At The Paley Center last week, former Disney CEO Michael Eisner framed this crossroads as a familiar pattern in Hollywood. Media companies “possess enormously valuable IP”, but also consistently misjudge how or whether to extend it into unfamiliar formats. His talk focused on Hollywood’s long, troubled history with entering the gaming industry: “The problem wasn’t creative, he argued — it was technological illiteracy: gaming ‘was so technologically driven in the beginning, which was not the strong suit of any of us.’”

This problem of technological illiteracy still persists between Hollywood and gaming. A gaming executive told me in 2023 that it is a generational problem: “They aren’t gamers” (something Eisner appears to have indirectly acknowledged).

Eisner did not discuss generative AI, but the new medium is as “technologically driven in the beginning” as gaming was in the 1980s. The emerging technology is rapidly upending traditional processes and business models for content production, distribution and the legal protections for intellectual property. For this reason, it is harder for anyone to identify when to license IP versus when to build.

He did discuss Warner Communications’ failure with Atari—it purchased the video console owner in 1976, and had success until it reacted to competitive pressures from home computers by oversaturing the market with video game titles. That contributed to the video game console market crashing in 1983. Eisner’s point was that because Warner management had no background in gaming, it made product decisions that did not reach sales expectations. Disney had a similar experience with gaming under Eisner’s successor Robert Iger with Disney Interactive Studios, which lost $200 million per year from 2008 to 2012 and had already begun licensing to third-party publishers like Electronic Arts by the time it shut the division down in 2016.

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Yesterday’s multi-year strategic alliance between Kraft Heinz Company and The Walt Disney Company—which “spans foodservice, media, events and more”—seems straightforward.

Kraft Heinz will be the exclusive provider of cream cheese, some condiments and macaroni and cheese at Disney’s North American parks and resorts, and on the Disney Cruise Line. It will be able to use Disney’s characters and stories across 10 of the food company’s brands, including Heinz, Philadelphia and Kraft Mac & Cheese.

As for the “more”, this deal also “unlocks opportunities for integrated marketing campaigns, digital content and brand-led marketing campaigns across Disney’s media platforms.” It is not core to the deal, but as phrased, it opens the door to experimentation in the marketing space.

These two elements of the deal mirror two recent themes.

First, the licensing of Disney’s characters and stories echoes the “INVERSION” strategy being touted by People, Inc. Chairman Barry Diller—a bet on products and services “birthed out” of its “enormous reservoir of content”. Diller aims to own the branded products instead of licensing, but the business logic is effectively the same: Brand equity from popular IP with existing fan bases translates into product demand.

Unlike People, Inc., Disney is able to find win-win scenarios with giant CPG companies like Heinz because of its extraordinary theme parks business model ($10 billion in operating income in 2025) and broader fan bases for its IP. By comparison, People, Inc. has much less leverage.

Second, the integrated marketing deal heads in the direction of where I believe generative AI advertising is headed.

In April, I wrote an essay about how Nielsen’s The Gauge is “broken” and how “the traditional media value chain—produce content, attract audiences, sell advertising against those audiences, measure with Nielsen—is collapsing at each node.”

I cited an essay from Secret Level founder Jason Zada. It argued that brands are now learning to develop original IP, put it in front of an audience, learn in real time and iterate, the same way a tech company ships and improves a product, rather than betting everything on one expensive, slow-moving campaign.

Kraft Heinz is partially doing that in this deal, but is renting Disney’s IP and audience to “learn in real time and iterate”. Zada adds, “The fear of the big swing gets a lot smaller when you can take fifty fast swings first, each one more informed than the last.”

I also argued in April that Netflix’s ad inventory is increasingly worth more than its streaming content. The same logic applies here. “Integrated marketing campaigns, digital content and brand-led marketing campaigns across Disney’s media platforms” enable Kraft Heinz to take many “fast swings” within Disney’s ecosystem and with Disney’s customers.

The upside for Disney is that it reaps the benefits from the licensing deal—We do not know the terms of the deal, particularly whether the licensing revenues are tiered based on success parameters. The downside really depends on the generative AI and branding savvy of Kraft Heinz.

I wrote in May that “All roads of the [conversion] funnel lead to a sale. The economics are obvious to all parties, production cost savings from generative AI are real and brands have every incentive to adopt.” So if Kraft Heinz has generative AI and branding savvy, we will see these ads within the next year. If it doesn’t, that will confirm this is a traditional licensing deal from risk-averse executives, and reveal just how far behind these two giant companies are in the AI marketplace.

On its surface, the deal seems quite traditional. But it will be worth keeping an eye on what the two companies do together around marketing.

Disney’s deal with Sora—which collapsed when OpenAI abruptly killed it for reasons unrelated to the deal—signaled its openness to third parties creating videos using its characters. It is opening a similar door for Kraft Heinz to do so. We are not far from AI-generated ads pairing Disney characters with Heinz ketchup.

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Co-CEO Greg Peters explained to investors on the earnings why that story has evolved:

“[W]hen I started about 20 years ago, we had one number to describe engagement, hours, just flat hours, no weighting, no adjustments and very similar to how we’ve evolved other metrics in the business. Since then, we’ve gone through about a dozen major iterations of our understanding that.

We get more and more sophisticated because we know, ultimately, it’s combined quality, variety and quantity of engagement that translates into satisfaction and value for members.”

Technology companies like Apple have ditched their vanity metrics when unit sales became disconnected from the actual profit engine, so this pattern is not unusual on its own. But subscription revenue is price times subscriber count—there is no abstraction layer between them the way there is for Apple's unit sales.

Peters’ answer is a wordy concession that Netflix has lost the simplicity of its subscriber and advertising engagement story. In the past, growth was told through subscriber growth. Engagement was told through various reports and Top 10 lists. Its decisions to stop releasing subscriber numbers and to reduce the releases of “What We Watched” to once per year concede that it cannot tell either of these stories anymore.

It does not have an alternative story for investors yet—it relies on a financial story about profit—and they have reacted logically: Its stock price is down 8.4% since the earnings call.

Netflix has long set the market standard for the storytelling of growth in streaming. It is worth asking in the flux that Peters describes: What if they not only do not have a story now, but have lost the story of the media and entertainment marketplace altogether?

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“The premise is that if management cannot optimize shareholder value across unrelated assets, then they should either discard those assets or find managers who do understand how to connect them in ways that audiences want.”

The “point” of “portfolio reconstruction” is “not only that the corporate structure of cable bundles no longer matters. It is that the entire corporate entity needs to be rethought.”

Comcast is now pursuing its version of portfolio reconstruction. First, on January 2nd it spun off some cable networks into Versant. The recently announced spin-off of NBCUniversal was its second move. It was the first explicit admission by a large legacy media company that bundling scale-driven and IP-driven businesses under one roof cannot create value in the AI era.

