5 AI Lawmaking Mistakes Policymakers Are Making Now

The rush to regulate artificial intelligence is running into a predictable problem: lawmakers, despite quality intentions, are creating legislation that misses the mark. A flurry of activity at both the federal and state levels, spurred by concerns over potential misuse and unintended consequences, is yielding laws that are often overly broad, poorly defined, and ultimately counterproductive. This isn’t a matter of malicious intent, but rather a series of recurring blunders in how these complex technologies are approached from a legal perspective. The Trump administration’s recent shift towards prioritizing AI competitiveness, including a December 2025 executive order aimed at reducing regulatory hurdles, only heightens the stakes as Congress and state legislatures continue to explore their own controls. As Forbes reported just days ago, the trend of poorly conceived AI legislation is continuing.

The Illusion of Control Through Broad Definitions

One of the most common pitfalls is attempting to define AI too broadly. Many proposed laws aim to regulate “artificial intelligence” without establishing a clear, technical definition. This leads to ambiguity, potentially encompassing software and algorithms that were never intended to be subject to the new rules. The result? Increased compliance costs for a wider range of businesses, and a chilling effect on innovation. California’s October 2025 bill requiring disclosures for AI chatbots is an example of this trend, as highlighted by Skadden, Arps, Slate, Meagher & Flom LLP. The lack of specificity creates a legal minefield, forcing companies to err on the side of caution and potentially stifle beneficial applications of AI.

Focusing on Outputs, Not Processes

Another frequent mistake is regulating the outcomes of AI systems rather than the processes used to develop and deploy them. For example, a law might prohibit discriminatory outcomes from an AI-powered loan application system. While the goal – preventing discrimination – is laudable, focusing solely on the output ignores the crucial steps taken to mitigate bias during the development phase. A more effective approach would be to require developers to demonstrate that they have implemented robust bias detection and mitigation techniques, rather than simply penalizing them for unintended discriminatory results. This shifts the emphasis from reactive enforcement to proactive responsibility.

Ignoring the Rapid Pace of Technological Change

AI is evolving at an unprecedented rate. Legislation drafted today may be obsolete tomorrow. Lawmakers often struggle to keep pace with these advancements, resulting in laws that are quickly outdated and ineffective. The “Winning the Race: America’s AI Action Plan” released by the White House in July 2025, and detailed in a Skadden client alert, acknowledged this challenge, advocating for the reconsideration of existing regulations. A more flexible, adaptive regulatory framework is needed – one that can be updated quickly to address emerging challenges and opportunities. This could involve establishing regulatory sandboxes or adopting a principles-based approach that focuses on overarching goals rather than specific technical requirements.

Creating Unworkable Compliance Burdens

Many proposed AI laws impose compliance requirements that are simply unworkable for smaller businesses and startups. Demanding extensive documentation, independent audits, or the implementation of complex technical safeguards can create significant barriers to entry, effectively stifling competition and innovation. This disproportionately impacts smaller players who lack the resources to navigate these regulatory hurdles. A tiered regulatory approach, with different requirements based on the size and risk profile of the AI system, could help to address this issue.

Overlooking the Importance of International Harmonization

AI is a global technology, and regulations developed in isolation are unlikely to be effective. A patchwork of conflicting laws across different jurisdictions creates uncertainty for businesses operating internationally and hinders the development of a global AI ecosystem. Efforts to harmonize AI regulations across countries are essential to ensure a level playing field and promote responsible innovation. The U.S. Needs to actively engage in international discussions and collaborate with other nations to develop common standards and principles for AI governance. The National Conference of State Legislatures notes the ongoing robust discussions regarding AI concerns, highlighting the need for coordinated efforts.

What’s on the Horizon for AI Regulation?

The current landscape is one of ongoing debate and experimentation. Congress and state legislatures are continuing to grapple with the challenges of regulating AI, and we can expect to see a continued stream of proposed legislation in the coming months. The Trump administration’s focus on AI competitiveness adds another layer of complexity, potentially leading to clashes with lawmakers who prioritize safety and ethical considerations. AI developers and companies employing the technology will need to closely monitor these developments and proactively engage with policymakers to shape the regulatory landscape. The key will be finding a balance between fostering innovation and mitigating the potential risks of this transformative technology. Expect increased scrutiny of AI chatbots, particularly regarding their impact on minors, as investigations and proposals continue to proliferate. The next six to twelve months will be critical in determining the future of AI regulation in the United States.