12 Of The Best LEGO Car Sets Ever Made






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LEGO’s flagship car sets have quietly crept into premium-price territory over the years. But these sets are not the blocky toys you used to build in under an hour, dismantle, and lose in a bottomless pit of colored bricks under your bed. These days, many of them are serious display pieces — and they’re primarily aimed at the adult market. They often have thousands of parts, clever building techniques, and enough detail to make even non-enthusiasts stop and look twice.

In fact, LEGO has been courting adult builders and collectors for years. The Danish company now leans into licensed cars, realistic scale models, and complex builds that feel much closer to engineering projects than to traditional toys. As a result, there’s a full catalog of sets that look more at home on display next to motorsport memorabilia or diecast models than on a play mat.

This list assembles 12 of the best LEGO car sets ever made, although it’s a subjective list and many great kits have been left out. However, the included models justify their place through smart designs, satisfying builds, and, of course, serious shelf presence. Some are faithful recreations of real-life performance cars; others are movie icons or beloved classics. But all prove beyond doubt that LEGO car sets are among the most collectible display pieces for both gearheads and brick fans alike.

LEGO Icons Pickup Truck

LEGO made the decision not to brand this pickup truck after any specific manufacturer. Instead, it blended the rounded styling of several American trucks from the 1950s to create a single, composite design — something new yet instantly familiar. The LEGO Icons Pickup Truck is a dark red, broad-shouldered farm truck steeped in nostalgia, one that could easily have rolled out of rural America 70 years ago. Under the hood, the V8 engine even features a dome-shaped design, a nod to the hemispherical combustion chambers that Chrysler used in its trucks during that era.

To achieve its smooth, gap-free bodywork, the model relies heavily on SNOT (studs not on top) techniques, where bricks are oriented sideways to create a flush surface. It also comes with a full suite of seasonal accessories for different display setups, and the wooden side railings can be removed to switch it from a farm truck to a work truck — a small change that shifts the whole character of the set. It’s not just an aesthetic gem, though. The 1,677-piece set also has some functional details. The hood opens up to reveal that distinctive engine, the doors open and close, the tailgate drops, and the front wheels turn with the steering wheel.

LEGO Technic Ferrari Daytona SP3

In February 1967, three Ferraris crossed the finish line side by side at the 24 Hours of Daytona — taking first, second, and third place on American soil and gaining revenge against Ford after its dominant win at Le Mans the year before. To honor one of the most dramatic events in motorsport history, Ferrari built one of its fastest cars ever — the Daytona SP3. Only 599 were made, and each one is powered by the most potent naturally aspirated V12 Ferrari has built to date, producing about 829 horsepower at 9,250 rpm.

The LEGO Technic Ferrari Daytona SP3 captures much of that same presence, albeit on a smaller scale. But you’ll need to budget for a long build. At 3,778 pieces and hundreds of pages of instruction, you could spend days building it. But it is time well spent. Every stage reveals something new, like a mechanism you didn’t expect or a detail that makes you stop and appreciate the engineering. 

Under the rear hood, a hidden lever triggers the butterfly doors. They swing open smoothly and hold their position. Lift the rear and you can see the V12 engine. Its pistons move as you roll the finished car forward, and the removable roof, working steering, 8-speed sequential gearbox, and suspension all work exactly as they should — and there isn’t a single sticker on the model, so every detail is clean and permanent. Once built, it stretches to just over 23 inches long and fills a shelf similar to how the real thing would fill a showroom.

LEGO Batman 1989 Batmobile

In 1989, director Tim Burton gave the world “Batman,” complete with a wild-eyed Michael Keaton, a chaotically cackling Jack Nicholson, and a Batmobile so outrageously cinematic that it looked like it drove straight out of a fever dream. It was long, deeply black, and adorned with sweeping fins — an iteration that arguably beats any other Batmobile that has made it to the big screen. 

LEGO did it absolute justice with the 1989 Batmobile kit. Some even say the three minifigures are worth the price of the set alone. Batman comes with a one-piece cape and cowl made from a rubber-like material that mimics how it looked in the movie. The Joker’s gloriously over-the-top outfit is captured in full detail, and his manic grin is perfect. Bruce Wayne’s love interest, Vicky Vale, rounds out the trio. She’s armed with her trusty camera, and both she and the Joker are exclusive to this set.

