Linda Malek, JD

How Healthcare Organizations Can Balance Federal and State AI Regulations

The White House AI Action Plan is designed to position the United States as a global leader in artificial intelligence by accelerating development, adoption, and innovation across industries, including healthcare. According to Linda Malek, JD, partner at Crowell & Moring, the plan’s intent is twofold: to maintain US competitiveness against other nations advancing rapidly in AI, and to create an environment that fosters safe, efficient, and scalable AI implementation.

For hospitals, health systems, and health-tech companies, the plan could significantly shape the pace and scope of AI adoption through several key mechanisms. One of the most notable is the introduction of regulatory sandboxes—controlled environments where new AI tools can be tested and validated with reduced bureaucratic friction. These sandboxes are intended to streamline approval processes for AI-driven medical devices, clinical software, and digital tools, effectively “cutting red tape” and allowing innovations to reach clinical settings faster.

Another major component involves public investment in infrastructure. The plan calls on agencies such as the National Institute of Standards and Technology (NIST) and the U.S. Food and Drug Administration (FDA) to expand national data and computing infrastructure. This includes developing large-scale data centers and improving access to high-quality, diverse datasets—resources essential for training and validating AI models.

By emphasizing both regulatory flexibility and technical capacity-building, the Action Plan aims to lower barriers to entry for healthcare innovators while ensuring oversight and accountability remain in place. Ultimately, Malek suggests, this initiative could enable faster clinical integration of AI tools, strengthen domestic innovation pipelines, and help U.S. healthcare systems leverage AI more effectively for patient care, operational efficiency, and research advancement.

Malek also dives into the role sandboxes could play in helping healthcare organizations test and implement AI safely, while protecting patients; how providers and health systems prepare for potentially conflicting requirements when it comes to AI-related regulations; the steps healthcare organizations can take now to align with the Action Plan and position themselves for regulatory changes in the next few years; and much more.

With both federal and state governments pursuing AI-related regulations, how should providers and health systems prepare for potentially conflicting requirements?

 That is a challenge, certainly because the federal signaling that we're getting is to kind of open things up and create less obstacles, fewer regulations, more innovation, more freedom to innovate, more building of large databases and use of the data in those databases. On the state side, you have Colorado and Utah that have specific AI legislation, but you also have quite a number of other states that regulate in the context of AI under their consumer protection laws, and those laws are very focused on individual privacy rights and deception around companies not telling consumers how they may use their data in an AI context.

I think that there are ways to harmonize both of those requirements and sets of goals. I think that one thing that's important is to sort of map what the compliance vulnerabilities might be as you're developing your AI tools, looking at the most stringent laws, which at this point are probably the state laws. I think that focusing a lot on themes that are going to be relatively important to the federal government as well as to the state government, are themes like transparency and fairness and accuracy as it relates to AI output, and as it relates to disclosures to consumers about how their data is going to be used for AI purposes.

Really looking at those key themes as you're developing your AI will be important to try to navigate the requirements as they sit between the state and federal governments. Obviously documenting everything and ensuring that your systems are adaptable, because the laws are going to develop and they're going to change, and so your systems are going to have to adapt to meet those requirements.

Videos

In the third part of her Pharma Commerce video interview, Linda Malek, JD, partner at Crowell & Moring, explains how healthcare organizations can harmonize both approaches by prioritizing fairness, transparency, and adaptable systems.

Why Regulatory Sandboxes Offer a Safe Space for AI Innovation in Healthcare

What role could regulatory sandboxes play in helping healthcare organizations test and implement AI safely, while protecting patients?

 In Europe, the regulatory sandbox is already a more well-developed concept, and so here in the US and through the AI Action Plan, I would imagine it will develop in its own unique way. I think at at least a high level for regulatory authorities, the sandbox allows legislators and other oversight agencies to really understand how the technology is developing, because very often, the technology outpaces the regulation that we have in place. By creating a regulatory sandbox, you have an opportunity for regulators to be working closely with and observing the development of AI with private companies, and so in order for them to understand those developments and how industry is using these developments, they're better able to develop rules around what best practices should look like in the development of AI.

I think that's very important when it comes to patients and other consumers who may utilize these technologies, because if you look at a partnership—that is what occurs in a regulatory sandbox. You have the regulators on one side, and then you have organizations, businesses on the other side who are able to have some regulatory certainty, as they are developing these technologies, so that they can position themselves in such a way as to push forward with the innovation, while the regulators are looking at where they may need to push back.

