Featured Post from Emory University, Goizueta Business School

AI Art: What Should Fair Compensation Look Like?

Jun 28, 2024

5 min

New research from Goizueta’s David Schweidel looks at questions of compensation to human artists when images based on their work are generated via artificial intelligence.

Artificial intelligence is making art. That is to say, compelling artistic creations based on thousands of years of art production may now be just a few text prompts away. And it’s all thanks to generative AI trained on internet images. You don’t need Picasso’s skillset to create something in his style. You just need an AI-powered image generator like DALL-E 3 (created by OpenAI), Midjourney, or Stable Diffusion.

If you haven’t tried one of these programs yet, you really should (free or beta versions make this a low-risk proposal). For example, you might use your phone to snap a photo of your child’s latest masterpiece from school. Then, you might ask DALL-E to render it in the swirling style of Vincent Van Gogh. A color printout of that might jazz up your refrigerator door for the better.

Intellectual Property in the Age of AI

Now, what if you wanted to sell your AI-generated art on a t-shirt or poster? Or what if you wanted to create a surefire logo for your business? What are the intellectual property (IP) implications at work?

Take the case of a 35-year-old Polish artist named Greg Rutkowski. Rutkowski has reportedly been included in more AI-image prompts than Pablo Picasso, Leonardo da Vinci, or Van Gogh. As a professional digital artist, Rutkowski makes his living creating striking images of dragons and battles in his signature fantasy style. That is, unless they are generated by AI, in which case he doesn’t.

“They say imitation is the sincerest form of flattery. But what about the case of a working artist? What if someone is potentially not receiving payment because people can easily copy his style with generative AI?” That’s the question David Schweidel, Rebecca Cheney McGreevy Endowed Chair and professor of marketing at Goizueta Business School is asking. Flattery won’t pay the bills. “We realized early on that IP is a huge issue when it comes to all forms of generative AI,” Schweidel says. “We have to resolve such issues to unlock AI’s potential.”

Schweidel’s latest working paper is titled “Generative AI and Artists: Consumer Preferences for Style and Fair Compensation.” It is coauthored with professors Jason Bell, Jeff Dotson, and Wen Wang (of University of Oxford, Brigham Young University, and University of Maryland, respectively). In this paper, the four researchers analyze a series of experiments with consumers’ prompts and preferences using Midjourney and Stable Diffusion. The results lead to some practical advice and insights that could benefit artists and AI’s business users alike.

Real Compensation for AI Work?

In their research, to see if compensating artists for AI creations was a viable option, the coauthors wanted to see if three basic conditions were met:

– Are artists’ names frequently used in generative AI prompts?

– Do consumers prefer the results of prompts that cite artists’ names?

– Are consumers willing to pay more for an AI-generated product that was created citing some artists’ names?

Crunching the data, they found the same answer to all three questions: yes.

More specifically, the coauthors turned to a dataset that contains millions of “text-to-image” prompts from Stable Diffusion. In this large dataset, the researchers found that living and deceased artists were frequently mentioned by name. (For the curious, the top three mentioned in this database were: Rutkowski, artgerm [another contemporary artist, born in Hong Kong, residing in Singapore] and Alphonse Mucha [a popular Czech Art Nouveau artist who died in 1939].)

Given that AI users are likely to use artists’ names in their text prompts, the team also conducted experiments to gauge how the results were perceived. Using deep learning models, they found that including an artist’s name in a prompt systematically improves the output’s aesthetic quality and likeability.

The Impact of Artist Compensation on Perceived Worth

Next, the researchers studied consumers’ willingness to pay in various circumstances. The researchers used Midjourney with the following dynamic prompt:

“Create a picture of ⟨subject⟩ in the style of ⟨artist⟩”.

