The EU AI Act’s definition of an AI system is intentionally broad, covering any machine-based system that operates autonomously, adapts after deployment, and generates outputs that influence environments.

Understanding this definition is crucial for compliance, as it determines whether your technology falls under the world’s first comprehensive AI regulation.

The European Union’s Artificial Intelligence Act, which entered into force on August 1, 2024, represents a landmark moment in technology regulation. As the world’s first comprehensive legal framework on AI, the Act aims to foster trustworthy AI in Europe while addressing the risks AI systems may pose to safety and fundamental rights.

But before organisations can navigate the Act’s complex requirements, they must first understand a fundamental question: what exactly constitutes an AI system under this new law?

The EU AI Act’s Core Definition

At the heart of the AI Act lies Article 3, which provides the regulatory foundation for determining what falls under its scope.

According to Article 3(1) of the AI Act, an ‘AI system’ means “a machine-based system that is designed to operate with varying levels of autonomy and that may exhibit adaptiveness after deployment, and that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments”.

This definition deliberately casts a wide net. The definition is very broad, as most of the criteria also apply to traditional software programs. The decisive factor in determining whether a system is considered AI is therefore usually whether it is designed for autonomous operation.

Breaking Down the Seven Key Components of AI System

To truly understand what counts as an AI system, let’s examine the seven essential elements embedded in the Act’s definition:

1. Machine-based system – The technology must be implemented using computers, software, or digital infrastructure rather than purely biological or manual processes.
2. Designed to operate with varying levels of autonomy – This is often the distinguishing factor between AI and traditional software. The system must be capable of functioning independently to some degree, making decisions without constant human intervention.
3. May exhibit adaptiveness after deployment – The system can modify its behaviour or performance based on new data or experiences encountered after it’s been put into use.
4. For explicit or implicit objectives – The system pursues defined goals, whether clearly stated by programmers or emergent from its design and training.
5. Infers from input – Rather than simply following pre-programmed rules, the system draws conclusions or makes determinations based on the data it receives.
6. Generates outputs – The system produces results that weren’t directly programmed but were derived through its inference processes.
7. Can influence physical or virtual environments – The outputs have the potential to affect the real world or digital spaces where they operate.

What Does AI System Definition Mean in Practice?

The broad scope of this definition has significant implications for businesses across Europe and beyond. Consider some common examples:

Clearly covered systems include:

• Machine learning algorithms that recommend products to customers
• Computer vision systems that identify objects in images
• Natural language processing tools that generate or analyse text
• Predictive analytics systems that forecast business outcomes
• Autonomous vehicles and robotics systems

Less obvious but still covered systems might include:

• Advanced spam filters that adapt their detection methods
• Dynamic pricing systems that adjust based on market conditions
• Sophisticated chatbots that generate contextual responses
• Automated content moderation systems on social platforms

Traditional software typically excluded from AI Act:

• Basic calculators or spreadsheet applications
• Simple rule-based systems without learning capabilities
• Standard database management systems
• Static websites or basic mobile applications

The Numbers Tell the Story

The rapid adoption of AI technologies makes understanding these definitions increasingly critical. The adoption of AI technologies has skyrocketed in recent years. In 2019, 58% of organizations used AI for at least one business function; by 2024, that number jumped to 72%. The use of generative AI nearly doubled from 2023 to 2024, going from just 33% to 65%.

In the European Union specifically, 13.5% of enterprises with 10 or more employees used artificial intelligence technologies to conduct their business in 2024, indicating a 5.5 percentage point growth from 8.0% in 2023. Leading countries include Denmark (27.6%), Sweden (25.1%) and Belgium (24.7%).

Why Precision Matters: The Risk-Based Approach to AI Systems

Understanding what qualifies as an AI system isn’t merely an academic exercise. The AI Act defines 4 levels of risk for AI systems, and each category carries different obligations:

• Prohibited systems face complete bans
• High-risk systems must undergo rigorous conformity assessments and ongoing monitoring
• Limited-risk systems require transparency disclosures
• Minimal-risk systems face few regulatory requirements

The classification of your technology as an AI system triggers this risk assessment process, potentially subjecting your organization to significant compliance obligations.

Global Implications of AI System Regulation Beyond Europe

While the EU AI Act directly applies within European borders, its influence extends far beyond. The EU AI Act also applies to providers and deployers outside of the EU if their AI, or the outputs of the AI, are used in the EU. This extraterritorial reach means that any organization whose AI systems produce outputs used within the European Union must consider compliance, regardless of where they’re headquartered.