There will soon be three different business models solving three problems related in origin but increasingly unrelated in practice. The paths forward for Versant and Comcast are straightforward: the former can ride out the slow but profitable decline of cable and the latter is a broadband, wireless and entertainment platforms business serving more than 65 million homes and businesses.

Two weeks ago I argued that the best path forward for NBCUniversal is its own version of “portfolio reconstruction”: It should pursue a partnership with a cloud company. This would enable NBCUniversal to license its IP to generative AI users via subscription or per use fees, and also to brands and merchandisers that can quickly produce new long-tail ideas from its library of IP. It also would emulate the Ellison family’s model for Paramount Skydance and Oracle Cloud Infrastructure, but at a smaller scale and without the family control.

A post on X yesterday from Microsoft CEO Satya Nadella directly challenged this recommendation: “In the AI age, the buyer risks giving away knowledge, just in order to use what they bought.”

He adds: “You essentially pay for intelligence twice, once with money, and again with something even more valuable: the proprietary knowledge you must reveal to make that intelligence useful. The better you want the model to perform, the more of that knowledge you have to feed it!”

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As longtime subscribers may recall, my rule is try not to publish when on holiday unless something newsworthy happens. The news of the Comcast split hits on a few recent themes so I am sending an abridged version for my paid subscribers below.]

On Monday Comcast announced that it plans to separate NBCUniversal and Sky from its connectivity (Cable, Broadband, Mobile) businesses.

Comcast Co-CEO Mike Cavanagh told investors that there was no longer a strategic rationale for its “flywheel” model across Cable, Theatrical and Theme Parks: “where previously we believed that the scale and diversification benefits warranted operating these businesses as one company, we now have simply changed our mind about that.”

In a separate memo to employees, he outlined an aggressive vision to “play offense and move with urgency”: “With a strong balance sheet and a public company stock, we will have the resources and flexibility to pursue the growth opportunities we believe in most.”

The not-so-subtle is that a Comcast as large media company no longer can extract marginal value from a library of IP. So, NBCU will pursue traditional paths of mergers and acquisitions to grow the business. But in this market where the value of IP is being aggressively re-imagined by Bollywood, Paramount Skydance and 1.2 billion people using the internet for the first time, what should Comcast do?

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A24 partner and A24 Labs leader Scott Belsky (the former Chief Product Officer of Adobe) told The Wall Street Journal that the objective is “better uses [of AI] that preserve creative control and support risk-taking.” He added that the new tools “won’t look anything like the prompted generation type of AI that people feel uncomfortable with.”

But the most notable detail for our purposes is this sentence: “Their multiyear, nonexclusive deal doesn’t give Google access to A24’s data, including its film and television library.” Instead, it is a bet that the studio’s roster of artists and auteurs will gravitate towards the tools.

A24 is known more for “arthouse gems” than blockbuster IP—so this detail makes sense. Also, A24’s recent success with YouTube creator Kane Parsons’ horror movie “Backrooms”—which just had the biggest opening in A24 history at $81.4 million on a $10 million budget—is also on the vanguard of “Internet Collaborative IP“. It understands that a next generation of storytelling is emerging from creators working with their audiences to build and improve stories.

The article reads like Google making a conservative bet on something Runway CEO Cristóbal Valenzuela recently described as a “Cambrian explosion of creativity, weirdness, new media, and new forms of expression and art” that is “just around the corner.” However, when viewed through the lens of “Internet Collaborative IP”, the deal establishes Google in this emerging marketplace for both generative AI and Hollywood: Google’s YouTube is a core engine of ideation, community and distribution of “Internet Collaborative IP” before a studio acquires the IP; and DeepMind now has tools within the studio’s pre-production side and the production processes.

With A24, Google is building the early stages of a seamless path from YouTube to theatrical distribution for content created by YouTubers like Parsons, Curry Barker (“Obsession”) and Markiplier (“Iron Lung”) and generative AI creators. That pipeline effectively looks like:

Creator → YouTube → Community → IP → Studio → Production Tools → Theatrical → Paid Downloads (YouTube) and/or Subscription Streaming (Netflix)

In this model, Google has a role in everything but the last two stages—and the real “meat” lies in the first three stages.1 It is worth noting it enables paid downloads of YouTubers’ movies in post-theatrical windows instead of subscription streaming.

Looking at this chain, we can immediately see the problem for both traditional streamers and Netflix: Together, Google and A24 will capture more value across the chain. Netflix and other streamers who buy A24 movies and TV shows will be left waiting for the “scraps” of streaming distribution.

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Last week’s essay on Lionsgate’s deal with Runway concluded:

What does it cost risk-averse executives to truly take on risk? Bollywood’s answer is: far more than they are imagining now.

I had a few conversations and exchanges over the past week that left me thinking my focus on Hollywood is understating the magnitude of this challenge. That if we look at the future of AI in Hollywood from the outside in—like what is happening in Bollywood or through the lens of the Disney v Minimax lawsuit—the industry will never move fast enough to catch up.

The business culture was built to create and support TV and movies for an incredible once-in-a-lifetime profitable business model (cable at 40% EBITDA margins and broadcast at 20%) and a hit-driven model (theatrical at 3% to 6% operating margins) built for passive viewing. Streaming emerged as a medium for interactive viewing. The most successful and profitable once-in-a-lifetime profitable business model has emerged on interactive platforms Netflix (67% EBITDA margins)—but not on YouTube (estimated to have “mediocre” margins), while their legacy media company streaming competition are either losing money or barely breaking even (Disney at 5% operating margins for streaming).

The obvious question for any corporation is where to find additional profits as the cable industry declines and theatrical struggles to recapture COVID-era attendance.

Generative AI enters that equation in two ways: Replacing existing cost-centers like traditional visual effects (VFX) or replacing live productions altogether. The former has been happening in Hollywood since 2023, where ~75% of entertainment industry executives were already using AI to remove, reduce, or consolidate jobs. More recently, Netflix bought Ben Affleck’s AI studio InterPositive “to accelerate the use of artificial intelligence in its filmmaking”.

Netflix’s last engagement report is the missing piece that explains the significance of these moves. Its What We Watched in H2 2025 showed total hours viewed in the second half of 2025 increased by only 2 percent. Research firm MoffettNathanson estimates that Netflix’s global user base grew by 10 percent last year, “which translates to an 8 percent decline in daily engagement per subscriber.“

Both that acquisition and the Lionsgate-Runway partnership prove that Hollywood can buy AI capabilities. However, the recent guild negotiations have proven that its core participants will never be unethical or shameless enough to compete with AI studios and corporations from countries like India, China who do not protect copyrighted materials in AI or lean towards embracing AI technology over traditional forms of human creativity. In Singapore, a 2021 Copyright Act explicitly allows commercial AI training on copyrighted content in a way that U.S. and EU law does not.