The subjects chosen were the advertising creation known as the Most Interesting Man in the World, the fictional candy tycoon Willy Wonka, and the deceased TV painting instructor Bob Ross (Why not?). The artists cited were Ansel Adams, Frida Kahlo, Alphonse Mucha and Sinichiro Wantabe. The team repeated the experiment with and without artists in various configurations of subjects and styles to find statistically significant patterns. In some, consumers were asked to consider buying t-shirts or wall art. In short, the series of experiments revealed that consumers saw more value in an image when they understood that the artist associated with it would be compensated.

Here’s a sample of imagery AI generated using three subjects names “in the style of Alphonse Mucha.”

Source: Midjourney cited in http://dx.doi.org/10.2139/ssrn.4428509

“I was honestly a bit surprised that people were willing to pay more for a product if they knew the artist would get compensated,” Schweidel explains. “In short, the pay-per-use model really resonates with consumers.” In fact, consumers preferred pay-per-use over a model in which artists received a flat fee in return for being included in AI training data. That is to say, royalties seem like a fairer way to reward the most popular artists in AI. Of course, there’s still much more work to be done to figure out the right amount to pay in each possible case.

What Can We Draw From This?

We’re still in the early days of generative AI, and IP issues abound. Notably, the New York Times announced in December that it is suing OpenAI (the creator of ChatGPT) and Microsoft for copyright infringement. Millions of New York Times articles have been used to train generative AI to inform and improve it.

“The lawsuit by the New York Times could feasibly result in a ruling that these models were built on tainted data. Where would that leave us?” asks Schweidel.

"One thing is clear: we must work to resolve compensation and IP issues. Our research shows that consumers respond positively to fair compensation models. That’s a path for companies to legally leverage these technologies while benefiting creators."

David Schweidel

To adopt generative AI responsibly in the future, businesses should consider three things. First, they should communicate to consumers when artists’ styles are used. Second, they should compensate contributing artists. And third, they should convey these practices to consumers. “And our research indicates that consumers will feel better about that: it’s ethical.”

AI is quickly becoming a topic of regulators, lawmakers and journalists and if you're looking to know more - let us help.

David A. Schweidel, Professor of Marketing, Goizueta Business School at Emory University

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Professor of Marketing & Roberto C. Goizueta Professor in Business Technology

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May 7, 2026

8 min

Expert Insights: Want More Engagement? Eliminate the Barriers.