But then there are the toys. Just where does he get those wonderful toys? Turn the exhaust and a pair of machine guns pop up from the bodywork, while a sliding canopy raises and moves forward to reveal a detailed cockpit. The finished model sits proudly on a rotating display stand, and you’ll never tire of admiring it from every angle. It’s a 3,308-piece set that stretches past 23.5 inches once built — and it looks so good that even Alfred would be impressed.

LEGO Icons Back to the Future Time Machine

When “Back to the Future” hit theaters in 1985, you just knew it was only a matter of time before the DeLorean DMC-12 would become one of the most iconic sci-fi vehicles in movies and TV. LEGO had to get its version right. It first had a crack at it with a smaller Ideas set in 2013, but the 2022 LEGO Icons Back to the Future Time Machine is the definitive build. The 14-inch completed model consists of 1,872 pieces, and it has remained a popular LEGO set since its release. 

Building it is a genuinely rewarding experience. Intricate sub-assemblies seem barely held together until they suddenly lock in place, and that recognizable shape slowly emerges piece by piece. The details are strong too. The flux capacitor is lit from inside by a light brick, the tires fold smoothly into flight mode, and the gull-wing doors are slowed by friction pins when they open and close.

With minor adjustments and some accessory swapping, you can configure the vehicle to appear as it did in each of the three movies. The Part I configuration has the lightning rod complete with grappling hook and plutonium case. The Part II configuration swaps in Mr. Fusion, hover conversion, and Marty’s hoverboard, while Part III is covered by the period-appropriate whitewall tires and the replacement time circuits Doc Brown built in the old West.

LEGO Technic McLaren P1

The McLaren P1 set out to be the best driver’s car in the world, and it delivered. It is widely considered one of the best McLarens of all time and part of the Holy Trinity of hypercars, alongside the Ferrari LaFerrari and Porsche 918. The LEGO Technic McLaren P1 is the fifth set in the Ultimate Car Concept Series, and at 3,893 pieces, it is a serious undertaking. The build demands your full attention from start to finish because if you get something wrong early, you’ll be taking it apart later. It might be complex, but building it is a blast.

Inside the finished model, the V8 cylinders are transparent so you can watch the pistons move. The hybrid system is also replicated, allowing you to switch between combined power, electric-only mode, and neutral, while the paddle shifters operate the gearbox. In addition, a worm gear mechanism adjusts the rear wing, and the dihedral doors open wide. At 23 inches long, the finished model will sit on your shelf as a bold statement. That said, collectors might like to know that if you keep the box sealed past its expected retirement date at the end of 2027, its value is predicted to rise significantly.

LEGO Technic Porsche 911 RSR

The 911 RSR is Porsche’s first-ever mid-engine 911 race car, and LEGO developed its 1,580-piece Technic replica in direct partnership with the German automaker. It’s a collaboration that shines through in the detail. The swan neck rear wing and extended rear diffuser are faithfully reproduced, and the body curves are beautifully shaped using flex tubes. Lift the rear bodywork, and you’ll see the six-cylinder boxer engine, with pistons that move as you roll the car forward. The working differential and independent suspension add further mechanical credibility, and — as a bonus — the cockpit features a track map of the Laguna Seca circuit printed onto the driver door.

For anyone looking for a display Porsche 911, this finished model is 19 inches long and will sit proudly in any room. It’s a satisfying build, too, moving through its stages in a logical sequence. There’s nothing overly complicated, and it’s even fairly easy to get through for younger builders. And for anyone new to large Technic builds, the Porsche 911 RSR is the perfect warm-up for bigger models.

LEGO Technic Land Rover Defender

The gearbox on the LEGO Technic Land Rover Defender alone justifies its place on this list. With four gears, high and low modes, a reverse gear, and two levers plus a selector to control it all, it was one of the most advanced gearboxes LEGO Technic had produced at the time. On top of that, the olive green and black color scheme is spot on, and the front of one of the most iconic Land Rover models ever produced is unmistakably the Defender from every angle. You can turn the mounted spare wheel on the rear to swing the tail door open, while under the bonnet, you’ll find a working winch and a six-cylinder engine complete with moving pistons.

The 2,573-piece Defender also comes loaded with all the overlanding gear you need for the wilderness. It’s a display piece that looks ready to go anywhere, but it’s the build itself that makes it one of LEGO’s most entertaining Technic projects. Starting with the rear suspension and working through the chassis, gearbox, interior, and bodywork in a logical sequence, you’ll find little surprises at every stage, like forward-folding rear seats that reveal that complex gearbox. 