The owners of studios want and need to find more profitable business models, especially in online media. Rapid subscriber growth normally delivers less engaged consumers—but an 8-point gap between hours growth and subscriber growth suggests something more structural for Netflix—paying subscribers are finding alternative sources of entertainment. A drop in engagement is the opposite of what a platform increasingly relying on ads needs to convey to the marketplace.

As I wrote in March, Netflix now has plenty of competition from both emerging generative AI apps like ChatGPT and Claude, and especially vertical video streaming:

“The challenge for Netflix is not only that this new format is competitive with the 27-year-old incumbent in such a short period of time, but that its weekly and monthly spend suggests consumers value the new format more.”

This is a signal that there is a substitution underway and being accelerated by the 1.2 billion new users who gain access to the internet between 2022 and the end of 2026. Those two signals point to the deeper challenge: Hollywood is moving too slowly, and not relative to Bollywood’s or generative AI’s production costs.

Instead, it is racing against the rapidly evolving attention habits of an audience that has not yet decided what “good enough” means—and is making that decision with less and less Hollywood content in the room. Buying AI capability inside a guild-constrained culture for long-form content seems to be an insufficient solution for rapidly changing audience preferences around storytelling.

From Passive Viewing to Internet Collaborative IP Storytelling Models

What to do instead?

Obvious signs point to vertical video and generative AI as alternative content formats to be embraced as the 1.2 billion increasingly consume storytelling within them. Hollywood studios appear more eager to embrace the former than the latter.

“Internet collaborative IP”—which I wrote about earlier this month—appears to be a more viable solution. It is “IP that is for the people by the people… an interactive story that was built over time that you feel a part of if you were there which makes you want to go and see it and celebrate it because the people made the story.”

The approach marries both the interactivity of online storytelling consumption and the passive consumption of theatrical. It suggests the answer is not for studios to produce long-form content faster or cheaper with AI across televisions and movie theater screens. Instead, it is to rapidly embrace content formats the 1.2 billion are already choosing and to do it before their habits calcify into something Hollywood had no hand in shaping.

To date, we have only seen three movies from YouTubers— “Iron Lung”, “Backrooms” and “Obsession”—emerge and succeed at the box office. That seems likely to grow before any of the guilds shift their embrace of AI. That is because for studios, the corporations that own them and the guilds that have contracts with them, the production budgets can be extraordinarily low (budgets for “Obsession” and “Iron Lung” were both under $1 million) and human creativity can be both protected and thriving.

AS I previously argued in both “Make Ads or Make Stories” and “Bottlenecks and The Greenlight Gap, advertising is the only path where the economics for both creators and distributors make sense in a marketplace where generative AI scales. There is a second solution—one that involves brands, advertising and content partnerships—which I will take up in a future essay.

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There is an obvious streaming angle to this—Fox has already had success with the free, ad-supported platform Tubi. It surpassed $1 billion in revenue for the first time in FY 2025 and now comprises 23% of Fox’s total advertising business. According to Nielsen’s most recent The Gauge, it is the second most-watched free-streaming service in the U.S., behind only The Roku Channel. Acquiring Roku is doubling-down on that business and boosting Fox’s share of U.S. TV consumption by platform from 2.2% to 5.2%, which would equal Disney’s current share across three apps and compete for third place behind Netflix.

There is also an obvious U.S. advertising angle to this: Combining Roku with Fox’s broadcast and cable networks—and Tubi—would give them the third-largest share of U.S. television viewership by distributor(10.2% as of March 2026), behind only Disney (10.6%) and YouTube (13.2%). Fox will be able to offer advertisers competitive scale and sophisticated ad-targeting.

There is a less obvious generative AI marketplace angle to this. For the past two years I have been researching and analyzing how and why AI restructures who captures value in entertainment. My answer has been: whoever owns both the content and the infrastructure (The Ellisons controlling Paramount Skydance and Oracle, Amazon owning MGM Studios). Fox will own two key points of infrastructure:

1. 100 million connected TV households worldwide using a Roku streaming player, a first-party Roku-made TV, or “one of the many Roku TV models built by” its global hardware partners

2. Roku’s advertising platform and Operating System which enables them to capture revenues from digital advertising and distribution of third-party streaming services

But what business will a combined Fox and Roku be in when the streaming model is hitting headwinds, and generative AI creators are more incentivized to produce content for consumers via advertising than original content?

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Recent conversations with people in Hollywood point to a shift in mentality towards AI from both studios and guilds. Some highlighted the upcoming IPOs for OpenAI and Anthropic as making AI seem less abstract and more an inevitable reality. Some pointed to few, if any, signs of vitriol between studios and guilds in the current negotiations. All suggested that various mindsets of fear and resistance I heard in conversations as recently as six months ago were disappearing.

Similar signals of a thaw, if not a vibe shift, have emerged in the past few days. Lionsgate announced yesterday it is taking an equity stake in Runway, the generative AI video company. It expands on a partnership launched in 2024. The deal includes using Lionsgate’ existing catalogue of intellectual property for an AI short-form series and starting a new development program to create new intellectual property using AI.

I previously wrote about Runway’s partnership with Lionsgate last year and then again in February about the range of “unforeseen complications” that emerged: The “limited capabilities that come from using just Runway’s AI model” and “copyright concerns over Lionsgate’s own library and the potential ancillary rights of actors”.

This deal seems to solve for both: Short-form series appears to be a business opportunity that avoids the challenges encountered incorporating Runway into pre-production. New IP obviates the thorny questions around copyright and compensating rightsholders of old IP (in theory).

Risk-Taking

This deal is emerging both against the contrasting backdrops of the guild negotiations and Bollywood’s aggressive embrace of AI. Through the lens of the former, it reads like aggressive and possibly transgressive risk-taking —the possible use of existing franchises and characters will create inevitable exposure to public-backlash around labor, likeness, authorship and intellectual property. It will also be subject to the final version of SAG-AFTRA’s ​​12 basic ground rules for the use of digital replicas in its tentative agreement with AMPTP.

Through the lens of the constraint-free “Wild West” of Bollywood, the deal seems like a half-measure. A smaller, traditional studio is embracing AI for short-form content and new IP, only. The partnership is built to aggressively use AI to push new movies into theaters, revise old ones or create movies based on public domain IP like mythology or The Bible.

Disney Precedent

In some ways the Lionsgate-Runway deal echoes Disney’s abruptly-cancelled deal with OpenAI. Last December, Disney and OpenAI announced a surprise three-year licensing agreement: Disney would license 200+ characters to OpenAI’s Sora platform, invest $1 billion and become a “major customer” of OpenAI’s APIs “to build new products, tools, and experiences” Depending on who you asked, that deal was perceived as Disney taking a significant risk, or as I argued, securing the optics of a significant risk but really investing in operational cost efficiencies. Now that the deal is dead, Disney never got to answer that question.