There's a check, there's a balance, but yet there's an opportunity to develop in this sort of protected environment. I think that from the standpoint of patients and other consumers, that should give some assurances that the AI is being developed in a way that sort of replicates how it's going to happen in the real world and how it may apply to them, and that it's not sort of AI run amok, because there's a lot of fear I think around AI as well. To develop AI in a regulatory sandbox framework like this should provide, I think, some comfort that it's being developed in a way that is going to reflect best practices in real time.

In the second part of her Pharma Commerce video interview, Linda Malek, JD, partner at Crowell & Moring, notes that by bringing regulators and innovators together, regulatory sandboxes could help US healthcare organizations test and refine AI tools responsibly, which allows oversight agencies to keep pace with rapid technological change.

Pharma’s AI Evolution: Balancing Innovation, Transparency, and Regulation

Artificial intelligence (AI) is rapidly transforming the pharmaceutical industry, but companies are still navigating how best to align innovation with growing regulatory expectations around transparency, traceability, and control. According to Honeywell’s insights, approximately 99% of organizations are already experimenting with some form of AI. However, the scale and depth of adoption vary significantly across the sector.

Shawn Opatka, representing Honeywell Life Sciences, noted that pharma companies are leveraging AI primarily to address persistent workforce gaps, skill shortages, and inefficiencies in knowledge management. Many organizations are using the technology to bridge operational gaps and enhance regulatory or quality systems, though the industry remains far from full-scale integration. AI’s appeal lies in its ability to automate complex tasks, improve compliance, and strengthen product traceability, key requirements as global oversight becomes more stringent.

Adding to the momentum is the White House’s recent AI Action Plan, designed to establish the United States as a global leader in artificial intelligence. Linda Malek highlighted that the plan emphasizes not just acceleration but also smarter regulation. It proposes measures such as regulatory sandboxes, controlled environments where companies can safely test AI technologies, as well as streamlined approval processes to reduce bureaucratic hurdles for AI-driven medical devices and software.

The plan also calls for investment in critical infrastructure, including large-scale data centers and greater access to high-quality datasets, enabling more robust model training and algorithm development.

Together, these shifts signal a pivotal moment for pharma and healthcare organizations: as AI becomes integral to quality, safety, and efficiency, balancing innovation with regulatory confidence will define the next era of digital transformation in life sciences.

How are evolving regulatory expectations around transparency, traceability, and control shaping the way pharma companies approach AI adoption?

 I think companies are, from what I'm seeing, really jumping into AI, and we see different levels of engagement, but our data actually shows that about 99% of organizations are doing something with AI. What are they doing? I think it varies widely. If I think about it, particular to the businesses we serve as Honeywell, how are they doing it in quality and regulatory areas, as you mentioned, and traceability, that really varies, but we do see a lot of adoption.

I think what we see in it is the willingness to try new things with AI and fill gaps that companies are struggling to fill today. I think we all know the reasons why AI has been adopted, whether it's skill gaps, worker shortage, just the wealth of knowledge. I think that's where a lot of companies are experimenting, but I think we're a long way from full-scale adoption.

Meanwhile, how might the White House AI Action Plan influence the pace and scope of AI adoption across hospitals, health systems, and health-tech companies?

The White House AI Action Plan that came out recently was interesting in that it really focuses on trying to make the United States a leader as it relates to AI. There's a lot of discussion throughout the document around trying to accelerate development of AI in the United States, trying to keep pace with and get ahead of our competitor countries, and ways to do that.

I think in terms of how that plan will influence the scope of AI adoption across hospitals and health systems and health tech companies, is that there are a number of different mechanisms whereby the Action Plan tries to ease the regulatory burden, like through regulatory sandboxes—which we can talk about in more detail later—and trying to streamline approval processes for AI adoption, in terms of cutting what they term as red tape to ease approval pathways for AI medical devices and software.

Invest in infrastructure, government infrastructure and calling upon agencies like NIST and like the FDA and others to try to build out data centers, to try to increase access to large datasets and so on, which are essential for really training AI models and algorithms.

As AI adoption accelerates across life sciences, Shawn Opatka, VP and GM of Honeywell Life Sciences, and Linda Malek, JD, partner at Crowell & Moring, discuss how regulatory expectations and federal initiatives—like the White House AI Action Plan—are shaping the technology’s future role in pharma quality, traceability, and healthcare systems.

Linda Malek, JD

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