Technical

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.

What it triggers

The European Union Coordinated Plan on Artificial Intelligence — 2021 review sets out recommendations for Member States to invest in and develop enabling conditions such as cross-border data spaces, computing capacity, and workforce skills to support AI research, deployment, and market uptake.source
The Coordinated Plan on Artificial Intelligence (EU, 2021 review) as applied in Bulgaria calls for actions to build foundational elements including scaled computing capacities and data governance to enable AI innovation across sectors.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.

Coordinated Plan on Artificial Intelligence (EU, 2021 review) — (applies to Bulgaria as EU Member State)Definition 1 of 2

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.

Coordinated Plan on Artificial Intelligence — 2021 reviewDefinition 2 of 2

Not to be confused with

ecosystem enablers

Ecosystem enablers refer to broader capabilities supporting AI adoption and scale, while enabling conditions specifically denote the foundational elements like skills, computing, and data required for AI development and deployment.

Foundational infrastructure

Foundational infrastructure focuses on core physical and virtual resources for data and AI, whereas enabling conditions encompass a wider set of prerequisites including human capital and governance frameworks.

Questions and answers

What are the key enabling conditions for AI under the EU Coordinated Plan?

The key enabling conditions include cross-border data spaces, computing and processing capacity, microelectronics, standards, data governance frameworks, and workforce skills. These are essential to support AI research, deployment, and market uptake across Member States.

How does the 2021 review of the Coordinated Plan address enabling conditions in Bulgaria?

It identifies foundational elements such as skills and talent pipelines, scaled computing capacities, common data spaces, and open research practices as necessary to develop and deploy AI in Bulgaria as an EU Member State.

What is the purpose of focusing on enabling conditions in AI policy?

Focusing on enabling conditions aims to build lab-to-market pathways, promote interoperable and scalable projects, and accelerate investment and policy alignment for trustworthy AI across the EU and its Member States.