Runway recently raised $315 million in Series E funding at a $5.3 billion valuation to “pre-train the next generation of world models and bring them to new products and industries.” Lionsgate is sending a similar message to shareholders that Disney did: Whatever the perceived costs or risks of AI may be to the creative industry, shareholders will see inevitable financial upside from a legacy media company hitching its wagon to a fast-growing AI platform.

But Is This Enough Risk?

The Eros recut of a 2013 hit movie “Raanjhanaa” proved that Both theatergoers and 958 million active internet users in India are increasingly forming their entertainment expectations around AI-generated content. Hollywood and Bollywood compete for the same customers on the same digital platforms. A creator at the Artist & The Machine Summit framed it best: Asia and Africa are leveraging AI to change the scale and speed at which content is being produced and monetized. With hundreds of millions more arriving online across Africa and other territories getting internet access for the first time, this means a conservative solution that works for the Hollywood ecosystem will struggle to compete globally.

More risk must be assumed by a Lionsgate and Runway partnership to produce content faster and cheaper in order to compete in a global marketplace. Monday’s essay suggested that the model also needs to be “internet collaborative IP”, which is “IP that is for the people by the people essentially. It is an interactive story that was built over time that you feel a part of if you were there which makes you want to go and see it and celebrate it because the people made the story.”

That model is the antithesis of a studio model. It is more like a creator model. It captures the human creative collective that has built Hollywood. It is also its antithesis—audience input eliminates the need for a team of “expert” creatives driving the creative. That makes the model cheaper.

Instead, Lionsgate and Runway seem to be taking the traditional studio approach to AI. It is a studio that thinks short-form AI content and new IP with a hot AI platform counts as risk-taking. That contrasts with the Bollywood ecosystem where the entire production model is being reimagined and restructured.

This raises a difficult question: What does it cost risk-averse executives to truly take on risk? Bollywood’s answer is: far more than they are imagining now.

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Collectively, both are grossing more than Disney’s “Star Wars: The Mandalorian and Grogu”, which has earned $145 million worldwide on its opening weekend and $294 million since May 22—and on a budget of $165 million.

There are obvious explanations for the financial success of the films: production studios like Focus Features—which distributed “Obsession”—Blumhouse—an executive producer on “Obsession”—and A24—which produced “Backrooms”—are revolutionizing the horror genre both creatively and financially. Horror’s popularity as a genre partially explains these box office successes.

The deeper story here is that YouTubers have individually and collectively outperformed a major studio’s IP juggernaut. The broad brushstrokes of that story map to my argument that the new media marketplace is “more McLuhan than Christensen”: the invisible “groundrules [sic], pervasive structures and overall patterns” of the internet empower creators to have a more interactive relationship with their consumers.

But theater screens are not interactive like a touchscreen or keyboard—they are physical spaces outside of and not contained by Google’s vertical ecosystem. There is only one previous instance of a YouTuber finding success in theaters: In January, Markiplier released his adaptation of the video game “Iron Lung” and grossed $50 million worldwide on a budget of $3 million.

A clearer answer emerged over the weekend from YouTube creators Colin & Samir. They published a video that pinned the success of “Obsession” and “Backrooms” on what they called “internet collaborative IP”:

“This is a story that is built by this generation. It is not IP like Star Wars or Jurassic Park or Spider-Man that is already pre-existing and that the studios are telling us we should go and see. It is IP that is for the people by the people essentially. It is an interactive story that was built over time that you feel a part of if you were there which makes you want to go and see it and celebrate it because the people made the story.”

Their broader point is that “ for all of the conversation about how Hollywood is dying, sure Hollywood is not the same that it was, but it’s [not] dying. [I]t’s just going through an evolution”. An emerging calculus of community interactivity and “great storytelling” is key to the evolution, and that was also a key theme to last week’s stories.

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Earlier this week I had dinner with a subscriber who suggested I look at Amazon’s announcement last week at “AI on the Lot” through the lens of the pre-Paramount decrees studio system.

In the 1930s and 1940s, the “Big Five” Hollywood studios were vertically integrated across production, distribution and exhibition. An antitrust ruling from the Supreme Court in 1948’s United States v. Paramount Pictures, Inc. forced the studios to sell off their theater chains and also outlawed additional anticompetitive tactics with independent theaters. In 2020, U.S. District Court Judge Analisa Torres ended the decrees in response to the U.S. government’s request to do so. She noted:

“In today’s landscape, although there may be some geographic areas with only a single one-screen theater, most markets have multiple movie theaters with multiple screens simultaneously showing multiple movies from multiple distributors. There also are many other movie distribution platforms, like television, the internet and DVDs, that did not exist in the 1930s and 40s.”

Studios used to control what audiences saw, when they saw it and where—that is no longer true in today’s diverse entertainment marketplace. Past licensing tactics—like block booking, circuit dealing, and resale price maintenance—would be analyzed in modern antitrust law under the rule of reason: “evaluating the specific market facts to determine whether a practice’s anticompetitive harm outweighs its procompetitive benefits.”

The conventional response to Amazon’s announcement is to quote Clayton Christensen’s disruption theory—new technology enables new vertical integration, and integrated players win early markets. The logic behind Torres’ ruling—that the technological constraints around distribution had transformed the market—is Marshall McLuhan’s “the medium is the message” in legalese. Amazon’s announcement at AI on the Lot, Paramount Skydance’s partnership with Oracle and Google’s Veo 3-to-YouTube-Shorts pipeline all suggest that within only six years, the technological constraints around entertainment distribution had changed exponentially again.

Torres’ analysis already seems outdated.

Vertical Integration in AI

Last December I wrote about the generative AI marketplace (diagram above), where the Ellisons control both content and infrastructure. Amazon enjoys similar vertical integration with MGM Studios and AWS. At AI on the Lot it outlined how its studio, generative AI tools and cloud infrastructure could support animation projects from “people who are leaning into [generative AI] or curious.” There were two other implicit parts to Amazon’s vertical integration pitch: Over 200 million Prime Video subscribers worldwide and “almost 300 million” Fire TV devices “purchased around the world”.

Vertical Integration But No Hardware

Paramount Skydance—via its partnership with Oracle and likely merger with Warner Bros. Discovery—will have similar vertical integration: Paramount and Warner Bros. IP, Oracle’s AI tools, Oracle’s Cloud Infrastructure and distribution via streaming and cable and broadcast networks. However, they will lack the hardware distribution end point.

