Policy Brief
Artificial intelligence is becoming increasingly accessible to enterprises, but access to technology does not automatically translate into effective implementation or measurable business value. Evidence generated by the AI-ImpactSK project shows that Slovak enterprises differ substantially in their stage of AI adoption, organisational readiness, skills, data conditions, governance practices and ability to assess the value created by AI. These differences mean that a uniform policy approach is unlikely to address the actual constraints faced by enterprises.
The central policy objective should therefore not be to maximise the number of enterprises reporting that they use AI. Public and enterprise-support policies should instead strengthen the capacity of firms to determine whether AI addresses a genuine business or operational problem, prepare the organisational and technical conditions required for implementation, test proposed applications under controlled conditions, evaluate their benefits and risks, and sustain or scale them only where the available evidence supports continuation. Conventional automation, process redesign, postponement and non-adoption remain valid outcomes where AI does not provide a credible business case or where readiness and risk conditions do not justify implementation.
The AI-ImpactSK evidence supports a coordinated portfolio of policy measures rather than isolated grants, generic training or technology-promotion activities. Enterprises frequently require combinations of finance, specialised advice, skills development, data preparation, testing opportunities, governance support and credible implementation evidence. The appropriate combination should depend on the enterprise’s adoption stage, readiness, identified constraint and use-case risk. Support should begin with the enterprise problem and the nearest realistic next step, not with the availability of a particular funding instrument or technology.
Key policy message: Support better AI decisions, not AI adoption for its own sake.
Effective public support should help enterprises move from a clearly defined business problem to an evidence-based decision: prepare, pilot, scale, revise, postpone or stop. The lightest intervention capable of resolving the identified constraint should be preferred, and continued public support should depend on demonstrated readiness, measurable results and manageable risk.
This Policy Brief summarises the evidence and recommendations presented in Deliverable D6.1 – Policy Recommendations Report. Detailed evidence, methodological limitations and implementation specifications are provided in the main report and Annexes A–C.