Anyone born in the 70’s or earlier will probably remember it well. Time was when playing any kind of video game meant physically disporting yourself to the local arcade—a twilight zone of flashing neon, electronic beeps and bops, and the clink of quarters hitting the slot. As technology advanced, the videogame came to you. Home consoles and TV stations rigged with joysticks duly became the mainstay of gaming. The Atari 2600 brought the arcade experience into dens all over the US; Pac-Man, Space Invaders, and Asteroids now at the fingertips of a generation of games who no longer needed to leave home to play. Fast forward to the era of smart phones and hi-tech, and gaming has evolved again. Today, Fortnite, Minecraft, and The Legend of Zelda can accompany you pretty much anywhere—onto a train or a bus, into the canteen at work or school, or under the covers at 2am. In our always-on, on-demand world, video gaming increasingly meets players where they are; a play-anywhere, digital user experience that empowers individuals to engage with their game of choice wherever they are, whenever it suits, and via whatever platform they prefer, desktop or mobile. For users, the benefits seem clear. But what about game producers? As availability expands to new channels and platforms, how does it change user behavior? Does it deepen engagement or does cross-platform continuity simply end up redistributing play—the addition of each new platform shifting players away from, and effectively cannibalizing, existing channels? It’s a conundrum, and not just for video game producers. Retailers, bankers, insurance firms, media, and hospitality providers—anyone with an online-first approach looking to meet their customers wherever they are—should also be cognizant of the potential downsides of channel expansion in the digital space. Weighing in here is research by Professor of Marketing and expert in the intersection of sports and cultural analytics and marketing Michael Lewis. Together with Wooyong Jo of Purdue, Lewis looks at the impact of omni-channel strategy on videogames—a proxy, he says, for other sectors and industries. What they find is critical for marketers and decision-makers in any context or business setting. Increasing the digital touchpoints between your product and customers does impact behavior—but the net results are overwhelmingly positive. Video game players play more, they spend more frequently, and they integrate gameplay more deeply into their everyday lives. In other words, the investment pays off. And the dividends in customer engagement are serious. Switching to the Switch To unpack all of this, Lewis and Jo partnered with a large US video game publisher to analyze player-level behavioral data for one its major titles in the Multiplayer Online Battle Arena, or MOBA genre. Players form teams and compete to destroy opposing team’s bases, selecting a character from a set of 100+ options. Revenue for the publisher comes from a “freemium” business model—users can make voluntary purchases to unlock new characters or buy cosmetic enhancements. These purchases are geared toward enhancing the gaming experience but don’t affect competitive outcomes, making them a critical measure of engagement. In 2019, the game was released for the Nintendo Switch, which can be docked in home consoles but is most commonly used as a mobile, hand-held device. PC players were given the option to download this new version and continue gameplay seamlessly using their existing accounts. Analyzing player behavior before and after the adoption of the new Switch platform, Lewis and Jo were able to zoom in on some critical measures of user engagement including game usage or the total number of matches played, in-game spending—what, when and how much players spent—and player inactivity or churn. “We were able to really get into player behavior over time, and what happens when you introduce the Switch option and remove the constraints of having to play in one place—the home or gaming PC,” says Lewis. “What happens when you make it possible for players to access the game they love while they’re commuting or on their lunchbreak?” Plenty, it turns out. Mobile access: gameplay, spending and churn Crunching the data, Lewis and Jo find that mobile access dramatically increases gameplay. Players who adopted the Switch version played approximately 31% more games than before—a dramatic uptick that underscores how flexibility gains translate into new opportunities to play and engage. And that’s not all. Lewis and Jo also find that gameplay becomes less concentrated within narrow windows—after school or work, say—and is now more spread out across the day, the result of the “ubiquity effect,” says Lewis. “Take away the constraints of having to be in a fixed location and you see players adding additional play sessions. Interestingly though, we don’t find any adverse effect on PC gaming. Players are simply playing more, and playing longer, rather than replacing PC time.” Then there’s in-game purchasing. MOBA-type games typically give players the option to voluntarily buy modifications for characters, known as “skins.” These skins are cosmetic enhancements: new armor, costumes, skill animations or effects. Crucially, these kinds of purchases don’t advance players to new levels of success in the game. Instead, they are used for personalization—to demonstrate status or to celebrate an in-game event. Lewis and Jo find that mobile adopters make more frequent in-game purchases. While the overall total doesn’t increase materially, these players are spending small amounts, more often—almost 7% more frequently than before. This makes intuitive sense, says Lewis. If players are logging in more often, they have more opportunities to feel inspired to want to spend on skins. But there’s another