Vertical Integration But No IP

Google is in a similar position with Gemini (Veo), Google Cloud, YouTube and 300 million active Google TV devices worldwide. Meta has the generative AI tools, proprietary cloud infrastructure, its Family of Apps (Facebook, Instagram, Messenger and WhatsApp) and hardware devices (Meta Quest, Meta Glasses). But both lack the proprietary IP of Paramount Skydance and Amazon’s MGM.

IP and Streaming But No Integration

Netflix owns IP and streaming, but owns no cloud of its own (it runs on AWS) and no hardware (it transferred an internal streaming device project to Roku in 2008 rather than launch it as its own product.). The question is what it will do to remain the dominant global subscription streaming service. It could be the exception that tests the rule, or an example of how full-stack integration is not the only path to market power. There are more emerging market signals it is moving in the direction of generative AI content, suggesting something will have to change.

The New Vertical Integration

The generative AI marketplace is in the early stages of a new wave of disruption and the key players are in the early stages of new versions of vertical integration. Those that can assemble a full stack will occupy the position the pre-Decrees studios held. Because this new vertical integration will exist across new technologies that are different from traditional theatrical distribution, it is not simply a reconstitution of the old one.

The pre-Paramount Decrees studios controlled what audiences saw, when they saw it and where. The new integrated companies have more far-reaching control—the cloud infrastructure that hosts the training data and the content, the AI pipeline that generates new content with studio IP, the algorithm that selects the content for the user and the device that delivers it. The constraints are mostly invisible, embedded in the medium itself.

Because these models are global, the new vertical integration may be more pervasive than theater ownership ever was. It operates through technological constraints that courts are being forced to understand and IP laws which vary depending on region and/or territory. That also implies that antitrust law will struggle to regulate this.

The old integration controlled access to exhibition. The new integration controls access to IP at the generation layer. That is not more pervasive in the theatrical sense. It is more foundational.

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A few greenlit projects were announced, including three original series, one of which was “Punky Duck” from “Maya and the Three” and “The Book of Life” director Jorge Gutierrez. Two days later, Gutierrez announced on X that he had “decided to drop out of the AI program at Amazon” and “will not be making a Punky Duck series”. The impetus was concerns from his community about “using AI to assist an animation pipeline”.

Another of the three was “Cupcake & Friends” from Buzzfeed Studios, which is based on its “Good Advice Cupcake” series starring Loryn Brantz. That same day Brantz responded to the announcement on Instagram: “The news that this character, who is based on my own personality and whom I created as a microphone to spread love and positivity, has been taken and turned into a soulless AI puppet feels like having my intestines pulled out of my body.”

Both stories confirm two of my takeaways from Artist & The Machine’s NY Summit. First, creators are starting to make AI deals—I had heard about Netflix deals but now we see Amazon’s MGM Studios is a player, too—and the first wave of deals is emerging. However, the backlash to Amazon’s announcement suggests we are still very much within the uncertainty of a market coordination failure: Every constituency holds a piece of the picture but no constituency can see the whole board.

Amazon holds a few pieces—a studio, generative tools and the cloud infrastructure to back generative AI content. However, its bet that this market position could succeed in a marketplace suffering from coordination failure now appears to have been partially wrong.

So now what?

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Today, YouTube announced two updates to its disclosure policies for AI content that advance both of these arguments. First, AI disclosure labels move to a more prominent position: below the video player for long-form content and as an overlay for Shorts.

Second, and more significant, YouTube is rolling out automatic AI detection. If a creator does not disclose that they used AI but YouTube’s systems “detect significant photorealistic AI use,” YouTube will now apply the label itself.

It also asserted its market power to regulate AI content via Veo and Google Cloud. It stated disclosures will remain permanent in “a handful of cases”, including:

• Content created using YouTube’s own AI tools, like Veo or Dream Screen.

• Content containing (the Coalition for Content Provenance and Authenticity (C2PA) metadata—an open standard for content origin and authenticity—indicating they were fully generative AI.

This assertion of regulatory power is the real story.

Past essays related to today’s analysis:

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SAG-AFTRA recently released to its members the terms of its tentative agreement with AMPTP. Last week SAG-AFTRA’s board recommended that its members approve the agreement.

The agreement reflects openness to the use of AI likenesses, which is a stark contrast to SAG-AFTRA’s four-month strike back in 2023. It builds upon established consent-based frameworks for digital replicas from the 2023 deal that ended the strike.

I previously wrote in “Why SAG’s ‘Tilly Tax’ Falls Short of Bollywood’s AI Future” that the business rationales for the old Hollywood production playbooks are “steadily eroding”. By contrast, Bollywood’s aggressive embrace of new AI-driven playbooks has created “new sources of revenue with more cost effective models.” That aggressiveness included a studio using AI to re-cut a 2013 hit movie “Raanjhanaa” over the lead actor’s public objection.

I argued that:

“Hollywood needs to follow Bollywood’s lead and experiment with those to figure out its future. That is going to involve choices that have been anathema to actors, directors and writers. There are no sacred cows anymore—except for the canon of popular IP (e.g., “Star Wars”).”

This new agreement opens the door to some Bollywood-levels of risk-taking, but it also closes others.

Closed Doors

SAG-AFTRA had proposed a “Tilly Tax”, a fee named after the “first” AI actor in Hollywood which studios would have to pay to the union in exchange for using a commercially deployed, fully synthetic AI character with no underlying human performer.

The agreement SAG-AFTRA actually reached is more nuanced and sophisticated than the “Tilly Tax” would have been. Section 39 sets 12 basic ground rules for the use of digital replicas. It is built upon a guiding principle of “acknowledg[ing] and reaffirm[ing] the importance and central role of human performance in motion pictures and the potential impact on employment under this Agreement when a Synthetic created through a [generative AI] system is used in a human role that would otherwise be performed by a human.”

Instead of a “Tilly Tax”, the AMPTP agrees that an AI actor will not be used unless it brings “significant additional value” that neither a human performance nor their digital replica could bring. That means the use of Synthetics—AI characters not recognizable as any specific real person, not voiced by a human—faces a higher bar than digital replicas and the one the “Tilly Tax” would have established. That proposal assumed that AI actors like Tilly Norwood portended the inevitable replacement of human actors.

Producers are now agreeing that human talent is the rule and AI talent will be the rare exception. They also agree that if they choose to violate this provision, SAG-AFTRA may seek damages in arbitration in an amount that could be larger than what could have been paid to a natural performer for rendering a performance for which the Synthetic was used.

In both cases, it is more expensive than the Bollywood model.

The tentative agreement closes doors to allowing producers to use a digital replica to render a performance into another language without the performer’s consent. That provision will start for productions commencing principal photography on or after July 1st, 2027. Films that began shooting before the cutoff carry the old no-consent rule for the life of those pictures.

