisational ones. Skills gaps and limited employee trust in AI also influence the implementation of AI and opportunities to get more value from it.
"AI can scale only when people trust it. Trust grows when organisations establish clear governance, build the right skills, prepare the organisation for change, and demonstrate value."
Only a small proportion of organisations have established coherent, enterprise-wide AI governance frameworks. Many continue to work without formal structures or dedicated risk management processes. Even where governance exists, it's often partial and not consistently embedded across the business.
“Knowing which AI use cases are high-risk, which need human oversight, and which can run autonomously gives teams the clarity to deploy AI faster. Regulation isn’t slowing AI adoption, the absence of internal rules is.”
Four CEE markets, four speeds
There are significant AI maturity gaps across companies in different CEE countries.
Slovak companies lead on strategy readiness, mid-to-high investment, benefit realisation, and governance maturity.
Organisations in the Czech Republic follow closely, with the highest share of large investments (€750,000+) and the most fully coherent enterprise-wide governance models (6%).
In Poland, respondents show a split picture: strong implementation and clear gains in cost, security, and customer insights, but the highest share of companies with no strategy.
Romanian companies are still at an early stage.
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