With artificial intelligence gaining rapid acceptance across all areas of business, businesses globally are preparing themselves for an ever-shifting, and much more intricate regulatory environment in 2025.
Although the holy grail of a single AI law globally is yet to be found, a quilt of regional and national laws is emerging, putting the onus on companies to be more vigilant and engage in focused planning to comply with the law.
The EU AI Act contributes to the world’s first comprehensive framework, taking a risk based approach. Organisations deploying “high risk” AI systems – such as in medical devices, recruitment and credit scoring – will need to meet strict obligations for risk management, data governance and transparency and human oversight, including a requirement for both mandatory registration and CE marking.
Adherence to these rules will be important to prevent the imposition of heavy fines and the excluding of them from the EU market.
The United States model of changing regulation is more decentralized, on the other hand. While there’s still no federal law on the books for A.I., a few states have taken the lead.
For example, California has already passed laws that affect AI-processed personal information and AI in healthcare, including a requirement for transparent disclosures for AI-generated patient communications, and the extension of data privacy rights to AI-processed data.
Other states, such as Texas and Maryland, are actively working on their own AI governance frameworks. This patchwork manner of regulation requires multi-state businesses to comply with widely varying state standards.
In addition to individual laws, a key theme that is emerging internationally is a focus on transparency, accountability and ethical AI. Regulators are more and more requiring transparent labeling for AI-generated work, strong protections against algorithmic bias, and ways for users to know the reasoning behind AI-made decisions.
For instance, China has introduced new mandatory labeling rules for AI sustantiated contents, which become effective in September 2025, and is continuing to refine its overall AI governance framework.
For businesses, evolving in this world means focusing on a few key things. First, organizations must perform robust audits to locate and categorize every AI system in use according to how risky it is. Secondly, creating strong AI governance systems that incorporate data privacy practices, ethical determining processes, and human supervision from design to deployment is critical.
Finally, making investments in AI literacy and readiness across the business will be critical to engage employees with and advance a culture of responsible AI adoption where employees will know what is required and expected of them in the evolving policies. The year ahead is likely to be a challenge for businesses as they look to make the most of what AI has to offer but must respond to a growing sea of regulation.
