In today’s column, I examine the increasing use of AI sandboxes as a regulatory safety net.
Here’s the deal. Suppose an AI maker is creating an AI that could inadvertently cause substantial harm. That might not be the intention of the AI maker; nonetheless, there is a chance that the AI could go destructively awry. If the upsides of the AI are great, it makes sense to realistically figure out what the downsides are and try to curtail or limit them.
Lawmakers are at times crafting new AI laws requiring the use of an AI sandbox or containment system so that AI makers are forced to safely test their AI. The regulation says that it is permissible to work on such AI, though only while it is contained inside the AI sandbox. The AI sandbox is to be a tightly controlled environment that will keep the AI from escaping into the public realm. Whatever happens in the AI sandbox is not supposed to cause any external impacts.
Some lawmakers and policymakers are highly supportive of the AI sandbox approach, while others worry that these AI sandboxes might give us a false sense of security, namely that while testing the AI, it manages somehow to leak or break out and cause harm anyway. The matter is a tradeoff of potential benefits versus possible harm. The path to AI that brings about cures to cancer and other amazing upsides is likely to have hiccups along the way, ergo AI sandboxes might be a suitable legal mechanism to keep advancing AI with less chances of dire risk.
Let’s talk about it.
This analysis of AI breakthroughs is part of my ongoing Forbes column coverage on the latest in AI, including identifying and explaining various impactful AI complexities (see the link here).
AI And The Law
As a quick background, I’ve been extensively covering and analyzing a myriad of facets regarding the intersection of AI and the law for many years. You can find my writings not only in my Forbes column but also as posted in Bloomberg Law, ABA Law Journal, The National Jurist, The Global Legal Post, Lawyer Monthly, The Legal Technologist, MIT Computational Law Journal, and so on.
There are two major perspectives on the mixture of AI and law:
- (1) Law & AI. The application of laws to the governance and regulation of AI.
- (2) AI & Law. The application of AI to perform legal reasoning.
Thus, you can apply the law to AI, and conversely, you can apply AI to the law. For my big picture overview of both of these exciting and rapidly evolving realms, see my discussion at the link here and the link here.
When it comes to applying the law to AI, the aim is to establish suitable regulations and provide appropriate governance on how AI should be devised and implemented. There are longstanding concerns that AI makers aren’t giving due attention to the ethical ramifications of their wares. Ethical issues are construed as “soft laws” and aren’t as formidable as legally enacted laws, known as “hard laws”. To level the playing field and keep AI makers on the up-and-up, some believe that we need more lawmakers to make more laws about AI.
It might seem easy to just go ahead and pile on new AI laws. The problem is that for each new AI law, there is a solid chance of creating confusion and muddying the waters of AI expectations. Yes, ironically, though AI laws are supposed to straighten things out, if the AI laws aren’t properly crafted, they can lead to all sorts of undesirable adverse consequences.
Sandboxes As A Regulatory Scheme
A trend that is quickly gaining traction consists of writing new AI laws that have a provision specifically associated with AI sandboxes. To make sure we are all talking about the same phenomenon when it comes to sandboxes, let’s go ahead and consider my three definitions about the overall sandbox approach.
First, a longstanding legal mechanism consists of establishing regulatory sandboxes in general. These are usually done for a specific purpose. For example, suppose lawmakers want to encourage the development of consumer-oriented financial products such as digital payments. A new law in the financial realm might specify that companies wanting to develop and test digital payments can do so by invoking a regulatory sandbox that protects the firms from various legal exposures during the testing process.
Here is my ad hoc definition of regulatory sandboxes:
- My definition of regulatory sandboxes: “A regulatory sandbox can be established by lawmakers via enacting a law that allows entities to test innovations under defined conditions with tailored regulatory requirements, supervision, and time limits. It is a sandbox because the testing is generally done without the customary legal restrictions or legal exposures that would ensue. Regulatory sandboxes can vary widely in scope, legal effect, and oversight, but are generally designed to enable controlled experimentation while managing risk and informing future regulation.”
AI Sandboxes Are Tech Environments
Now that we’ve defined regulatory sandboxes, I’d like to switch gears and move outside of the legal domain. Within the AI field, AI makers often set up a computer-based environment that is closed off from the rest of the world and allows them to test their AI without concern for the AI touching anything beyond the controlled environment. This helps prevent accidental issues such as the AI accessing the Internet and causing trouble elsewhere online.
These are commonly referred to as AI sandboxes. They often don’t have anything particularly to do with laws or regulations per se. It is just something that AI makers do to be on the safe side (better to be safe than sorry). It allows them the freedom to play extensively with the AI and not worry about any demonstrative harm occurring.