LEGO Technic Dom’s Dodge Charger

Are there any other cars in film history that can carry the weight of Dom Toretto’s 1970 Dodge Charger R/T in “Fast & Furious”? After all, it’s one of the flashiest cars in the movie, and LEGO had to ensure it got it as authentic as possible. It’s a 1,077-piece Technic replica that was launched in collaboration with both Universal Studios and Dodge, so nailing the details was never going to be a problem.

The car’s V8 engine sits under an opening hood with moving pistons, while the engine carries an internal chain mechanism that adds a layer of authenticity you might not expect at this scale. The suspension is well-judged, too. It has enough give to make this muscle car genuinely satisfying to handle, while the wheelie bar deploys, allowing you to recreate one of the most iconic scenes from the first movie. Tucked into the trunk, you’ll even find the nitro bottles Dom used to win the film’s final race. 

The build is pretty accessible for most, though fitting the interior roof assembly is a bit of a challenge. Younger builders might need help at this point, but halfway through construction, the full mechanical package is operational; you can get those wheels spinning across the bedroom floor before the bodywork has even been put together. Once built, the Dodge Charger is striking — it’ll even win the hearts of those who have no interest in the movie.

LEGO Technic Bugatti Chiron

At a cost of around $3 million and featuring a W16 engine that produces 1,479 horsepower, the Bugatti Chiron exists in a world most of us can only dream about. However, the LEGO Technic Bugatti Chiron has a reputation as being one of the most premium building experiences the company has ever offered, compensating dreamers a little. It takes its name from Louis Chiron, the legendary driver who raced for Bugatti in the 1920s and ’30s, and the Technic version offers the signature two-tone blue in homage to the marque’s heritage. 

The build even replicates the way the real Chiron is put together, with the front and rear sections constructed independently before being joined together. It’s quite the build, too. With 3,599 pieces requiring 970 steps across 628 pages of instruction, it can take about half a day to construct. It deserves the commitment, though, and there is a nine-episode podcast that accompanies the build, taking you inside the making of the real car.

Mechanically, the speed key raises the rear wing just as it does on the real thing. But it’s the eight-speed gearbox that impresses most. It’s designed around the real car’s seven-speed system, but the eighth gear was forced in because LEGO geometry simply doesn’t allow for an odd number. Engage the paddle shifter, and you can run it through the gears and watch the pistons respond and work harder as the ratios change.

LEGO Icons Ghostbusters ECTO-1

The 1959 Cadillac Miller-Meteor was originally built, among other things, as a hearse or an ambulance — quite fitting, given what it would eventually be used for in the “Ghostbusters” movies. If you ain’t afraid of no ghost, this 2,352-piece LEGO Icons Ghostbusters ECTO-1 is based on the more recent sequel “Ghostbusters: Afterlife.” It’s the definitive ECTO-1 build; however, the rust stickers are pretty much the only real difference from the 1984 original, so you can simply leave them off if you want the classic ECTO-1.

The deeply satisfying build takes around six hours, and it’s packed with clever techniques like using ball-and-hitch connections to achieve otherwise impossible angles on the rear quarter panels and a gear-and-axle system that puts the roof instruments in motion as the rear wheels turn. Some of the parts are also genuinely creative. The front grille is assembled from 44 minifigure roller skates, which makes little sense until you see it. You’ll also find other satisfying details like a Marshmallow Man bag that goes in the front passenger seat and, of course, a proton pack. 

Creator Expert Ford Mustang

The 1967 Ford Mustang GT Fastback is one of the most celebrated American muscle cars ever built. And when you open the hood of this 1,471-piece Creator Expert Ford Mustang set, you’ll find a big-block 390 V8 engine hiding intricate details you might never have expected. Among them are a battery with color-coded terminals and an oil filler cap bearing the Mustang emblem. The car is finished in Acapulco Blue, and the white racing stripes are printed on for a level of detail that tells you everything you need to know about what LEGO’s priorities were when designing it.

As it’s a Creator set, mechanical details are limited beyond the rear axle adjusting to change the rake angle, the steering wheel turning the front wheels, and the doors, hood, and trunk opening and closing. Customization options are a pleasure, though. You can switch between the configurations of a standard road car and a race-prepped muscle car by adding or removing the included supercharger, side exhaust pipes, ducktail spoiler, chin spoiler, and nitrous oxide tank. The build is full of clever techniques that make you pause and think, too. For example, the doors close flush with the quarter panels thanks to half-bows built into the door jamb, and the dashboard is secured using Technic beams that line up perfectly with a slope brick.