factor that may be at work. “With this kind of in-game purchasing, it’s likely that a lot of it is about credibility. When you buy a skin or a character pack, it’s like you have more aura within the game; you want to signal something to other players and let yourself be known. And this is more than just monetary, it’s about a deeper kind of engagement,” says Lewis. “It’s possible that as mobile access makes the game more of a frequent companion, as the rate of play increases, there’s this effect that players fall deeper into the community—their engagement deepens even more.” Interestingly, the shift to mobile access had the most significant impact precisely on those players whose pre-Switch in-game purchasing was lowest. These users, who were arguably most likely to disengage and drift away from the game, became significantly more active once the hand-held option became available. “If you have players spending less and less inside the game, the intuition is that these are the customers you are most at risk of losing,” says Lewis. “Bringing in the Switch has seen these customers—those more prone to churn—actively reengage with the game, maybe because they have greater propensity for the mobile version.” Either way, this should be a particularly interesting finding for marketers, he adds; retaining existing users is typically cheaper than attracting new ones. “The evidence suggests that mobile access can serve not only as a growth strategy, but also a defensive one if it helps keep marginal users engaged; those who might otherwise have detached from the product altogether.” Help Them Switch So far, so encouraging. There is one potential downside to porting a game or online product to a new channel, however, and that is usability. Lewis and Jo find that players who switched between platforms experience a slight, initial decline in in-game performance—likely because of differences in the control systems between devices. Players who’ve been using keyboard and mouse controls may need time to adapt to hand-held controllers. To mitigate this, he and Jo suggest that producers could offer tutorials or introductory gameplay modes that accelerate the learning curve as users adjust to the new interface. In most cases, usability should be factored in as an additional, hidden cost, when developers and organizations are contemplating investing in more online customer touchpoints. “Expanding your online channels will always have some cost. Taking a game from one platform and porting it to another one isn’t free, so you will want to anticipate the hurdles, even as you weigh up the clear benefits,” says Lewis. “The key is to make sure you protect your users. With things like video games, you want to think about how to guide or upskill your players, maybe have them play bots at first to ramp up their capabilities. Whenever you create a new channel that has a different operating system from the user’s perspective, you’re probably going to want to provide some aid to your fan community.” The benefits of omni-channel access should always be weighted against the costs involved, counsels Lewis. Even so, today’s competitive pressures—the seemingly inexorable march of technological innovation and evolving user expectations—are likely to make platform expansion unavoidable for most online businesses. In the world of video gaming, as major franchises release new products across multiple platforms, and player preferences become more sophisticated, companies may simply have to adopt similar strategies to remain competitive. “As everyone else invests in the same new technologies, you almost have to do the same—just as a matter of doing business,” says Lewis. “If you are launching a video game, you’ve got to compete with whatever Call of Duty or Grand Theft Auto are doing. You can’t just tell your players they can only engage on one platform. The competition is continuously raising the stakes just in terms of the bare minimum.” Building Fandom: the Connective Cultural Tissue More broadly, Lewis and Jo’s findings speak to how human beings form communities of shared passion around business entities and, perhaps more compellingly, around cultural phenomena: video games, for sure, but also sports teams, music, films, comic books, fashion, and more. Understanding the mechanisms that drive and deepen engagement sheds more light on what Lewis calls the “connective cultural tissue of fandom: ”the powerful social bonds, camaraderie, and shared identity that connect people to cultural entities and to each other. Fandom, he argues, is the “key to our world.” Understanding fan behavior is critical to understanding how it is that games, brands, sporting teams, or politics forge communities built on shared passion. “Whatever your organization or business is, you are going to be interested in driving passion. You want people to engage and love what you do. What we’re looking at in this study is a building block towards understanding how cultural entities fit into consumers’ lives, and how eliminating barriers helps to expand communities and drive relationships—extending reach and engagement by weaving cultural experiences more deeply into everyday life.” The real challenge in front of organizations, be they video game producers or online retailers, says Lewis, is to give their product the kind of “cultural meaning” that creates fans—and not just users. “When you think about the behavior of fans, the level of passion and engagement that exists around cultural phenomena—whatever they are from video games to FIFA, the English Football League to the Super Bowl, Taylor Swift to the Republican Party—that’s where you see the passion that really drives the world. And that to me, is critical in understanding how business works, how societies function, and how our world evolves.”