Open Doors

Last month’s essay outlined how Bollywood’s ecosystem lacks every constraint that paralyses U.S. media and entertainment is absent: no SAG-AFTRA equivalent forcing consent for digital replicas, no U.S.-style litigation pressure on AI training data and no insurer refusing to underwrite AI risk. Bollywood is able to do so because it is building an AI-native media marketplace that does not require U.S. IP, consent law or distribution.

SAG-AFTRA’s tentative agreement anticipates these dynamics while forcing the market to prioritize and protect human actors and their digital likenesses. For producers seeking Bollywood-type cost efficiencies and business success stories, this creates friction. The outcome of “Raanjhanaa” —which sold 35% of available Tamil-language tickets in the release month—involved little-to-no friction.

The only Bollywood-like provision permits studios to license performer footage to non-affiliated third parties for “training a public-facing, commercially-available Generative Artificial Intelligence System”. However, that is subject only to written notice and a meeting with the union.

What Does Friction Look Like?

The question now is what this friction will look like in practice. Generative AI is targeting Hollywood’s production cost model directly, and Bollywood is the live proof of concept. The market reality is that Hollywood producers will rationally seek Bollywood-like cost-efficiencies and business case studies.

The producers and SAG-AFTRA have opted to reshape the rules rather than adapt to the market—which is the strategic choice my earlier essays argued they would make. Because these rules are enforceable via both agreement and arbitration, they add approval processes and disincentives at a time when competitive markets in Asia and Africa are emerging without similar rules. This may be either a soft, selective enforcement mechanism or a more sophisticated deterrence mechanism.

This suggests that—for all protections for human talent that the agreement achieves—these protections may come at the expense of competitive advantage in a global marketplace. Bollywood is demonstrating that there is a business to be built in embracing AI technology at the expense of traditional norms. Similar case studies are rapidly emerging in Asia and Africa.

The SAG-AFTRA deal suggests Hollywood is the lone exception. The real “tell” will be in whether the arbitration clause is ever enforced. That will be the best measure of how Hollywood is managing its existing global power against AI-driven upstarts across the world.

Past essays related to today’s analysis:

I spent so much time chatting and meeting new people in the hallways that I missed the talks I had planned to see. At some point it became clear that the speed at which everything is changing is faster than the human imagination. It was a lot of information to process.

Multiple people I spoke with complained of various “bottlenecks”.

The common “bottleneck” was that corporate America cannot move fast enough. That is not always the case—I have heard from multiple AI creators that Netflix is making deals for generative AI shows and movies to be released later in the year. Otherwise, I heard about legal bottlenecks. I also heard various versions of challenges with “market understanding and approval readiness” at the management levels at both Hollywood studios and ad agencies. There is too much friction in the institutional machinery that decides what gets made, cleared and distributed for creators and ad campaigns.

That leaves a gap between what AI can make and what organizations are prepared to greenlight. The business model for AI content in its current phase lives in that gap.

I went into the summit thinking that advertising is the path ahead for certainty. It is objectively the better business model for creators to monetize their content, and brands and agencies are increasingly those creators full-time.

I left the Summit unsure of that conclusion. Here is why.

Past essays related to today’s analysis:

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Today I want to take a moment to pull and tease out the structure of what I see playing out in the marketplace.

Recent essays focused on People, Inc.’s “INVERSION” and recent technological challenges to celebrity likenesses because they are parts of the same problem: What are the businesses for intellectual property when the medium shifts?

IP holders know they need to act. People, Inc.’s “INVERSION” is the most obvious example of an IP holder taking action. Chairman Barry Diller and newly appointed CEO Neil Vogel have been evangelizing the strategy in interviews and letters to shareholders. Diller’s long track record of success in digital media and Vogel’s success in transforming About.com—a neglected internet hub IAC acquired from the New York Times in 2012—to digital publishing heavyweight DotDash Meredith within less than a decade make them credible strategists.

But both have been quick to acknowledge that brands are dying—Vogel told journalist Peter Kafka “40 of our brands don’t matter, about seven or eight of them matter”—and they both have conceded that many of their bets likely will not work as businesses.

Their message to investors is clear: Management recognizes and understands the uncertainty. They cannot wait around for audiences to rethink how they value People, Inc.’s portfolio of website and magazine brands. They have a strategic need to take action now, even if it involves 200+ bets (according to Diller) and many failures. They can do so because their cash flow is not being disrupted yet.

Last Thursday’s essay argued that the strategy is directionally right given the emerging disruption from AI. However, Diller’s hope that INVERSION will build “a giant company” seems unlikely to be achieved. Even with competitive advantages in digital media like its AI ad platform D/Cipher, the strategy still faces structural uncertainties in the marketplace and emerging competition from small-to-medium-sized businesses. Those uncertainties lie in business affairs, legal, policy, strategy, underwriting, investment and partner-facing teams each evaluating part of the same opportunity while IP law weakens from AI disruption. Without it, there is increasingly less of a common language and decision-making framework.

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Last October, I wrote that intellectual property holders in media and entertainment “risk being fragmented before they can fragment themselves.” Around the same time, People, Inc. Chairman Barry Diller described—in a podcast interview with Patrick O’Shaughnessy—a strategy his company now calls “INVERSION”. Rather than licensing its brands to CPG companies, People, Inc. would partner with them to build and own consumer products. Their best strategy is to fragment themselves.

In a recent podcast interview, CEO Neil Vogel framed this approach to fragmenting People, Inc. around “permission”:

“Brands that people love and care about, they’re going to be permissioned to do different things. When we figure out what they’re permissioned to do, we’re going to do those things and that’s how we’re going to connect with audiences and that’s how we’re going to make money. And it actually works.”

“Permission” reveals the dynamic beneath “being fragmented before they can fragment themselves.” Even as platform disruption and an accelerating supply of creator-led products erode the value of publisher brands, People, Inc. still has talent and assets—first-party data, editorial relationships and advertiser trust—to identify a market need and build a branded product around it. Diller has touted a few initiatives: a Southern Living tea, a chef-driven product line from Food & Wine and a Travel & Leisure entertainment property with the cultural reach of “The White Lotus.”

However, there are two challenges to this. First, as I wrote on Monday, Meta, Google and Amazon are making it easier for creators and SMBs to build, market and sell products without a publisher in the value chain. They are “flattening” both production and distribution models—collapsing financial, legal and technical barriers to entry—enabling more competition that will “fragment” People, Inc.’s portfolio of companies. Vogel conceded this reality in his interview on Channels with Peter Kafka: “we’ve already lost more than half of our referrals from Google”. As a result, “40 of our brands don’t matter, about seven or eight of them matter.”

Second, generative AI platforms like Sora and Seedance 2.0 are demonstrating how quickly brand identity can be replicated by producers who have no stake in the original. INVERSION responds by maneuvering around that erosion. Rather than defending brand value in channels where it is under pressure, People, Inc. bets that brand equity can be converted into physical product demand before it depreciates further.