LEGO Technic Lamborghini Sián FKP 37

The Lamborghini Sián FKP 37 is one of the most visually arresting supercars ever made and among the fastest Lamborghinis ever built. The LEGO Technic version captures it perfectly. The lime green color scheme with golden rims is far from subtle, but it helps the car dominate any shelf or room where it’s displayed. Every detail is printed, too. You won’t find a single sticker anywhere on this car. Even the display plate is fully printed. 

But, at 3,696 pieces, it’s one serious undertaking. The transmission is the most complex section of the build and will test your concentration, but conquering it makes the build so satisfying. The end result is a stunning 23-inch-long model that will likely stop the conversation of anyone who takes a look. 

Features-wise, the scissor doors deploy at the touch of a trigger, and the V12 pistons move. Beneath the chassis, the eight-speed gearbox sits exposed so you can watch it work as you move through the ratios. Additionally, the suspension absorbs movement in a way that feels surprisingly true to life, and the movable rear spoiler adjusts for top-speed mode. 

Methodology

We drew on a combination of crowd-sourced rankings from BrickRanker and sales performance where data was available. However, these were balanced against more subjective considerations — build experience, mechanical complexity, visual impact, and what can only be described as the “cool factor.” No methodology is perfect when it comes to “best of” LEGO sets, and any such list will inevitably invite disagreement from readers. So apologies in advance to those other awesome LEGO car sets that didn’t make the final cut.





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Recent Reviews


In May 2024, we released Part I of this series, in which we discussed agentic AI as an emerging technology enabling a new generation of AI-based hardware devices and software tools that can take actions on behalf of users. It turned out we were early – very early – to the discussion, with several months elapsing before agentic AI became as widely known and discussed as it is today. In this Part II, we return to the topic to explore legal issues concerning user liability for agentic AI-assisted transactions and open questions about existing legal frameworks’ applicability to the new generation of AI-assisted transactions.

Background: Snapshot of the Current State of “Agents”[1]

“Intelligent” electronic assistants are not new—the original generation, such as Amazon’s Alexa, have been offering narrow capabilities for specific tasks for more than a decade. However, as OpenAI’s CEO Sam Altman commented in May 2024, an advanced AI assistant or “super-competent colleague” could be the killer app of the future. Later, Altman noted during a Reddit AMA session: “We will have better and better models. But I think the thing that will feel like the next giant breakthrough will be agents.” A McKinsey report on AI agents echoes this sentiment: “The technology is moving from thought to action.” Agentic AI represents not only a technological evolution, but also a potential means to further spread (and monetize) AI technology beyond its current uses by consumers and businesses. Major AI developers and others have already embraced this shift, announcing initiatives in the agentic AI space. For example:  

  • Anthropic announced an updated frontier AI model in public beta capable of interacting with and using computers like human users;
  • Google unveiled Gemini 2.0, its new AI model for the agentic era, alongside Project Mariner, a prototype leveraging Gemini 2.0 to perform tasks via an experimental Chrome browser extension (while keeping a “human in the loop”);
  • OpenAI launched a “research preview” of Operator, an AI tool that can interface with computers on users’ behalf, and launched beta feature “Tasks” in ChatGPT to facilitate ongoing or future task management beyond merely responding to real time prompts;
  • LexisNexis announced the availability of “Protégé,” a personalized AI assistant with agentic AI capabilities;
  • Perplexity recently rolled out “Shop Like a Pro,” an AI-powered shopping recommendation and buying feature that allows Perplexity Pro users to research products and, for those merchants whose sites are integrated with the tool, purchase items directly on Perplexity; and
  • Amazon announced Alexa+, a new generation of Alexa that has agentic capabilities, including enabling Alexa to navigate the internet and execute tasks, as well as Amazon Nova Act, an AI model designed to perform actions within a web browser.

Beyond these examples, other startups and established tech companies are also developing AI “agents” in this country and overseas (including the invite-only release of Manus AI by Butterfly Effect, an AI developer in China). As a recent Microsoft piece speculates, the generative AI future may involve a “new ecosystem or marketplace of agents,” akin to the current smartphone app ecosystem.  Although early agentic AI device releases have received mixed reviews and seem to still have much unrealized potential, they demonstrate the capability of such devices to execute multistep actions in response to natural language instructions.