Nov 17, 2025

5 min

12 Days of Holiday Experts - Goizueta Business School Sources for the Season

It's that time of the year again! And as Americans get ready for another journey into the festive season, there are always opportunities for stories to be told about shopping, travelling, buying, returning, and making sure you don't get ripped off or scammed during all the hustle and bustle, Here's a stocking full of topics and expert sources who are here to help with your coverage this holiday! Gifts, Giving, and all the Costs That Come With It Economics of the Holiday Season A successful Q4 makes the difference between annual profitability and loss for many businesses. Professor Tom Smith is available to discuss seasonal hiring, retail expectations, the impact of tariffs, and the importance of the holiday season to retailers. View his profile here Black Friday & Using AI to find the Perfect Gift Professor Doug Bowman expects to see more Shoppers (esp. Gen Z) experimenting with GenAI for personalization, inspiration, product discovery, summarizing reviews, generating lists, and finding deals. Results may be mixed, depending on the data the AI was trained on. He also expects more purposeful and complex shopping, with fewer impulse purchases and more searching (both online and in brick-and-mortar stores), due to lower inventory levels/assortments at some retailers. View his profile here Food and Travel Pricing Professor Saloni Firasta Vastani can discuss the cost of this year’s holiday dinners. What’s gone up and what’s gone down? She can also discuss the cost of travel this holiday season and offer tips on how consumers can secure a better deal. View her profile here Avoiding Holiday Overspend Professor Usha Rackliffe can discuss how holiday shopping can expose consumers to credit products, such as store credit cards, that offer various incentives and often result in overspending. She can discuss the pros and cons of the buy now, pay later offers and how interest rates will play into this year’s holiday shopping and spending. View her profile here Gift Giving Professor Ira Bedzow says there are three ways gift-giving can promote both personal growth and professional development. View his profile here Gifts Express Relationship, Not Reciprocity. Contracts and transactions are about keeping score—I give, you give back. Gifts are about connection. A thoughtful gift doesn’t close a deal; it opens a door. Personally, it reframes love and friendship as ongoing commitments rather than conditional exchanges. Professionally, treating interactions as opportunities to build trust creates loyalty, sparks creativity, and builds a culture no contract can guarantee. The Art of Perspective-Taking in Choosing Gifts: The best gifts come from stepping outside yourself and asking: What would this person really want? This act of empathy is a skill worth practicing. Personally, it pulls us beyond ego; professionally, it sharpens our ability to anticipate needs, see through others’ eyes, and make decisions aligned with their values—a foundation for real leadership. Gifts as Lessons in Friendship and Human Connection: True friendship isn’t built on ideology, convenience, or self-interest. It’s rooted in caring for someone simply for who they are. Gift-giving is a rehearsal for that kind of connection. Personally, it reminds us that what we truly want typically comes through relationships, not rivalry. Professionally, it shows that lasting success rests less on shared advantage and more on genuine respect and human connection. Shopping for Sustainability Consumers are increasingly seeking eco-friendly products, and brands that emphasize sustainability are likely to see higher sales. Nearly 69% of shoppers prefer to buy from companies committed to ethical practices, such as those that use carbon-neutral shipping and offer recyclable packaging. Professor Dionne Nickerson focuses on how companies can integrate sustainability in their products and why it matters to consumers. View her profile here Pressure Purchasing As the days inch closer to the holidays, shoppers feel the pressure to find a gift. Professor Max Gaerth can discuss how stress, scarcity, and time pressure shape purchasing decisions. View his profile here Online Shopping and Influencing AI Changing How We Shop Professor David Schweidel examines how new AI tools are transforming the shopping experience and the ways brands utilize AI to engage with prospective customers and personalize product recommendations. He can also discuss OpenAI’s Atlas and how it puts ChatGPT directly into your browser. View his profile here Influencers Influencing Our Purchases How are creators impacting the economy, and are influencers impacting our purchasing decisions? Professor Marina Cooley looks at the creator economy and how TikTok and Instagram are impacting our holiday wish lists, and what it takes for a product to go from unknown to trending. She can also discuss TikTok Shop (something Instagram has struggled to execute). View her profile here How to Attract Customers to the Store this Holiday: Shopping looks different, and it is up to retailers to stand out not just in the brick-and-mortar world but also online. The success of a business can balance on the customer experience. Professor Reshma Shah can discuss the policies that brick-and-mortar retailers need to have in place to successfully merge online shopping and the in-person shopping experience. View her profile here Holiday Scams Tis The Season for Scams Bad actors are using AI to scam consumers. From phone calls to emails, Professor Tucker Balch can tell us how to spot a scam and what we can do to protect ourselves. View his profile here Holiday Returns Product Returns Professor Doug Bowman can discuss the retail strategy and the impact of holiday gift returns, comparing online returns to those in brick-and-mortar stores. View his profile here He can also weigh in on: Why are returns so expensive for retailers? Online returns vs. brick and mortar returns Predicting online returns - helping retailers understand how likely it is that a product will be returned. As well: Are retailers still offering free returns? What’s this costing them? Is this likely to continue? What will they do differently? If you’re a journalist covering the holiday season, our experts can help shape your story. Use the “Connect” button on any expert’s profile to send an inquiry — all inquiries are monitored by our media team to ensure a quick, timely response.