Given Diller’s ambition for INVERSION to build “a giant company,” and given data suggesting giant CPG hits have been rare in the past decade, brand equity and first-party data alone are not sufficient. A difficult environment for incumbents is getting harder faster.

The Real Question: Viability

The more immediate question is not whether People, Inc. can produce a giant hit but whether it can produce a viable one.

“Viability” implies a product that generates an annuity on existing brand equity. “Giant”implies a product with compounding returns, deepening the audience relationship with every sale and building an asset worth more than the brand that launched it. Analysis of 301 CPG breakout brands by CPG brand strategist Matt Alldian points toward viable, not giant, as the realistic outcome for People, Inc.

That market logic points to a deeper dynamic. People, Inc. is an incumbent media company. It seeks to partner with incumbent CPG companies to protect and extend the life of its brands. Both must compete with a growing supply of SMBs empowered by technology companies with massive advertising reach.

We have seen this dynamic before in the Interactive Advertising Bureau’s “The 200 vs. The 10 Million” framework from 2022. The 200 were the limited group of advertisers who supplied 88% of US network TV revenue. The 10 million were the emerging SMB advertisers on Facebook and Google. Platforms that bet on the latter made the better long-term play, and legacy media companies are playing catch up. Instagram now reports that over 200 million business accounts worldwide are posting videos and photos.

Recent earnings calls suggest that number will only keep growing. Amazon CEO Andy Jassy told investors last week that the AI tools make it “so much faster and so much easier” for SMBs and predicted there will be “a lot more advertisers with the rise of what’s happening in AI.” Google SVP and Chief Business Officer Philipp Schindler told investors on its Q1 2026 earnings call that AI-driven Search advertising campaigns enable SMBs to reach customers “at a scale that really wasn’t possible even a few years ago.”

The implication is clear—more SMBs with more tools will compete directly with both media incumbents offering products and CPG incumbents. With traditional TV inventory declining and streaming advertising fragmented across multiple Smart TV operators and streaming services, the incumbents will have less leverage over the rest of the marketplace. Kraft Heinz’s new CEO Steve Cahillane recently admitted as much to the Wall Street Journal: “I think we took for granted that brands would always stay relevant with consumers, and they don’t, no brand does.”

Reach is not Resonance

A media brand product play that lacks intentional audience building monetizes existing brand equity—an annuity on a depreciating asset. A creator-led brand with genuine audience resonance compounds, because every piece of content deepens the relationship that drives purchase.

People Inc. has reach and its first-party data (via its AI ad targeting product D/Cipher) can identify consumers for whom the brand resonates. The harder question is whether any of its brands have the depth of relationship that converts to purchases from fan bases—and not just a one-time trial driven by brand recognition.

Any partnership with a CPG incumbent begins with incompatible survival modes. A media brand survives on audience trust and monetizable attention—a niche of loyal, paying readers is a viable business. A CPG brand survives on shelf velocity and distribution coverage at scale. Under market pressure, both incumbents will optimize for their own survival in opposite directions.

Three outcomes are possible once a product finds resonance:

1. A viable product creates an annuity—steady revenue from a loyal niche that licensing alone would not capture, with both parties content to maintain the arrangement.

2. A hit product creates a revenue spike, but the shelf life of breakout CPG brands is shortening—what looks like a compounding asset may be a one-hit wonder that fades before it can become the foundation of anything larger.

3. A “giant” product generates sustained compounding returns and consumer retention over time, but Alldian’s data suggests this is the exception and not the rule. It also shows creators and brands with highly targeted products are best-positioned to succeed.

In the first scenario, People, Inc. has a revenue stream but not a company-defining asset. In the second, it needs to have a larger pipeline of products. In the third, the partnership structure that enables INVERSION may be the very thing that prevents it from reaching Diller’s ambition.

It makes one wonder whether People, Inc. may be better off licensing its IP to multiple SMBs and letting them compete for the best consumer product.

Past essays related to today’s analysis:

He then answered the question himself using Claude Code, which ingested 383 brands across nine industry breakout lists (e.g., Bain Insurgent), and then filtered them to 301 brands. Alldian asked Claude to enrich each company entry with founding year, ownership, revenue and exit data, then filtered the results against strict criteria.

The exercise found that among the 301 brands, every “giant” hit—excluding Feastables—was founded 2015–2019 and broke out over the last five years. That includes soda brand Olipop (2018, $1.85B valuation), water brand Liquid Death (2018, $1.4B valuation), nutritional supplements brand Alani Nu (2018, $1.8B Celsius acquisition) and meat snack brand Chomps (2012, ~$500M revenue).

Among companies founded between 2021 and 2026, only Happy Dad, Lemme, Prime Hydration and Byoma are on multiple lists but, none has reached the multi-list, billion-dollar-outcome tier yet. Only Byoma is not a creator-led brand.

Last week I argued that “faster” is the key variable of the “faster, cheaper, better” maxim in both AI-era content development and product development. Last week’s earnings calls reveal why this is a crucial market obstacle to People, Inc.’s ambitions.

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Yesterday, IAC announced in an 8-K filed with the SEC that it was rebranding to People, Inc.

The filing includes a more formalized version of “INVERSION”, which Chairman Barry Diller briefly outlined in a podcast interview with Invest Like The Best last September, and which I wrote about in “Your Favorite Magazine Should Start Making Tequila”.

I wrote that Diller’s concept of INVERSION suggested that “as online commerce has matured, there are more avenues to monetizing this IP via a DTC business or partner with someone looking for new ideas for TV shows.” Diller added on the podcast “If you think about our businesses [through the lens of INVERSION], you succeed and fail, but you’ll come up with hundreds of things to pursue that, if some of them work out, you’ll build a giant company.”

Yesterday Diller defined INVERSION in a letter to shareholders:

“[It] means taking each of our properties and their intellectual capital and turning them into opportunities to play a direct role in creating new products and services that we own directly, rather than the traditional publishing model of licensing brands. We have literally 19 separate initiatives operating now that are exclusive of the traditional publishing model. I intend for us to be the principal, rather than the licensor, wherever we can in the products and services that will be birthed out of our enormous reservoir of content.”

I wrote then that Diller was betting on its “history and much experience in online commerce” to build this business, the same rationale that he argued positioned it to unlock unusual value from MGM Resorts back in 2020 (it now owns 26% of the company). Notably, Diller writes that “the very hard assets of MGM Resorts” and a “mostly virtual media business” will make up the “corpus of People Incorporated”. Diller sells this as “a perfect hedge in a world that is changing so unpredictively fast.”

The world is changing fast, but INVERSION may not be the right bet on a hedge. I wrote previously that the underperformance of BetMGM relative to its competitors suggests Diller’s and People, Inc.’s keen strategic insights do not always translate to execution. Execution still matters. The generative AI marketplace is already revealing where the limits are.