Like prior technological revolutions—personal computers in the 1980s, e-commerce in the 1990s and smartphones in the 2000s—the emergence of agentic AI technology challenges existing legal frameworks. Let’s take a look at some of those issues – starting with basic questions about contract law.

Note: This discussion addresses general legal issues with respect to hypothetical agentic AI devices or software tools/apps that have significant autonomy. The examples provided are illustrative and do not reflect any specific AI tool’s capabilities.

Automated Transactions and Electronic Agents

Electronic Signatures Statutory Law Overview

A foundational legal question is whether transactions initiated and executed by an AI tool on behalf of a user are enforceable.  Despite the newness of agentic AI, the legal underpinnings of electronic transactions are well-established. The Uniform Electronic Transactions Act (“UETA”), which has been adopted by every state and the District of Columbia (except New York, as noted below), the federal E-SIGN Act, and the Uniform Commercial Code (“UCC”), serve as the legal framework for the use of electronic signatures and records, ensuring their validity and enforceability in interstate commerce. The fundamental provisions of UETA are Sections 7(a)-(b), which provide: “(a) A record or signature may not be denied legal effect or enforceability solely because it is in electronic form; (b) A contract may not be denied legal effect or enforceability solely because an electronic record was used in its formation.” 

UETA is technology-neutral and “applies only to transactions between parties each of which has agreed to conduct transactions by electronic means” (allowing the parties to choose the technology they desire). In the typical e-commerce transaction, a human user selects products or services for purchase and proceeds to checkout, which culminates in the user clicking “I Agree” or “Purchase.”  This click—while not a “signature” in the traditional sense of the word—may be effective as an electronic signature, affirming the user’s agreement to the transaction and to any accompanying terms, assuming the requisite contractual principles of notice and assent have been met.

At the federal level, the E-SIGN Act (15 U.S.C. §§ 7001-7031) (“E-SIGN”) establishes the same basic tenets regarding electronic signatures in interstate commerce and contains a reverse preemption provision, generally allowing states that have passed UETA to have UETA take precedence over E-SIGN.  If a state does not adopt UETA but enacts another law regarding electronic signatures, its alternative law will preempt E-SIGN only if the alternative law specifies procedures or requirements consistent with E-SIGN, among other things.

However, while UETA has been adopted by 49 states and the District of Columbia, it has not been enacted in New York. Instead, New York has its own electronic signature law, the Electronic Signature Records Act (“ESRA”) (N.Y. State Tech. Law § 301 et seq.). ESRA generally provides that “An electronic record shall have the same force and effect as those records not produced by electronic means.” According to New York’s Office of Information Technology Services, which oversees ESRA, “the definition of ‘electronic signature’ in ESRA § 302(3) conforms to the definition found in the E-SIGN Act.” Thus, as one New York state appellate court stated, “E-SIGN’s requirement that an electronically memorialized and subscribed contract be given the same legal effect as a contract memorialized and subscribed on paper…is part of New York law, whether or not the transaction at issue is a matter ‘in or affecting interstate or foreign commerce.’”[2] 

Given US states’ wide adoption of UETA model statute, with minor variations, this post will principally rely on its provisions in analyzing certain contractual questions with respect to AI agents, particularly given that E-SIGN and UETA work toward similar aims in establishing the legal validity of electronic signatures and records and because E-SIGN expressly permits states to supersede the federal act by enacting UETA.  As for New York’s ESRA, courts have already noted that the New York legislature incorporated the substantive terms of E-SIGN into New York law, thus suggesting that ESRA is generally harmonious with the other laws’ purpose to ensure that electronic signatures and records have the same force and effect as traditional signatures.  

Electronic “Agents” under the Law

Beyond affirming the enforceability of electronic signatures and transactions where the parties have agreed to transact with one another electronically, Section 2(2) of UETA also contemplates “automated transactions,” defined as those “conducted or performed, in whole or in part, by electronic means or electronic records, in which the acts or records of one or both parties are not reviewed by an individual.” Central to such a transaction is an “electronic agent,” which Section 2(6) of UETA defines as “a computer program or an electronic or other automated means used independently to initiate an action or respond to electronic records or performances in whole or in part, without review or action by an individual.” Under UETA, in an automated transaction, a contract may be formed by the interaction of “electronic agents” of the parties or by an “electronic agent” and an individual. E-SIGN similarly contemplates “electronic agents,” and states: “A contract or other record relating to a transaction in or affecting interstate or foreign commerce may not be denied legal effect, validity, or enforceability solely because its formation, creation, or delivery involved the action of one or more electronic agents so long as the action of any such electronic agent is legally attributable to the person to be bound.”[3] Under both of these definitions, agentic AI tools—which are increasingly able to initiate actions and respond to records and performances on behalf of users—arguably qualify as “electronic agents” and thus can form enforceable contracts under existing law.[4]