Sep 19, 2025

6 min

#Expert Perspective: When AI Follows the Rules but Misses the Point

When a team of researchers asked an artificial intelligence system to design a railway network that minimized the risk of train collisions, the AI delivered a surprising solution: Halt all trains entirely. No motion, no crashes. A perfect safety record, technically speaking, but also a total failure of purpose. The system did exactly what it was told, not what was meant. This anecdote, while amusing on the surface, encapsulates a deeper issue confronting corporations, regulators, and courts: What happens when AI faithfully executes an objective but completely misjudges the broader context? In corporate finance and governance, where intentions, responsibilities, and human judgment underpin virtually every action, AI introduces a new kind of agency problem, one not grounded in selfishness, greed, or negligence, but in misalignment. From Human Intent to Machine Misalignment Traditionally, agency problems arise when an agent (say, a CEO or investment manager) pursues goals that deviate from those of the principal (like shareholders or clients). The law provides remedies: fiduciary duties, compensation incentives, oversight mechanisms, disclosure rules. These tools presume that the agent has motives—whether noble or self-serving—that can be influenced, deterred, or punished. But AI systems, especially those that make decisions autonomously, have no inherent intent, no self-interest in the traditional sense, and no capacity to feel gratification or remorse. They are designed to optimize, and they do, often with breathtaking speed, precision, and, occasionally, unintended consequences. This new configuration, where AI acting on behalf of a principal (still human!), gives rise to a contemporary agency dilemma. Known as the alignment problem, it describes situations in which AI follows its assigned objective to the letter but fails to appreciate the principal’s actual intent or broader values. The AI doesn’t resist instructions; it obeys them too well. It doesn’t “cheat,” but sometimes it wins in ways we wish it wouldn’t. When Obedience Becomes a Liability In corporate settings, such problems are more than philosophical. Imagine a firm deploying AI to execute stock buybacks based on a mix of market data, price signals, and sentiment analysis. The AI might identify ideal moments to repurchase shares, saving the company money and boosting share value. But in the process, it may mimic patterns that look indistinguishable from insider trading. Not because anyone programmed it to cheat, but because it found that those actions maximized returns under the constraints it was given. The firm may find itself facing regulatory scrutiny, public backlash, or unintended market disruption, again not because of any individual’s intent, but because the system exploited gaps in its design. This is particularly troubling in areas of law where intent is foundational. In securities regulation, fraud, market manipulation, and other violations typically require a showing of mental state: scienter, mens rea, or at least recklessness. Take spoofing, where an agent places bids or offers with the intent to cancel them to manipulate market prices or to create an illusion of liquidity. Under the Dodd-Frank Act, this is a crime if done with intent to deceive. But AI, especially those using reinforcement learning (RL), can arrive at similar strategies independently. In simulation studies, RL agents have learned that placing and quickly canceling orders can move prices in a favorable direction. They weren’t instructed to deceive; they simply learned that it worked. The Challenge of AI Accountability What makes this even more vexing is the opacity of modern AI systems. Many of them, especially deep learning models, operate as black boxes. Their decisions are statistically derived from vast quantities of data and millions of parameters, but they lack interpretable logic. When an AI system recommends laying off staff, reallocating capital, or delaying payments to suppliers, it may be impossible to trace precisely how it arrived at that recommendation, or whether it considered all factors. Traditional accountability tools—audits, testimony, discovery—are ill-suited to black box decision-making. In corporate governance, where transparency and justification are central to legitimacy, this raises the stakes. Executives, boards, and regulators are accustomed to probing not