Here is my ad hoc definition of AI sandboxes:
- My definition of AI sandboxes: AI sandboxes are computer-based controlled environments for developing, testing, and evaluating AI under constrained or structured conditions. This is usually done in an offline manner so that there is a limited chance of the AI impacting anything outside of the controlled environment. AI makers might make use of an AI sandbox entirely of their own volition, and/or they might do so because of a law or laws that stipulate the use of an AI sandbox for certain classes or types of AI.
Regulatory AI Sandboxes
Now, let’s go ahead and combine the aspects of regulatory sandboxes with the particulars of AI sandboxes, thus we would have regulatory AI sandboxes. It is a match made in heaven, as they say.
Here is my ad hoc definition of regulatory AI sandboxes:
- My definition of regulatory AI sandboxes: “A regulatory AI sandbox can be established by lawmakers via enacting a law that allows entities to test AI innovations under defined conditions with tailored regulatory requirements, supervision, and time limits. AI sandboxes are computer-based controlled environments for developing, testing, and evaluating AI under constrained or structured conditions. The testing is generally done without customary legal restrictions or legal exposures that would ensue. Regulatory AI sandboxes can vary widely in scope, legal effect, and oversight, but are generally designed to enable controlled experimentation of AI while managing risk and informing future regulation.”
The gist is that a regulatory AI sandbox is a legally stipulated means of providing legal insulation for AI makers who are pursuing innovations in AI. The promise is that the AI sandbox will provide secure containment, thus limiting any spillover during AI testing. In return, the AI maker is provided with temporary exemptions from specific legal aspects and granted a legally allowed safe harbor.
A law might explicitly require that designated regulatory agencies or empowered third parties must provide supervisory oversight of the regulatory AI sandboxes to ensure that the matter is kept on the up-and-up.
An Example Of Regulatory AI Sandbox
I’m sure you are wondering whether regulatory AI sandboxes are in existence. Yes, but so far it is somewhat rare. For my state-by-state analysis of the numerous state-level AI laws, see the link here, of which few currently enable AI sandboxes. My prediction is that we will see policymakers and lawmakers increasingly opting to include regulatory AI sandboxes in the newest AI laws.
Let’s take a brief look at one such instance.
In my coverage of the recently enacted Texas AI law known as TRIAGA (HB 149), the Texas Responsible Artificial Intelligence Governance Act, which got underway this year in 2026, I briefly touched upon the full range of what the AI law encompasses; see my in-depth analysis at the link here. This sweeping law about AI includes a provision specifically associated with AI sandboxes. Texas is one of the few states that has opted to legally indicate a provision for AI sandboxes.
The description that I will be citing is found in Section 553.051 of the Texas AI law, under the title of “Establishment of Sandbox Program,” and continues throughout additional sections and subsections.
Let’s get started with the overall purpose of the stipulated AI sandbox provision:
- “(a) The department, in consultation with the council, shall create a regulatory sandbox program that enables a person to obtain legal protection and limited access to the market in this state to test innovative artificial intelligence systems without obtaining a license, registration, or other regulatory authorization.”
As you can plainly see, the idea is that rather than forcing an AI maker to have to upfront get special licenses, registration, or regulatory authorization to try out AI that might veer into unlawful territory, the AI maker can instead make use of an AI sandbox. The AI maker gains applicable legal protection accordingly. This helps to streamline the advancement of AI.
Legal Basis For AI Sandboxes
The AI law explains why a legally stipulated AI sandbox would be useful:
- “(b) The program is designed to: (1) promote the safe and innovative use of artificial intelligence systems across various sectors including healthcare, finance, education, and public services; (2) encourage responsible deployment of artificial intelligence systems while balancing the need for consumer protection, privacy, and public safety; (3) provide clear guidelines for a person who develops an artificial intelligence system to test systems while certain laws and regulations related to the testing are waived or suspended; and (4) allow a person to engage in research, training, testing, or other pre-deployment activities to develop an artificial intelligence system.”
The bottom line is that if society wants AI that stretches boundaries, but might step over the line into unlawful acts, an AI sandbox provides a means to ascertain whether the AI can be properly shaped to stay within lawful actions.
It could be that while testing the AI, the AI reveals untoward tendencies, which the AI maker can proceed to fix. If this happened outside of the AI sandbox, presumably the AI maker would have instantly broken the law and be subject to criminal and civil actions. Instead, via the AI sandbox, they can keep readjusting until the AI is ready for usage outside an AI sandbox (well, if the AI can be sufficiently corrected).