AI Tools and E-Commerce Transactions

Given this existing body of statutory law enabling electronic signatures, from a practical perspective this may be the end of the analysis for most e-commerce transactions. If I tell an AI tool to buy me a certain product and it does so, then the product’s vendor, the tool’s provider and I might assume—with the support of UETA, E-SIGN, the UCC, and New York’s ESRA—that the vendor and I (via the tool) have formed a binding agreement for the sale and purchase of the good, and that will be the end of it unless a dispute arises about the good or the payment (e.g., the product is damaged or defective, or my credit card is declined), in which case the AI tool isn’t really relevant.

But what if the transaction does not go as planned for reasons related to the AI tool? Consider the following scenarios:

  • Misunderstood Prompts: The tool misinterprets a prompt that would be clear to a human but is confusing to its model (e.g., the user’s prompt states, “Buy two boxes of 101 Dalmatians Premium dog food,” and the AI tool orders 101 two-packs of dog food marketed for Dalmatians).
  • AI Hallucinations: The user asks for something the tool cannot provide or does not understand, triggering a hallucination in the model with unintended consequences (e.g., the user asks the model to buy stock in a company that is not public, so the model hallucinates a ticker symbol and buys stock in whatever real company that symbol corresponds to).
  • Violation of Limits: The tool exceeds a pre-determined budget or financial parameter set by the user (e.g., the user’s prompt states, “Buy a pair of running shoes under $100” and the AI tool purchases shoes from the UK for £250, exceeding the user’s limit).
  • Misinterpretation of User Preference: The tool misinterprets a prompt due to lack of context or misunderstanding of user preferences (e.g., the user’s prompt states, “Book a hotel room in New York City for my conference,” intending to stay near the event location in lower Manhattan, and the AI tool books a room in Queens because it prioritizes price over proximity without clarifying the user’s preference).

Disputes like these begin with a conflict between the user and a vendor—the AI tool may have been effective to create a contract between the user and the vendor, and the user may then have legal responsibility for that contract.  But the user may then seek indemnity or similar rights against the developer of the AI tool.

Of course, most developers will try to avoid these situations by requiring user approvals before purchases are finalized (i.e., “human in the loop”). But as desire for efficiency and speed increases (and AI tools become more autonomous and familiar with their users), these inbuilt protections could start to wither away, and users that grow accustomed to their tool might find themselves approving transactions without vetting them carefully. This could lead to scenarios like the above, where the user might seek to void a transaction or, if that fails, even try to avoid liability for it by seeking to shift his or her responsibility to the AI tool’s developer.[5] Could this ever work? Who is responsible for unintended liabilities related to transactions completed by an agentic AI tool?

Sources of Law Governing AI Transactions

AI Developer Terms of Service

As stated in UETA’s Prefatory Note, the purpose of UETA is “to remove barriers to electronic commerce by validating and effectuating electronic records and signatures.” Yet, the Note cautions, “It is NOT a general contracting statute – the substantive rules of contracts remain unaffected by UETA.”  E-SIGN contains a similar disclaimer in the statute, limiting its reach to statutes that require contracts or other records be written, signed, or in non-electronic form (15 U.S.C. §7001(b)(2)). In short, UETA, E-SIGN, and the similar UCC provisions do not provide contract law rules on how to form an agreement or the enforceability of the terms of any agreement that has been formed.

Thus, in the event of a dispute, terms of service governing agentic AI tools will likely be the primary source to which courts will look to assess how liability might be allocated. As we noted in Part I of this post, early-generation agentic AI hardware devices generally include terms that not only disclaim responsibility for the actions of their products or the accuracy of their outputs, but also seek indemnification against claims arising from their use. Thus, absent any express customer-favorable indemnities, warranties or other contractual provisions, users might generally bear the legal risk, barring specific legal doctrines or consumer protection laws prohibiting disclaimers or restrictions of certain claims.[6]

But what if the terms of service are nonexistent, don’t cover the scenario, or—more likely—are unenforceable? Unenforceable terms for online products and services are not uncommon, for reasons ranging from “browsewrap” being too hidden, to specific provisions being unconscionable. What legal doctrines would control during such a scenario?

