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AI can help people and institutions work more productively, advance scientific research and improve public services—but those outcomes depend on the task, the data and how a system is used. The same technology can also produce harmful decisions, spread errors or be exploited for fraud and disinformation. Regulation can set protections and responsibilities around these risks; it cannot guarantee that harm disappears or that innovation proceeds unchanged.
What benefits can AI bring?
The potential gains are practical as well as scientific. The OECD’s 2024 analysis identifies productivity gains and faster scientific progress among AI’s possible benefits. In government, the OECD’s 2025 report describes ways AI may help automate or tailor services, support decision-making, detect fraud and enrich civil servants’ work and learning.
These are possibilities, not automatic results. A system that performs well on one task may be unsuitable for another, and its effect depends on the quality of its data, the people and processes around it, and whether it is monitored. Introducing AI does not by itself establish that a service is faster, fairer or more effective. OECD, Assessing potential future artificial intelligence risks, benefits and policy imperatives (2024); OECD, Governing with Artificial Intelligence (2025).
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What can go wrong?
Some risks arise from ordinary use. Skewed or unrepresentative data can contribute to harmful decisions. If a system’s operation is difficult to understand, it can be harder to explain or challenge an outcome. People may also rely too heavily on AI output, allowing mistakes to pass through a service or widening digital divides when some people cannot use or access that service effectively. These concerns are especially relevant when AI informs decisions affecting people.
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Other concerns reach beyond an individual system or decision. The OECD’s 2024 analysis identifies more sophisticated cyberattacks, manipulation and disinformation, fraud, democratic harms, incidents in critical systems, concentration of power, and exacerbated inequality and poverty among priority risks. They are risks the report identifies, not a prediction that each will occur in every deployment. OECD, Governing with Artificial Intelligence (2025); OECD, Assessing potential future artificial intelligence risks, benefits and policy imperatives (2024).
Why regulate the use of AI?
Regulation can establish baseline protections and clarify who is responsible for managing risks. It can require safeguards related to safety, fundamental rights, transparency and risk management, and give people and organizations a more predictable framework for using AI. The European Commission says the EU AI Act is intended to address risks to health, safety and fundamental rights while taking account of AI’s potential benefits and supporting innovation. In the Commission’s words, “The AI Act aims to address the risks to health, safety and fundamental rights of the individuals that AI systems may cause.” European Commission, Navigating the AI Act.
The EU AI Act is a regional legal framework, not a law that applies everywhere. The Commission describes it as risk-based: the framework differentiates according to risk rather than treating every use of AI identically. Its rules have staged application dates and transition arrangements, so whether a particular provision applies depends on the rule and timing. The Commission’s official overview should be checked for the current timeline and any updated transition dates before relying on a specific deadline. European Commission, AI Act.
What regulation can—and cannot—do
What it can do
- Set minimum expectations: establish protections and responsibilities for addressing defined risks.
- Make accountability more concrete: require attention to matters such as transparency, documentation, human oversight and risk management, depending on the applicable rules.
- Support trust: give organizations and the public clearer expectations about how AI should be assessed and governed.
- Shape incentives: make safety and rights part of deployment decisions instead of leaving them entirely to voluntary practice.
What it cannot do
- Eliminate every failure: rules cannot make data complete, ensure every system works as intended or prevent every malicious use.
- Replace judgment and oversight: an organization still needs people able to assess outputs, respond to errors and reconsider whether AI is appropriate for a task.
- Guarantee a particular social outcome: regulation does not prove that a system will improve productivity, fairness or service quality.
- Freeze the trade-offs: added safeguards can affect costs, processes and the pace or design of innovation. Policy must manage those trade-offs rather than assume regulation has no effect on them.
What responsible AI governance looks like in practice
Legislation is only one part of governance. The OECD’s 2025 guidance groups practical conditions around enabling capacity, safeguards and engagement. For an organization considering AI, that translates into a continuing process rather than a one-time approval:
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- Establish capability: assign governance responsibilities and consider whether the organization has suitable data, infrastructure, skills and investment. Procurement choices and partnerships also affect how a system can be managed.
- Assess the use before deployment: define the task and affected people, consider potential impacts, and decide whether an AI system is suitable. Impact assessments and experimentation can help surface problems before wider use.
- Put safeguards in place: make the system’s role and limitations transparent to relevant users, manage identified risks, and establish meaningful oversight and routes to address errors.
- Check performance over time: audit or otherwise review whether the system continues to perform as intended and whether risks or impacts have changed.
- Engage affected people and staff: involve citizens, civil servants and other relevant stakeholders in shaping and evaluating uses, rather than treating deployment as a purely technical decision.
These are OECD policy recommendations, not a substitute for checking the law that applies to a particular organization or use. The OECD’s framework also discusses international partnerships as part of the conditions for trustworthy AI. OECD, “Enablers, guardrails and engagement for unlocking trustworthy AI” (2025).
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to judge an AI policy or deployment
For a concrete decision, ask questions that connect the promised benefit to the possible harm and the controls available:
- What task is the AI meant to improve? Name the outcome being sought instead of treating adoption itself as a benefit.
- How serious could an error be? A mistake in a low-stakes suggestion differs from one that could affect safety, rights or access to a public service.
- Who is responsible at each stage? Identify the organizations developing, supplying and using the system, and check which obligations apply to each under the relevant jurisdiction.
- Can people understand and challenge consequential outcomes? Look for suitable transparency, documentation, oversight and ways to correct or appeal errors.
- How will the system be monitored? Specify risk management, impact assessment and audit arrangements rather than relying on claims about intended performance.
- Where and when does the rule apply? Check jurisdiction, the relevant legal provision and its effective date; a framework’s headline adoption date may not settle whether a particular requirement is in force.
For the EU, the Commission’s AI Act pages are the appropriate place to verify current scope and staged application. Elsewhere, the EU example should not be treated as a statement of local law.
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