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.

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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.

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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.

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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.

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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.

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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.

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One core message of Netflix’s Q1 2026 letter to shareholders last week is that the “landscape” of the media marketplace is “more dynamic than ever”. In a section entitled “Our Focus”, management lists a series of factors impacting the business:

• “Streaming continues to take view share from linear.

• Technology is enabling a massive increase in video content from a wide variety of storytellers.

• There are more ways for consumers to connect to the stories they love, including through open content platforms, interactive and gaming services.

• ‘Premium’ content is increasingly defined by the viewer.

• The lines between entertainment on TV and mobile devices are blurring.”

This story has been told in different ways by Netflix management over the course of the last few years. The gist has always been Netflix competes with some mix of YouTube, gaming and social media platforms. The new detail is in the second bullet point about “a massive increase in video content from a wide variety of storytellers.” That phrasing broadly implies both more human creators, and more content from generative AI tools and platforms.

The result is more creators, more content and more platforms are fragmenting both the demand for consuming content on TV and the definitions of “premium content”. Netflix is positioning itself as a success story in subscription streaming—”slightly higher-than-planned subscription revenue”—and ad-supported streaming—projected to grow 2x year-over-year in 2026 to $3 billion.

These twin bets on subscriptions and advertising assume its content and inventory remain valuable to both consumers and advertisers. But the market dynamics it describes in that same section point toward a collision. Advertisers are increasingly turning to AI storytellers to create stories using their brands. It is their own version of premium content, and their natural monetization model is advertising. The implication is that the programmatic pipes for ad buying that Netflix is building are the root of both its future business model and its future competition.

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Nanonoble is the sole operator of the version of Hailuo AI available to users in the United States. The lawsuit alleges that MiniMax, Nanonoble and SXJT disregarded U.S. copyright law by treating the studios’ copyrighted characters as if those were their own.

A motion to dismiss is, at its simplest, an argument for an outcome. As a rule, outcomes are determinative and arguments are not. In this case, this argument makes a number of counterpoints that mirror themes in my recent essays:

1. Cox Communications v. Sony Music Entertainment told IP holders that the legal system is the wrong venue for solving this problem at scale and that is the overall gist of the filing;

2. The 52 infringing videos were created by the studios themselves and not by any creators, which fails the Cox Commc’ns, Inc. v. Sony Music Ent. test of a service provider being secondarily liable

3. The studios may own popular IP like “Star Wars” but their complaint fails to explain why their copyright registrations also cover the characters within them—suggesting that there are “no sacred cows”;

4. U.S. copyright law does not reach conduct that occurred entirely abroad, suggesting Hailuo AI is one of those “thousands of tools” like Sora but which cannot be sued.

More importantly, the motion to dismiss also confirms the market coordination failure I highlighted last month with my Beer Marketplace paradigm: MiniMax and NanoNoble are arguing that they are neither able nor incentivized to police copyright the way the studios want both within and outside the U.S. The law is not the solution here.

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The market reaction both in the media and in my recent conversations with executives is one of surprise— the writers folded easily on the issue of AI after demanding strict terms on its usage only three years ago. All eyes now turn to the AMPTP’s negotiations with the Screen Actor’s Guild (SAG), which will resume on April 27th. SAG has proposed a “Tilly Tax”, a fee named after the “first” AI actor in Hollywood—who I wrote about last October—which studios would have to pay to the union in exchange for using an AI actor.

No one expects SAG to fold as easily around the “Tilly Tax”. But there are lessons to be learned from Bollywood, where Eros Media World recut a 2013 hit movie “Raanjhanaa” over the lead actor’s public objection.

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Google has previously estimated that there will be 1.2 billion new users who gain access to the internet between 2022 and the end of 2026. Services like SpaceX’s Starlink and Taara—an Alphabet X Moonshot company that uses beams of light to deliver high-speed data links—are expanding internet access to rural areas globally, and particularly in India and Africa.

As I wrote last August, this generation will be “the first to access the internet via AI platforms like ChatGPT and Claude, and not via start pages like Google, Yahoo or web browsers.” Reuters recently reported one impact of this new generation’s emergence in India: Bollywood studios “deploying AI at a scale unseen elsewhere” and audiences willing to pay for their AI-generated and AI-edited content. Bollywood producers are iterating and shipping AI-produced content, and audience demand is absorbing the rapidly evolving supply.

India is an emerging AI media marketplace that is unburdened by the regulatory and economic constraints of the U.S. marketplace. It is also rapidly being reshaped by growing internet access. It offers an important market test of Hollywood’s fear and AI platforms’ hopes for the future of entertainment.