Disappointing Returns from BetMGM

Diller argues in his letter that the MGM stock “continues to be wildly undervalued.” Back in 2020, Diller’s pitch on MGM was that IAC’s history and experience in online commerce positioned it to unlock unusual value from MGM. That has not happened over the past five years.

A big reason why is that People, Inc. has not added much obvious value to BetMGM since 2020. As data from iCasino shows (below), BetMGM has actually lost market share over the last four years. Its competitor DraftKings is up ~50% over the same period and FanDuel is effectively flat. MGM’s stock price ($36 today) has underperformed the markets, up 82% since August 2020 compared to 247% for the S&P 500 and 210% for NASDAQ. It is also down 22% from its all-time high of $50.90.

The market has largely soured on the betting market—DraftKings is down 35.4% year-to-date and 30.7% year-over-year. A big part of that is the emergence of prediction platforms like Kalshi and Polymarket, which are quickly capturing market share.

Product Development Requires Faster Speed

In the podcast interview, Diller outlined his vision of People Inc.’s editorial brands—an “incredible gold mine of content, of ideas and of subject areas”—becoming physical products, entertainment properties, and consumer goods.

I have previously written about “faster” being the key variable of the “faster, cheaper, better” maxim in both AI-era content development and product development. For content development, I wrote “‘faster’ is the variable that will change marketplaces more than ‘cheaper’” because that model favors both advertisers and AI storytellers alike.

As for product development, Trevor Sumner—the CEO of i-Genie.ai, an AI consumer insights platform that empowers leading brands and retailers like Bayer, Coca-Cola, Danone, L’Oreal, Unilever, Kenvue and Elida— explained to me last Spring why faster is the key variable in product development with AI:

“We can go from information to true insight to action plan faster than ever before. And I don’t care what industry you’re in, more agile decision making that’s more informed with higher success rates makes a lot of sense.”

People, Inc. is moving in this direction with the “19 separate initiatives” pitched by Diller.

Sumner’s sales pitch suggests that this number is too low. People, Inc. needs to move faster. Sumner was saying last Spring that they can move faster. Beyond Diller’s salesmanship, there is not much evidence yet People, Inc. is in a position to do so.

Adding Infrastructure Is Risky

Earlier this month, I highlighted one big challenge People, Inc. faces in creating new products and services that it owns “directly, rather than the traditional publishing model of licensing brands.” Betting on building, owning and distributing these new products typically requires building infrastructure—supply chain, fulfillment, retail relationships, regulatory expertise— that a digital media company like People, Inc. does not currently own.

A white-labeling strategy similar to the ones YouTube and TikTok creators pursue with manufacturers—like MrBeast’s Feastables chocolate business or Logan Paul’s and KSI’s Prime Hydration beverage—creates a near-instant path to market. This involves hiring a manufacturer to produce a product under the People Inc. brand. Like MrBeast, People Inc. owns the product and the customer relationship. The manufacturer is an invisible partner.

One question for the INVERSION model is which parts People, Inc. and Diller are more likely to own than outsource. Retail relationships are a likely bet—People, Inc. brands like The Spruce and Byrdie have had success with white-label paint, pets and makeup lines. The company has strong relationships with retail advertisers and Diller has a powerful network developed over seven decades.

Those are familiar risks. New unknowns are created by adding retail infrastructure in an era where storytelling creates moments but infrastructure captures value. Agility wins and complex corporate architecture slows companies down in an “unpredictively fast” marketplace—Sumner highlighted last Spring how brands are going to have faster product cycles. In response, Fortune 500 brands like Starbucks, Nike and Burberry are now “dismantling the unnecessary architecture that turned them into shapes too complicated for anyone to hold”, as Code & Theory’s Chief Creative Officer Craig Elimeliah recently wrote.

Infrastructure is not entirely a disadvantage to People, Inc., which is a storytelling business. It has built an in-house, AI ad targeting product called D/Cipher which reduces the technological architecture between advertisers and People’s first-party data. Diller says it will leverage D/Cipher and its first-party data to market those products.

Diller seems to believe that People, Inc.’s brands can result in products that get to market faster and are perceived as “better” because of the brand power of its portfolio of IAC and Meredith Publications. That may not be enough to produce hits when its advertisers are also placing similar bets, and iterating with sophisticated market research models. Advertisers also have more resources—P&G has a $342 billion market capitalization, which is 100x the market capitalization of IAC’s current market cap.

White-labeling, alone, will not be enough to compete.

The Larger Question

On the Q4 2025 earnings call, Diller pitched Southern Living's Southern Tea as a product People Inc. would own and distribute, a Food & Wine chef-driven product line and Travel & Leisure's "own White Lotus."

One question is how fast they can bring these to market and iterate against creators and advertisers pursuing similar strategies. A larger question is whether any INVERSION products can survive long enough to be the foundation of a “giant company”.

Their short-term priority should be speed to market. The good news is that “faster” is very much in the DNA of People, Inc.’s success. CEO Neil Vogel told Fast Company in January 2020: “Our job is to make great content that loads quickly with relevant non-intrusive advertising.”

Now the rebranded company’s job is to curate new brands for white-label partners who can produce and iterate quickly to deliver product to People, Inc. audiences. The other path is too slow and too expensive. That suggests their ultimate challenge will be whether they can come up with enough ideas to compete with their advertisers.

Past essays related to today’s analysis:

Google-owned YouTube recently announced an alternative path to that outcome: A deepfake detection tool for creators which it opened up to politicians and journalists last month, and expanded to actors, athletes, creators and musicians last week. Anyone “at high risk of having their likeness abused” can sign up to identify and request removal of deepfakes on its platform, whether or not they have a YouTube account.

The model is the “same concept” as its Content ID system to identify copyrighted content uploaded to its servers. Effectively, a celebrity, creator or public figure is uploading their likeness into Google’s cloud infrastructure, where AI learns to identify—but not produce—those likenesses across all content on the platform. That is an enforcement mechanism that operates at both the cloud-level—where the likenesses are identified—and the platform-level—where the videos with violations are either flagged or removed. This mechanism is “air-gapped”: constrained within the cloud and isolated from other models and the broader internet.

That is a double-edged sword. Likenesses can be protected independent of studios, which are slow to partner with cloud companies. However, unlike content ID—where music rightsholders are paid a portion of ad revenue where use of their music was identified—celebrities are not being compensated when their likeness is flagged. They and/or their management team must request the removal manually.

But that request for removal “does not guarantee that YouTube will pull the video”, as its community guidelines allow for “a number of cases like parody and satire” to remain on the platform.

These are operational costs. The deeper problems are structural.

Past essays related to today’s analysis:

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