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.

  • Uses of lnformation Limited to “What is Reasonably Necessary”
  • Use of Deidentified Data Not Within Scope
  • Screen Scraping Survives

After a yearslong lead-up, the Consumer Financial Protection Bureau (CFPB) published its final “open banking” rule in October. The rule effectuates the section of the Consumer Financial Protection Act, which charged

Section 230 of the Communications Decency Act (the “CDA” or “Section 230”), known prolifically as “the 26 words that created the internet,” remains the subject of ongoing controversy. As extensively reported on this blog, the world of social media, user-generated content, and e-commerce has been consistently

On March 21, 2024, in a bold regulatory move, Tennessee Governor Bill Lee signed the Ensuring Likeness Voice and Image Security (“ELVIS”) Act (Tenn. Code Ann. §47-25-1101 et seq.) – a law which, as Gov. Lee stated, covers “new, personalized generative AI cloning models and services that enable human

Generative AI has been most synonymous in the public mind with “AI” since the commercial breakout of ChatGPT in November 2022. Consumers and businesses have seen the fruits of impressive innovation in various generative models’ ability to create audio, video, images and text, analyze and transform data, perform Q&A chatbot

  • Flight and travel data has always been valuable for data aggregators and online travel services and has prompted litigation over the years.
  • Latest suit from Air Canada against a rewards travel search site raises some interesting liability issues under the CFAA.
  • The implications of this case, if the plaintiffs are successful, could impact the legal analysis of web scraping in a variety of circumstances, including for the training of generative AI models.

In a recent post, we recounted the myriad of issues raised by recently-filed data scraping suits involving job listings, company reviews and employment data.  Soon after, another interesting scraping suit was filed, this time by a major airline against an award travel search site that aggregates fare and award travel data.  Air Canada alleges that Defendant Localhost LLC (“Localhost” or “Defendant”), operator of the Seats.aero website, unlawfully bypassed technical measures and violated Air Canada’s website terms when it scraped “vast amounts” of flight data without permission and purportedly caused slowdowns to Air Canada’s site and other problems. (Air Canada v. Localhost LLC, No. 23-01177 (D. Del. Filed Oct. 19, 2023)).[1]   

The complaint alleges that Localhost harvested data from Air Canada’s site and systems to populate the seats.aero site, which claims to be “the fastest search engine for award travel.” 

It also alleged that in addition to scraping the Air Canada website, Localhost engaged in “API scraping” by impersonating authorized requests to Air Canada’s application programming interface.  

UPDATE: On February 5, 2024, the California district court granted the defendant Aspen Technology Labs, Inc.’s motion to dismiss Jobiak LLC’s web scraping complaint for lack of personal jurisdiction, with leave to amend. The court found that Jobiak had not adequately alleged that its copyright and tort-related claims arose out of the defendant’s forum-related activities and that there were no allegations that Jobiak’s database or website was hosted on servers in the California forum.  On March 8, 2024, the court dismissed the action with prejudice, as Jobiak did not submit an amended complaint within the time allowed by the court.  

In recent years there has been a great demand for information about job listings, company reviews and employment data.   Recruiters, consultants, analysts and employment-related service providers, amongst others, are aggressively scraping job-posting sites to extract that type of information. Recall, for example, the long-running, landmark hiQ scraping litigation over the scraping of public LinkedIn data.

The two most recent disputes regarding scraping of employment and job-related data were brought by Jobiak LLC (“Jobiak”), an AI-based recruitment platform.  Jobiak filed two nearly-identical scraping suits in California district court alleging that competitors unlawfully scraped its database and copied its optimized job listings without authorization. (Jobiak LLC v. Botmakers LLC, No. 23-08604 (C.D. Cal. Filed Oct. 12, 2023); Jobiak LLC v. Aspen Technology Labs, Inc., No. 23-08728 (C.D. Cal. Filed Oct. 17, 2023)).

Back in October 2022, the Supreme Court granted certiorari in Gonzalez v. Google, an appeal that challenged whether YouTube’s targeted algorithmic recommendations qualify as “traditional editorial functions” protected by the CDA — or, rather, whether such recommendations are not the actions of a “publisher” and thus fall outside of

Competition between Amazon’s third-party merchants is notoriously fierce. The online retail giant often finds itself playing the role of referee, banning what it considers unfair business practices (such as offering free products in exchange for perfect reviews, or targeting competitors with so-called “review bombing”). Last month, in the latest round

At the close of 2022, New York Governor Kathy Hochul signed the “Digital Fair Repair Act” (S4101A/A7006-B) (to be codified at N.Y. GBL §399-nn) (the “Act”). The law makes New York the first state in the country to pass a consumer electronics right-to-repair law.[1] Similar bills are pending in other states. The Act is a slimmed down version of the bill that was first passed by the legislature last July.

Generally speaking, the Act will require original equipment manufacturers (OEMs), or their authorized repair providers, to make parts and tools and diagnostic and repair information required for the maintenance and repair of “digital electronic equipment” available to independent repair providers and consumers, on “fair and reasonable terms” (subject to certain exceptions). The law only applies to products that are both manufactured for the first time as well as sold or used in the state for the first time on or after the law’s effective date of July 1, 2023 (thus exempting electronic products currently owned by consumers).