The Legal Caveats At Play
You might say that the AI maker has a get-out-of-jail-free card by making use of the AI sandbox. For example, this is what the law says about the potential actions of the statewide attorney general:
- “(c) The attorney general may not file or pursue charges against a program participant for violation of a law or regulation waived under this chapter that occurs during the testing period.”
And this is what state agencies can and cannot do:
- “(d) A state agency may not file or pursue punitive action against a program participant, including the imposition of a fine or the suspension or revocation of a license, registration, or other authorization, for violation of a law or regulation waived under this chapter that occurs during the testing period.”
You might be concerned that an AI maker might sneakily subvert this AI sandbox and use it as some kind of insidious cover for devious deeds. The law appears to give AI makers a tremendous amount of leeway. Recognizing this concern, an additional provision pulls back a bit and gives added teeth:
- “(e) Notwithstanding Subsections (c) and (d), the requirements of Subchapter B, Chapter 552, may not be waived, and the attorney general or a state agency may file or pursue charges or action against a program participant who violates that subchapter.”
The gist is that an AI maker must toe the line. They are not supposed to willy-nilly and sneakily undermine the purpose of the regulatory AI sandbox. That being said, we don’t yet know whether an AG or state agency will catch on when an AI maker goes down an unsavory path with an AI sandbox, nor whether legal action will be taken against the AI maker. As with all laws, until the rubber meets the road, it is hard to say what will happen in the real world.
Slew Of Complexity
I’ve introduced you to regulatory AI sandboxes from a 30,000-foot level. There is a lot of complexity and detail that come into the picture. I’ll give you a quick taste.
Some believe that a regulatory AI sandbox is a kind of “gift” to AI makers and should only be allowed in high-risk situations. A law might stipulate that an AI sandbox must be used in high-risk AI endeavors. The law might also say that medium-risk circumstances can request the use of an AI sandbox, but that it is not guaranteed you’ll get it, while low-risk AI cannot invoke it at all. Others believe that it should simply be a broadly defined case-by-case basis, whereby the AI maker must apply to use a regulatory AI sandbox and justify why they wish to use one.
Another aspect is who physically establishes the regulatory AI sandboxes.
Should the government have AI sandboxes ready to go and make those available to AI makers who are approved to use them? Or should the AI maker be responsible for establishing a regulatory AI sandbox that has been approved for usage? One view is that the government should not be in the business of creating AI sandboxes. Let the AI makers do this. Meanwhile, the government would exercise oversight. A contrasting view is that letting AI makers craft their own regulatory sandboxes is akin to letting the fox run the henhouse.
There is plenty of controversy underlying regulatory AI sandboxes. One especially heated topic is that if a law requires the use of AI sandboxes, the cost to the AI maker is going to be heightened when devising the AI. Lots of overhead goes toward setting up and maintaining the regulatory AI sandbox. This, in turn, suggests that only the elite or top money AI makers can afford to go this route, and locks out the smaller-sized AI makers. Perhaps this is a form of regulatory capture.
The Delicate Balance
Some final thoughts for now.
An enlarged viewpoint of regulatory AI sandboxes suggests that this isn’t solely about the testing of AI. Think of AI as being shaped in a systems life cycle fashion. First, an idea arises about what AI might be able to accomplish. Next, an effort is made to design the AI and then build it. Testing takes place. After the AI is put into production, it must be maintained and kept updated. This is the classic waterfall model or iterative system development life cycle (SDLC).
Regulatory AI sandboxes can be stipulated for the five major stages of the AI system life cycle, including:
- (1) Regulatory AI sandbox for AI concept and design: Establish a regulatory AI sandbox for guiding what AI gets built, and the AI architectural structure.
- (2) Regulatory AI sandbox for AI development: Establish a regulatory AI sandbox that is used during the AI building process.
- (3) Regulatory AI sandbox for AI testing: Establish a regulatory AI sandbox for the testing and adjustment of AI (this tends to be the most common usage).
- (4) Regulatory AI sandbox for AI deployment: Establish a regulatory AI sandbox for the fielding of AI.
- (5) Regulatory AI sandbox for monitoring AI upkeep: Establish a regulatory AI sandbox for the maintenance of AI.
Some would vehemently say that we absolutely need regulatory AI sandboxes for each of those stages. A retort is that this is craziness and an overzealous avenue of applying regulatory AI sandboxes. Focus on AI testing. Leave the rest alone.
Time will tell how this plays out.
On the topic of law, John Locke famously made this remark: “The end of law is not to abolish or restrain, but to preserve and enlarge freedom. For in all the states of created beings capable of law, where there is no law, there is no freedom.” The use and design of regulatory AI sandboxes must thread the fine line of encouraging AI innovation while protecting and securing the fate of humanity. That’s not an easy task, but one that needs to be ably managed.