The Backstop: User Liability under UETA and E-SIGN

Where would the parties stand without the developer’s terms? E-SIGN allows for the effectiveness of actions by “electronic agents” “so long as the action of any such electronic agent is legally attributable to the person to be bound.” This provision seems to bring the issue back to the terms of service governing a transaction or general principles of contract law. But again, what if the terms of service are nonexistent or don’t cover a particular scenario, such as those listed above. As it did with the threshold question of whether AI tools could form contracts in the first place, UETA appears to offer a position here that could be an attractive starting place for a court. Moreover, in the absence of express language under New York’s ESRA, a New York court might apply E-SIGN (which contains an “electronic agent” provision) or else find insight as well by looking at UETA and its commentary and body of precedent if the court isn’t able to find on-point binding authority, which wouldn’t be a surprise, considering that we are talking about technology-driven scenarios that haven’t been possible until very recently.

UETA generally attributes responsibility to users of “electronic agents”, with the prefatory note explicitly stating that the actions of electronic agents “programmed and used by people will bind the user of the machine.” Section 14 of UETA (titled “Automated Transaction”) reinforces this principle, noting that a contract can be formed through the interaction of “electronic agents” “even if no individual was aware of or reviewed the electronic agents’ actions or the resulting terms and agreements.” Accordingly, when automated tools such as agentic AI systems facilitate transactions between parties who knowingly consent to conduct business electronically, UETA seems to suggest that responsibility defaults to the users—the persons who most immediately directed or initiated their AI tool’s actions. This reasoning treats the AI as a user’s tool, consistent with the other UETA Comments (e.g., “contracts can be formed by machines functioning as electronic agents for parties to a transaction”).

However, different facts or technologies could lead to alternative interpretations, and ambiguities remain. For example, Comment 1 to UETA Section 14 asserts that the lack of human intent at the time of contract formation does not negate enforceability in contracts “formed by machines functioning as electronic agents for parties to a transaction” and that “when machines are involved, the requisite intention flows from the programming and use of the machine” (emphasis added).

This explanatory text has a couple of issues. First, it is unclear about what constitutes “programming” and seems to presume that the human intention at the programming step (whatever that may be) is more-or-less the same as the human intention at the use step[7], but this may not always be the case with AI tools. For example, it is conceivable that an AI tool could be programmed by its developer to put the developer’s interests above the users’, for example by making purchases from a particular preferred e-commerce partner even if that vendor’s offerings are not the best value for the end user. This concept may not be so far-fetched, as existing GenAI developers have entered into content licensing deals with online publishers to obtain the right for their chatbots to generate outputs or feature licensed content, with links to such sources. Of course, there is a difference between a chatbot offering links to relevant licensed news sources that are accurate (but not displaying appropriate content from other publishers) versus an agentic chatbot entering into unintended transactions or spending the user’s funds in unwanted ways. This discrepancy in intention alignment might not be enough to allow the user to shift liability for a transaction from a user to a programmer, but it is not hard to see how larger misalignments might lead to thornier questions, particularly in the event of litigation when a court might scrutinize the enforceability of an AI vendor’s terms (under the unconscionability doctrine, for example). 

Second, UETA does not contemplate the possibility that the AI tool might have enough autonomy and capability that some of its actions might be properly characterized as the result of its own intent. Looking at UETA’s definition of “electronic agent,” the commentary notes that “As a general rule, the employer of a tool is responsible for the results obtained by the use of that tool since the tool has no independent volition of its own.” But as we know, technology has advanced in the last few decades and depending on the tool, an autonomous AI tool might one day have much independent volition (and further UETA commentary admits the possibility of a future with more autonomous electronic agents). Indeed, modern AI researchers have been contemplating this possibility even before rapid technological progress began with ChatGPT.

Still, Section 10 of UETA may be relevant to some of the scenarios from our bulleted selection of AI tool mishaps listed above, including misunderstood prompts or AI hallucinations. UETA Section 10 (titled “Effect of Change or Error”) outlines the possible actions a party may take when discovering human or machine errors or when “a change or error in an electronic record occurs in a transmission between parties to a transaction.” The remedies outlined in UETA depend on the circumstances of the transaction and whether the parties have agreed to certain security procedures to catch errors (e.g., a “human in the loop” confirming an AI-completed transaction) or whether the transaction involves an individual and a machine.[8]  In this way, the guardrails integrated into a particular AI tool or by the parties themselves play a role in the liability calculus. The section concludes by stating that if none of UETA’s error provisions apply, then applicable law governs, which might include the terms of the parties’ contract and the law of mistake, unconscionability and good faith and fair dealing.