The 1.2 Billion

India now has 958 million Active Internet Users according to the Internet and Mobile Association of India (IAMAI). That reflects 8% year-over-year growth. 548 million active internet users in rural areas account for over 57% of total users. Those are growing at nearly four times the pace of urban India. 38% of India’s population—nearly 579 million people—are not yet active internet users.

Reuters depicts this emerging generation of Indian consumers as having media diets evolving away from theatrical and shifting to streaming. This has resulted in production budgets being cut. Now they consume “full-fledged AI-generated films”, movies dubbed in numerous languages using AI and older titles recut with AI to revive ticket sales at lagging theaters.

AI dubbing is particularly powerful in India, which has 22 official languages and hundreds of dialects. The technology substantially reduces the cost of serving submarkets of languages and dialects, which in turn creates new demand across those submarkets.

Aggressive Supply Side

Reuters also depicts a supply side aggressive on both costs and technology to meet this changing demand. A Bollywood director told Reuters: “In India, cinema isn’t about art. It’s purely business, so studios are going to use it to make mythologicals. Our audience is a sucker for it.”

The business logic favoring mythology has echoes in the AI-generated Revolutionary War series titled “On This Day ... 1776” from Hollywood director Darren Aronofsky and his AI-focused venture Primordial Soup—sponsored by Google, Salesforce and Time, and distributed on YouTube. On the 250th birthday of The United States of America, its founding mythology has never been more important.

They are proving there is a business in cheap AI-driven productions of American history guided by Hollywood production talent and without Hollywood acting talent (although George Washington often looks like Sean Penn). “On This Day ... 1776” is an independent venture structured to avoid paying expensive actors and production guilds, distributed on YouTube to bypass theatrical and streamer gatekeeping and sponsored to avoid relying on direct-to-consumer spending or streaming economics. It routes around Hollywood market constraints that are weaker or nonexistent in Bollywood.

Reuters noted that PVR Inox, India's largest cinema chain, is a partner in the experiment, not a casualty of it—AI recuts are being deployed to revive ticket sales at lagging theaters, inside the same window Hollywood is watching collapse (in 2025, location intelligence provider Kalibrate estimates average visit volumes declined by 15% year over year across major movie theater chains).

Technology firms are meeting the moment: Nvidia recently told an audience at India’s AI film fest that it is working to slash computing costs so that anyone can “create something substantial without putting a lot of money” into production.

This is structural alignment. Traditional storytellers are increasingly relying on AI and the technology firms are eager to deliver the infrastructure to help them. No one is waiting on anyone else to make the first move. Every constraint that paralyses the U.S. media and entertainment industry is missing in India. There is no SAG-AFTRA equivalent forcing consent for digital replicas, no copyright cases against AI platforms in a slow appeal process, no DMCA architecture to litigate around and no insurer refusing to underwrite AI risk.

The system does not need valuable IP. The myths are Indian, the audience is Indian, the distributors are Indian, and the only U.S. asset in the chain is the compute and model layer that the production companies rent by the hour.

A Hollywood Nightmare in Bollywood

India is the AI-native media marketplace Hollywood is fighting to prevent. It is evolving this fast because the 1.2 billion are not being converted from a prior media diet. The demand side is AI-native from first contact.

Their first internet experience is an AI platform, their first filmed entertainment is AI-generated mythology in their own dialect and their expectations are being set by what Bollywood ships this quarter. Supply and demand are forming together to create a new world of entertainment consumption—the only missing ingredient is Prosumer and Creator AI-generated content (see below). Google, Microsoft and Nvidia “partnering with local filmmakers” suggests that will emerge next.

The Hollywood nightmare is not that audiences will embrace AI-generated content. The Indian audience already answered that. The nightmare is that India is proving that an AI-first ecosystem does not need valuable U.S. IP, does not need U.S. consent law and does not need U.S. distribution. All it needs is U.S. tech infrastructure and the storytelling takes care of itself.

Bollywood production companies are already seeing the upside at the box office. Eros Media World recut a 2013 hit movie “Raanjhanaa” over the lead actor’s public objection and sold 35% of available Tamil-language tickets in the release month. Hollywood talent agents would have killed the recut before it reached production.

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Electricity followed this arc in the 19th and early 20th century. Bajarin and many other folks in my feeds and chat groups argue the build-out of today’s AI infrastructure now follows the same arc. Cynics counter that the inflated valuations of AI companies are a bubble like crypto, which also arrived as a buildout of “hardware and headlines” to replace traditional finance. 20 years into that marketplace, there are only $20 billion in onchain fees.1

The clearest signals from the advertising marketplace that “this time is different” with AI. Last week I argued that brands leveraging AI to build their own entertainment infrastructure will drive ad dollars out of the traditional advertising value chain altogether. I cited an argument that the barrier is lower for brands not to just become creators but 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.”

