I continue to get occasional notifications of new followers and subscribers. However, since April 2025, all my writing is posted to my Substack, The Mediator.

Click here to read the full post on my Substack, The Mediator.

I’m a little bit obsessed with this question: how do you know what’s important? As the volume of information increases, it’s an increasingly hard problem.

If you’re a student of anything that could be considered a system (like companies, industries, ecosystems, value chains, markets, networks, economies, culture, and geopolitics), part of the answer is to have a good mental model of that system. It should capture the most important concepts, assumptions, and causal relationships and explain how the system behaves and is likely to evolve over time. It gives you a filter to make sense of the daily deluge: does this support, contradict, or refine my model — or can I discard it as noise?

Putting it on paper keeps you honest. It exposes logical flaws and knowledge gaps. It encourages you to keep distilling it or, to paraphrase Einstein, to make it “as simple as possible, but no simpler.” It also forces you to revisit your assumptions and conclusions as facts change. The model should be a living, breathing thing.

The Mediator functions as my living, breathing mental model of the media business. I was recently talking to a media industry veteran and gave him my elevator pitch version (distilled from a recent presentation I posted online):

Over the last 20 years, digitization and the internet caused the cost to distribute media to functionally move toward zero, lowering barriers to entry. This disruption ushered in the tectonic trends that dominate the media business today:

• Stagnation of time spent;
• Fragmentation of attention (owing both to a massive increase in content supply and the changing consumer definition of quality);
• Disintermediation of traditional intermediaries as technology makes it easier for creatives and creators to reach consumers directly; and
• Concentration of both power in a few platforms and attention in a few megahits due to the amplifying effects of the positive feedback loops online.

GenAI is now poised to cause the cost to create media to also plummet, which over the next decade could be as disruptive, if not more so.

Without a beat, he replied, “Yeah, and one thing you’re missing is that revenue per hour has compressed.” My first thought was: [Expletive], how did I overlook that? It’s a big hole in my model.

I’ve written about this phenomenon in the video business a few times, like One Clear Casualty of the Streaming Wars: Profit and Video’s Fundamental Problem: It Over-monetizes. But it applies across media.

Deflation is another -ation that clearly belongs in the list.

Tl;dr:

• Disruption often causes structural price pressure.
• Sometimes lower prices boost demand substantially, both because of price elasticity and the development of new applications (the “Jevons paradox”). But this doesn’t apply to media, since time spent is already near saturation.
• That disruption causes price pressure in media isn’t a new idea. Jeff Zucker warned media companies about trading “analog dollars for digital dimes” in 2008. But what is perhaps surprising is the persistence of price pressure per unit of time.
• Below, I show that “traditional media” still monetizes much higher than “new media” per hour of consumption, ~20 or more years into the disruption of media distribution.
• In the U.S., linear video monetizes 50% higher than Netflix and 3X YouTube per hour; globally, on a per hour basis, console gaming monetizes 70% higher than PC and almost double mobile; and a purchased CD probably monetizes about 10X Spotify per hour.
• Does this matter? In the near term, the importance to each media vertical depends on the substitutability of new media for traditional and how far along we are in the disruption. So, it matters most in video, less in gaming, and least in music.
• The long-term implication is generalizable across media. This persistent, structural pressure on monetization is likely a harbinger of what will happen as GenAI lowers the cost to create content too.

Click here to continue reading the full post on my Substack, The Mediator.

Click here to read the full post on my Substack, The Mediator.

GenAI obviously has the potential to be extremely disruptive to media businesses in general and Hollywood in particular, but the speed and extent of this disruption hinge on a few critical unknowns. These include how far the technology will evolve and to what degree consumers will accept AI-enabled content, both of which I discussed in my last post (How Far Will AI Video Go?). Another is how and when the murky legal questions around GenAI will be resolved.

In this post I address another key unknown: whether talent will embrace it. That’s critical. Amid all the cool AI video demos, shorts, experiments, and fake movie trailers, it has remained very clear that AI video will only affect culture and the media business if people use it to produce compelling stories. Otherwise it’s just a parlor trick. But which people?

Talented people outside of Hollywood will unquestionably embrace it. There are probably tens or hundreds of thousands of “lost Einsteins” globally: creative and driven people who have an urge to create but either failed to make it in Hollywood or, more likely, never tried. I also think that there are thousands of people working in below-the-line jobs and around the periphery of Hollywood1 — development, production management, talent representation, marketing, etc. — who got into the entertainment business to tell stories, but for whatever reason found themselves in adjacent roles. (Interestingly, so far, many of the creatives at the forefront of AI have come from creative agencies — storytellers who do brand work but have long itched to tell stories of their own.)

But what about established talent within Hollywood? Attracting talented, successful storytellers would accelerate the disruption and enable GenAI to reach its full potential. People often talk about “Hollywood” as some monolithic thing, but of course it’s not. The studios and talent have long been in an uneasy codependent relationship, a combination of aligned and misaligned interests. Each desperately needs the other, but they share a mutual distrust and often clash over creative control, credit, and, of course, money. That tension boiled over during the strikes in 2023 and a lot of ill will remains.

In Hollywood, there has been a lot of vocal antipathy toward AI. But the ice is starting to thaw. Over the next year, I believe that many more Hollywood creatives will embrace it — including household name directors, writers, and producers — for three reasons: precedent, the continued progression of creative control in AI, and, most important, the problems in Hollywood will push them that way.