* * *

Thus, along an uncertain path we circle back to where we started: the terms of the transaction and general contract law principles and protections. However, not all roads lead to contract law. In our next installment in this series, we will explore the next logical source of potential guidance on AI tool liability questions: agency law.  Decades of established law may now be challenged by a new sort of “agent” in the form of agentic AI…and a new AI-related lawsuit foreshadows the issues to come.


[1] In keeping with common practice in the artificial intelligence industry, this article refers to AI tools that are capable of taking actions on behalf of users as “agents” (in contrast to more traditional AI tools that can produce content but not take actions). However, note that the use of this term is not intended to imply that these tools are “agents” under agency law.

[2] In addition, the UCC has provisions consistent with UETA and E-SIGN providing for the use of electronic records and electronic signatures for transactions subject to the UCC. The UCC does not require the agreement of the parties to use electronic records and electronic signatures, as UETA and E-SIGN do.

[3] Under E-SIGN, “electronic agent” means “a computer program or an electronic or other automated means used independently to initiate an action or respond to electronic records or performances in whole or in part without review or action by an individual at the time of the action or response.”

[4] It should be noted that New York’s ESRA does not expressly provide for the use of “electronic agents,” yet does not prohibit them either.  Reading through ESRA and the ESRA regulation, the spirit of the law could be construed as forward-looking and seems to suggest that it supports the use of automated systems and electronic means to create legally binding agreements between willing parties. Looking to New York precedent, one could also argue that E-SIGN, which contains provisions about the use of “electronic agents”, might also be applicable in certain circumstances to fill the “electronic agent” gap in ESRA. For example, the ESRA regulations (9 CRR-NY § 540.1) state: “New technologies are frequently being introduced. The intent of this Part is to be flexible enough to embrace future technologies that comply with ESRA and all other applicable statutes and regulations.”  On the other side, one could argue that certain issues surrounding “electronic agents” are perhaps more unsettled in New York.  Still, New York courts have found ESRA consistent with E-SIGN.  

[5] Since AI tools are not legal persons, they could not be liable themselves (unlike, for example, a rogue human agent could be in some situations). We will explore agency law questions in Part III.

[6] Once agentic AI technology matures, it is possible that certain user-friendly contractual standards might emerge as market participants compete in the space. For example, as we wrote about in a prior post, in 2023 major GenAI providers rolled out indemnifications to protect their users from third-party claims of intellectual property infringement arising from GenAI outputs, subject to certain carve-outs.

[7] The electronic “agents” in place at the time of UETA’s passage might have included basic e-commerce tools or EDI (Electronic Data Interchange), which is used by businesses to exchange standardized documents, such as purchase orders, electronically between trading partners, replacing traditional methods like paper, fax, mail or telephone. Electronic tools are generally designed to explicitly perform according to the user’s intentions (e.g., clicking on an icon will add this item to a website shopping cart or send this invoice to the customer) and UETA, Section 10, contains provisions governing when an inadvertent or electronic error occurs (as opposed to an abrogation of the user’s wishes).

[8] For example, UETA Section 10 states that if a change or error occurs in an electronic record during transmission between parties to a transaction, the party who followed an agreed-upon security procedure to detect such changes can avoid the effect of the error, if the other party who didn’t follow the procedure would have detected the change had they complied with the security measure; this essentially places responsibility on the party who failed to use the agreed-upon security protocol to verify the electronic record’s integrity.

Comments to UETA Section 10 further explain the context of this section: “The section covers both changes and errors. For example, if Buyer sends a message to Seller ordering 100 widgets, but Buyer’s information processing system changes the order to 1000 widgets, a “change” has occurred between what Buyer transmitted and what Seller received. If on the other hand, Buyer typed in 1000 intending to order only 100, but sent the message before noting the mistake, an error would have occurred which would also be covered by this section.”  In the situation where a human makes a mistake when dealing with an electronic agent, the commentary explains that “when an individual makes an error while dealing with the electronic agent of the other party, it may not be possible to correct the error before the other party has shipped or taken other action in reliance on the erroneous record.”



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