Like the EU’s General Data Protection Regulation (GDPR) in 2018, the EU AI Act could become a global standard, determining to what extent AI has regulatory oversight worldwide.

Practical Next Steps for Organisations

For organisations evaluating their exposure to the AI Act, consider these immediate actions:

• Conduct an AI inventory – Catalog all systems that might meet the Act’s definition of AI
• Assess autonomy levels – Determine which systems operate with meaningful independence
• Evaluate adaptiveness – Identify systems that modify their behavior after deployment
• Map influence patterns – Understand how your systems’ outputs affect physical or virtual environments
• Engage legal and compliance teams – Ensure proper interpretation of definitions within your specific context

Looking Ahead

Currently, most AI systems pose minimal risk and face no obligation under the AI Act, but companies can voluntarily adopt additional codes of conduct. However, as AI capabilities advance and become more pervasive, more systems may fall under higher-risk categories.

The European Commission has indicated that 6 February 2025 marked the release of Commission Guidelines on the definition of an artificial intelligence system established by Regulation (EU) 2024/1689 (AI Act), providing additional clarity for organisations working to understand their obligations.

Understanding what counts as an AI system under the EU AI Act is the first step in navigating this new regulatory landscape. While the definition is intentionally broad to capture rapidly evolving technologies, organisations that take a systematic approach to evaluation and compliance will be best positioned to leverage AI’s benefits while meeting their regulatory obligations.

As the AI ecosystem continues to evolve, staying informed about these foundational definitions will remain crucial for organisations across all sectors.

The EU AI Act doesn’t just regulate technology—it shapes how we think about the role of artificial intelligence in society, making these definitions a cornerstone of responsible AI development and deployment.

As AI adoption accelerates—with 72% of organizations now using AI—ensuring compliance isn’t just about avoiding penalties. It’s about building trust with customers and stakeholders – and here’s how to take the first step.

AI Act Glossary: Key Terms

1. AI System

A machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments.

2. High-Risk AI System

An AI system that poses significant risks to health, safety, or fundamental rights. These systems are subject to strict requirements and are listed in Annex III of the regulation.

3. Prohibited AI Practices

AI systems that are banned due to their unacceptable risk, including those that:

• Deploy subliminal techniques beyond a person’s consciousness to materially distort behavior.
• Exploit vulnerabilities of specific groups due to age, disability, or social or economic situation.
• Engage in social scoring by public authorities.
• Use real-time remote biometric identification in publicly accessible spaces for law enforcement, with specific exceptions (Source: eur-lex.europa.eu+1eur-lex.europa.eu+1)

4. General-Purpose AI (GPAI)

AI systems intended to perform generally applicable functions, such as image or speech recognition, which can be integrated into a wide range of applications.

5. Provider

A natural or legal person, public authority, agency, or other body that develops an AI system or has an AI system developed and places it on the market or puts it into service under its own name or trademark.

6. User

Any natural or legal person, public authority, agency, or other body using an AI system under its authority, except where the AI system is used in the course of a personal non-professional activity.

7. Placing on the Market

The first making available of an AI system on the Union market.

8. Putting into Service

The supply of an AI system for first use directly to the user or for own use in the Union for its intended purpose.

9. Conformity Assessment

The process of verifying whether the requirements set out in the regulation relating to an AI system have been fulfilled.

10. CE Marking

A marking by which the provider indicates that the AI system is in conformity with the applicable requirements set out in the regulation and other Union harmonisation legislation.eur-lex.europa.eu+1eur-lex.europa.eu+1

11. Notified Body

An independent and impartial body designated by a Member State to assess the conformity of high-risk AI systems before they are placed on the market or put into service.eur-lex.europa.eu

12. Post-Market Monitoring

All activities carried out by providers to proactively collect and review experience gained from the use of AI systems they place on the market or put into service, in order to identify any need to immediately apply any necessary corrective or preventive actions.

13. Transparency Obligations

Requirements ensuring that AI systems are designed and developed in a way that their operation is sufficiently transparent to enable users to interpret the system’s output and use it appropriately.

14. Fundamental Rights Impact Assessment

An assessment conducted to evaluate the potential impact of high-risk AI systems on fundamental rights, including privacy, non-discrimination, and freedom of expression.

15. AI Office

A European-level body established to support the implementation and enforcement of the AI Act, including the coordination of national supervisory authorities and the development of guidance and standards.