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TBPN had captured a small but valuable audience—70,000 viewers per episode across three-hour weekday shows on various online platforms.. The Wall Street Journal reported it earned around $5 million in revenue from advertising last year and was on track to make more than $30 million in revenue in 2026.

OpenAI’s move is analogous to its short-lived business plan to integrate Sora into the ChatGPT app last month—putting TBPN video one-click away from a global audience of 920 million weekly active ChatGPT users will help the show to grow and OpenAI to drive the conversation around its brand.

TBPN founders were rewarded with an extraordinary sales price in “the low hundreds of millions”, according to The Financial Times. In exchange they gave up advertising sales, sponsorships from third parties and editorial independence.

Something I previously wrote about OpenAI’s move to integrate Sora into ChatGPT applies here, too: “OpenAI’s move confirms that storytelling creates moments but infrastructure captures value.”

OpenAI is defining those moments as both scoops and “idea-driven conversations”. It argues where those conversations happen and who drives them “matters”.

This point also echoes something I wrote on Wednesday.

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Three developments from this past month reflect a weird moment for the $1 trillion advertising marketplace I wrote about in January.

First, the video market has become a zero-sum game with a shrinking ceiling. Streaming is pushing more consumers to cheaper, ad-supported tiers but only recapturing two-thirds of ad dollars being lost from linear, according to research firm MoffettNathanson. The rest of those ad dollars are leaking to YouTube and other digital platforms.

Second, Variety and The Wall Street Journal both reported that Nielsen’s popular “The Gauge” may be providing an inaccurate lens on the video marketplace. Nielsen had previously drawn estimates entirely from its own volunteer panels. In recent months, it began warning clients that “its broadcast and cable TV figures could see a boost in February after it began using a study from the industry’s Advertising Research Foundation to inform its estimates of the demographic groups in U.S. households and the technologies they use to watch TV.”

In response, Nielsen has yet to release The Gauge for February 2026. Streamers are pressuring Nielsen to delay the report because of this ARF methodology. The annual upfronts and newfronts events—where broadcasters and streaming platforms pitch upcoming inventory to marketers and ad buyers—start soon, and the industry does not have reliable data on where audiences actually consume content.

Last, Jason Zada—founder of entertainment studio Secret Level—argued in a recent essay that “the old playbook” of “interrupt, target, repeat” for TV and streaming advertisers is “getting harder and more expensive to run every year.” This model is also “always late”—”The gap between ‘this is culturally relevant right now’ and ‘our campaign is ready’ has always been the dirty secret of the industry.”

The message from all three different market signals: The traditional media value chain—produce content, attract audiences, sell advertising against those audiences, measure with Nielsen—is collapsing at each node.

Back to the $1 Trillion Ad Marketplace

In January I argued that the new AI advertising infrastructure being built—scene-level targeting, AI production tools, programmatic efficiency—”extracts value from storytelling without distributing value to storytellers.”

I added:

“The differentiation for monetizing storytelling is not quality—it is operating capabilities. For fat tail creators, that means infrastructure to monetize the moments algorithms surface. For successful mid-tail creators like TBPN, it means infrastructure to monetize without algorithmic ad targeting at all.”

Zada argues that in this market, the barrier is lower for brands not to just become creators but 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.”

The infrastructure of monetizing moments that algorithms surface favors this model: “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.” Agencies like Secret Level and AI storytellers working for brands are the ideal partners for this model.

Two Questions for Upfronts & Newfronts

This leaves two open questions for upfronts and newfronts.

First, what will happen to legacy media advertising spend?

Both Linear TV (-3.3%) and broadcast (-2.5%) Upfront spending fell last year, while streaming surged (13.9%). Whatever the revised Gauge says about streaming, YouTube is positioned to capture more. Measurement is broken. The upfronts are becoming less relevant—not only because key Nielsen data is unreliable but because there is an emerging alternative that does not need the sellers.

Second, if brands reduce spend with linear and streaming, will those dollars shift towards the creation of original IP?

If brands follow Zada’s model and build their own entertainment infrastructure, the dollars will not shift from linear to streaming or from streaming to YouTube. Instead, they will leave the traditional advertising value chain altogether. The upfronts are selling inventory inside a system that brands are beginning to build around.

A Hidden Catalyst

Zada’s proposal also connects to something I wrote in February:

“A Cambrian explosion of creators outside Hollywood may be coming. But the path to building and monetizing original IP requires physical infrastructure, legal literacy or an audience at scale. Most AI storytellers stand at the fork possessing none of these.

The successful path with brands has a lower bar—the skill set to orchestrate creative across multiple tools and a few days of schedule bandwidth.”

The implication is that Nielsen’s failure to measure audiences accurately is creating the conditions for brands to stop relying on third parties to create the moments to connect with those audiences. This will be a catalyst for generative AI creators like Zada to reap the gains.

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