Artificial Intelligence Compliance and Risk Management Strategies for 2026
As More States and Countries Adopt AI Laws, Compliance and Risk Management Are Becoming Increasingly Complex
Artificial Intelligence Team Lead
Contact NickArtificial intelligence (AI) remains a central focus in the business and legal worlds heading into 2026. As more companies find new and innovative ways to develop and leverage AI-based technologies, competition continues to increase—and AI systems are becoming more ingrained in many industries. At the same time, while legislatures and regulators are struggling to keep pace, they are starting to gain ground, and we have seen several significant legal developments and regulatory changes over the past year.
With that said, there is no question that the law of AI is still lagging—and this is somewhat of a double-edged sword for companies developing and using innovative AI platforms. On the one hand, the lack of clear legal or regulatory guidance in many respects means that companies (and their counsel) have to use their best judgment to apply laws and regulations that predate AI’s advent by decades. Conversely, as new laws and regulations take effect, companies (and their counsel) must identify patterns, keep pace, and determine whether legal developments require a substantial shift in their (or clients’) operations.
So, where do things stand currently? What can (and should) companies do to regulatory change management and risk effectively in 2026? Here are some key insights:
Artificial Intelligence Compliance in 2026
Regarding compliance, companies developing and licensing AI technology will need two main focus points in 2026: (i) AI-specific laws and regulations in the U.S. and abroad and (ii) applicable laws and regulations non-specific to AI.
AI-Specific Laws and Regulations
Effectively managing artificial intelligence compliance will become increasingly complicated in the years ahead. With machine learning continuing to grab headlines (and many lawmakers still struggling to grasp AI’s fundamental nature and implications), state legislatures have taken a piecemeal approach to putting guardrails in place. The current state-level AI laws vary widely in their focus and impact, with many raising more questions than they answer.
The National Conference of State Legislatures (NCSL) has published a list of AI laws passed in 2023 and a list of AI laws passed and proposed in 2024. Collectively, these serve as a good starting point for understanding the state of AI law in the U.S. today.
At the federal level, we do not yet have any AI-specific legislation (though the White House has issued a Blueprint for an AI Bill of Rights and, more recently, an Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence). How (and if) the federal government’s approach to addressing AI will change with the new administration remains to be seen. While a Republican Senator proposed broad-based AI legislation last November (the Federal Artificial Intelligence Risk Management Act of 2023), the bill failed to make it out of committee. Several other legislative efforts championed by both parties addressing specific AI-related concerns have also failed to gain traction in Congress.
While we have seen some federal agencies attempt to take the lead in providing industry guidance, we only have non-binding guidance at this stage. For example, in November 2024, the U.S. Department of Homeland Security (DHS) released a document titled Roles and Responsibilities Framework for Artificial Intelligence in Critical Infrastructure, in which DHS states:
“This Framework seeks to complement and advance the AI safety and security best practices established by the White House Voluntary Commitments and Blueprint for an AI Bill of Rights, the OMB M-24-10 Memorandum on AI, the work of the AI Safety Institute, and the DHS Safety and Security Guidelines for Critical Infrastructure Owners and Operators, among others.”
The White House Voluntary Commitments referenced in DHS’s Framework are “a list of commitments that companies are making to promote the safe, secure, and transparent development and use of generative AI (foundation) model technology.” They were established by a group of leading companies in the AI industry in 2023. While laudable in their intent, these voluntary commitments have not played a significant or consistent role in these (or other) companies’ AI-related decision-making over the past year.
Given that the guidance from DHS and others is non-binding, companies should consider it for what it is: a look at how the federal government might regulate AI in the future. While instructive, this guidance is also subject to change. If we eventually see AI-specific federal laws or regulations, they may or may not align with the guidance, which—by that point—is likely to be years old and perhaps far outdated by new developments in AI technology.
While the U.S. government has been slow to address the legal and societal implications of AI, other countries around the world are moving more swiftly. From Brazil to China, several countries have established or proposed guidelines that have the potential to significantly impact companies’ AI-related business in these jurisdictions. The European Commission, many European countries, and the United Kingdom also focus on AI governance with the EU AI Act. Since simply making technology available in a country can subject companies to that country’s laws and regulations in some cases, this will have to be a core compliance focus for many companies that develop and license AI technologies going forward.
As a final note on this subject, it is important to remember that the legal framework surrounding AI systems could change at any time. Bills are routinely proposed in Congress and statute legislatures across the country, and all it takes is one momentous event to get the ball rolling. With this in mind, companies (and their counsel) will need to continue to monitor closely for updates and regulatory adherence in 2026.
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Compliance Considerations that Are Non-Specific to AI System
Along with considering laws, regulations, and non-binding guidance that are specific to artificial intelligence, companies that develop and license AI technologies must also address laws and regulations that are non-specific to AI. Numerous laws and regulations fall into this category, and companies involved in all segments of the AI industry must ensure that they are taking adequate steps to meet all pertinent statutory and regulatory requirements.
Some important areas of state and federal (and international) compliance processes that are pertinent to companies in the AI industry include:
- Antitrust
- Data importing and exporting
- Data Security
- Intellectual property
- National security
- Privacy
- Procurement
These are just examples. From industry-specific laws and regulations (e.g., those pertaining to transportation and healthcare) to employment and securities laws, a wide range of other sources of binding authority may apply as well. Thus, here, too, a comprehensive and proactive approach is essential for effective compliance management.
Artificial Intelligence Risk Management in 2026
Regarding AI risk management, statutory and regulatory compliance is a core component. But it is also just one component of many. To effectively manage AI-related compliance risk in 2026 (and beyond), companies will need to take steps including:
1. Conducting a Comprehensive Compliance Needs Assessment
All companies that develop and use AI platforms should conduct a comprehensive compliance needs assessment. This assessment should identify applicable laws, regulations, and guidelines in all pertinent jurisdictions.
Along with identifying compliance risks, companies must address various potential non-compliance-related risks. For example, intellectual property infringement remains a critical concern in the generative AI sphere without clear guidance. From careful contract negotiation to careful use of AI tools in high-risk areas (such as healthcare and employment), companies may also need to address various other risks.
3. Developing and Implementing Risk-Focused Policies and Practices
After identifying all pertinent AI-related risks, companies must develop and implement risk-focused policies and practices to guide their development and use of artificial intelligence. These policies and practices will vary widely between companies with disparate needs. Ultimately, however, all companies’ AI-related policies and practices should be designed to effectively mitigate all forms of risk.
4. Monitoring for Threats and Addressing Them Promptly
Even with effective risk-focused policies and practices, threats can (and will) arise. With this in mind, monitoring is also a key aspect of risk management in the AI sphere. Companies should adopt protocols designed to identify threats as a matter of course, and when threats arise, companies should work with their legal counsel to respond appropriately.
Along with internal monitoring, external monitoring will be critical as well. Companies must rely on their legal counsel to continuously monitor for new AI-related risks. As the law continues to develop, it will be essential for companies to ensure that they update their compliance and risk management programs as necessary.
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