Enabling conditions
Foundational elements (skills, computing, data) required for AI.
How the laws define this
Both descriptions agree that enabling conditions are essential prerequisites—specifically including computing capacity, data governance measures, and workforce skills—required to support artificial intelligence research, deployment, and market uptake. Their key point of divergence lies in their operational scope and technical focus. The Coordinated Plan on Artificial Intelligence (EU, 2021 review), as it applies to Bulgaria as an EU Member State, frames these conditions around foundational elements such as human capital, open research practices, infrastructure, and general data governance to foster innovation and uptake across sectors. Conversely, the text from the Coordinated Plan on Artificial Intelligence — 2021 review highlights cross-border integration and industrial tools, explicitly specifying microelectronics, formal standards, cross-border data spaces, and lab-to-market pathways necessary to build interoperable, scalable projects across Member States. Consequently, while the entry applying to Bulgaria emphasizes broad cross-sector support, the other definition concentrates on technical standards, specialized hardware, and cross-border project execution.
Synthesised from the 2 statutory definitions below. Each one is quoted in full, with its source.
Definitions (2)
A set of foundational elements the Plan identifies as necessary to develop and deploy AI, including skills and talent pipelines, scaled computing capacities, common data spaces, and open research practices. Enabling conditions cover infrastructure, human capital, and data governance measures that support innovation and uptake across sectors.
Cross-cutting prerequisites—including cross-border data spaces, computing and processing capacity, microelectronics, standards, data governance frameworks and workforce skills—required to support AI research, deployment and market uptake. The Plan emphasises building these conditions to enable lab-to-market pathways and interoperable, scalable projects across Member States.
Related Terms
ecosystem enablers
Foundational capabilities that support AI adoption and scale....
Capability-building
Developing R&D, algorithmic expertise, and research capacity....
Talent
Human resources and skills base for AI development....
Infrastructure
Compute and storage resources like HPC and cloud services....
Foundational infrastructure
Core physical and virtual resources for data and AI....