just what decision was made, but also why. Did the compensation plan reward long-term growth or short-term accounting games? Did the investment reflect prudent risk management or reckless speculation? These inquiries depend on narrative, evidence, and ultimately the ability to assign or deny responsibility. AI short-circuits that process by operating without human-like deliberation. The challenge isn’t just about finding someone to blame. It’s about whether we can design systems that embed accountability before things go wrong. One emerging approach is to shift from intent-based to outcome-based liability. If an AI system causes harm that could arise with certain probability, even without malicious design, the firm or developer might still be held responsible. This mirrors concepts from product liability law, where strict liability can attach regardless of intent if a product is unreasonably dangerous. In the AI context, such a framework would encourage companies to stress-test their models, simulate edge cases, and incorporate safety buffers, not unlike how banks test their balance sheets under hypothetical economic shocks. There is also a growing consensus that we need mandatory interpretability standards for certain high-stakes AI systems, including those used in corporate finance. Developers should be required to document reward functions, decision constraints, and training environments. These document trails would not only assist regulators and courts in assigning responsibility after the fact, but also enable internal compliance and risk teams to anticipate potential failures. Moreover, behavioral “stress tests” that are analogous to those used in financial regulation could be used to simulate how AI systems behave under varied scenarios, including those involving regulatory ambiguity or data anomalies. Smarter Systems Need Smarter Oversight Still, technical fixes alone will not suffice. Corporate governance must evolve toward hybrid decision-making models that blend AI’s analytical power with human judgment and ethical oversight. AI can flag risks, detect anomalies, and optimize processes, but it cannot weigh tradeoffs involving reputation, fairness, or long-term strategy. In moments of crisis or ambiguity, human intervention remains indispensable. For example, an AI agent might recommend renegotiating thousands of contracts to reduce costs during a recession. But only humans can assess whether such actions would erode long-term supplier relationships, trigger litigation, or harm the company’s brand. There’s also a need for clearer regulatory definitions to reduce ambiguity in how AI-driven behaviors are assessed. For example, what precisely constitutes spoofing when the actor is an algorithm with no subjective intent? How do we distinguish aggressive but legal arbitrage from manipulative behavior? If multiple AI systems, trained on similar data, converge on strategies that resemble collusion without ever “agreeing” or “coordination,” do antitrust laws apply? Policymakers face a delicate balance: Overly rigid rules may stifle innovation, while lax standards may open the door to abuse. One promising direction is to standardize governance practices across jurisdictions and sectors, especially where AI deployment crosses borders. A global AI system could affect markets in dozens of countries simultaneously. Without coordination, firms will gravitate toward jurisdictions with the least oversight, creating a regulatory race to the bottom. Several international efforts are already underway to address this. The 2025 International Scientific Report on the Safety of Advanced AI called for harmonized rules around interpretability, accountability, and human oversight in critical applications. While much work remains, such frameworks represent an important step toward embedding legal responsibility into the design and deployment of AI systems. The future of corporate governance will depend not just on aligning incentives, but also on aligning machines with human values. That means redesigning contracts, liability frameworks, and oversight mechanisms to reflect this new reality. And above all, it means accepting that doing exactly what we say is not always the same as doing what we mean Looking to know more or connect with Wei Jiang, Goizueta Business School’s vice dean for faculty and research and Charles Howard Candler Professor of Finance. Simply click on her icon now to arrange an interview or time to talk today.