Tl;dr:

• Many in Hollywood have spoken out against AI, but some high-profile writers, directors, and producers are publicly endorsing it, with many more privately experimenting. Over the next year, I expect many more to emerge.
• There is a long history of creatives first rejecting new technologies as somehow undermining or bastardizing art, but then embracing them. In Hollywood, prior villains have included talkies, the DVD, and CGI.
• The deep learning models that power GenAI are massive, opaque, and hard to control. But commercial AI video and tool providers and the open source community are working hard to give professionals the fine-grained control they need. A non-exhaustive list of these efforts includes: training models with a richer understanding of visual terminology for more precise prompting; enabling conditioning of video models with both images and video; post-generation editing tools; ControlNets; fine-tuning; node-based editors; keyframe interpolation; and integration into existing edit suites/API support, among others.
• Perhaps most important, the challenges in Hollywood are inadvertently pushing creatives toward AI. With 2024 in the rearview mirror, it’s now clear that peak TV is truly over. Neither production activity nor spend bounced back from strike-depressed levels in 2023. From here, overall video content spend is unlikely to grow faster than video revenue — which is to say, not much. At the same time, rising sports rights and a mix shift toward acquireds will put even more pressure on original content. Tack on studios’ growing risk aversion and the path toward telling original stories in Hollywood is narrowing.
• Many talk about AI as a democratizing technology, but for some established talent it may be a liberating technology too.
• For a lot of people in Hollywood, AI still feels like a distant concern. As more talent embraces it, it will take on more urgency.

Click here to continue reading the full post on my Substack, The Mediator.

Starting April 2025, all full posts, including archived posts, will be available on my Substack, The Mediator.

I often write that the last 10–15 years in video(1) have been defined by the disruption of content distribution and the next 10 years are poised to be defined by the disruption of content creation.

Here’s the argument: The internet unbundled information from infrastructure and, with the help of a host of related technologies and massive infrastructure investment, caused the cost to move bits around to functionally head toward zero. We know what happened next.(2) Now, there is another emerging general purpose technology, GenAI, that may send the cost to make bits to head toward zero, too.

This symmetry of falling costs to move bits and make bits sounds good. It’s pithy and memorable. It seems plausible. But still: it is admittedly very high level and hand wavy.

What will GenAI really mean in practice for the video business? Will the cost to make TV and movies truly “fall to zero?” Will two kids in a dorm room one day make the “next Avatar?” Or, is GenAI another flavor of Silicon Valley’s naïve technological determinism, a blind belief that technology always marches forward and anything that’s technically possible is inevitable, without regard to pesky inconveniences like law, regulations, ethics and consumer demand? And what does disruption mean, anyway? Are we talking about complete devastation, the Kodak-disrupted-by-digital-cameras kind of disruption, or the far more benign Marriot-disrupted-by-Airbnb kind of disruption?

Figure 1. Two “Victims” of Disruption

The only credible answer to these questions is: no one knows. That doesn’t mean we’re completely flying blind though. We can frame out a range of possible outcomes by using scenarios.

Tl;dr:

• Scenario planning is a useful tool for navigating uncertainty. It can help identify the range of possible outcomes, the key milestones to watch, and the potential implications.
• A key step is identifying the two critical variables that will determine possible future states and the extreme potential outcomes for each. Below, I use technology development and consumer acceptance to construct a scenario matrix and analyze the possible state and implications of AI video in 2030.
• The possible outcomes for technology development range, at one extreme, from AI video models stalling out at their current capabilities to, at the other, completely resolving their current limitations in realism (especially the “uncanny valley”), audio-visual sync (especially lips), understanding real-world physics, and fine-grained creative control.
• The possible outcomes for consumer acceptance range from skepticism and sometimes outright hostility to fully embracing AI (and actually preferring it for some use cases). Steps along the way include consumers accepting it for certain content genres and use cases, especially those that don’t rely on emotive humans.
• Varying each of these variables between their extremes produces a 2 x 2 with four scenarios: low tech development, low consumer acceptance (“Novelty and Niche”); high tech development, low consumer acceptance (“The Wary Consumer”); low tech development, high consumer acceptance (“Stuck in the Valley”); and high tech development, high consumer acceptance (“Hollywood Horror Show”).
• Writing out narratives for each scenario is the most instructive part, because it helps make the abstract more concrete.
• Reality will probably fall somewhere in between, but this shows why it won’t require the most radical scenarios for the video business to change radically.

Click here to continue reading the full post on my Substack, The Mediator.

Starting April 2025, all full posts, including archived posts, will be available on my Substack, The Mediator.

A shift is underway across media. It’s happening on YouTube and Reels, Roblox and Fortnite, Soundcloud and Spotify, on Substack and Medium. On these platforms — across video, gaming, music and journalism — consumers are redirecting their time and attention to non-institutional, non-corporate content. Call it user generated, social, short form, independent, creator, whatever you like.

I recently wrote about the creator media economy in The Relentless, Inevitable March of the Creator Economy. It is one of the few bright spots in media. In that post, I sized the creator media economy at around $250 billion globally last year, or almost 15% of the total media and entertainment (M&E) market. I also showed estimates that over the last four years it has grown at about 25% per year, representing about half of all M&E growth. In this post, I dig deeper into a key cause and implication of this growth: consumers are redefining quality in media.

A common thread among this non-corporate content is that it usually doesn’t meet the same standards as corporate content. It is lower fidelity, less polished, less produced, more amateurish, rawer, more experimental. Measured against traditional standards of quality, you would call a lot of it crap. In most cases, traditional media companies would be embarrassed to put it out. But it keeps taking share of consumer time and attention anyway.

The only possible inference is that a lot of consumers are changing how they define quality in media, at least some of the time. For executives at incumbent media companies, it’s a big blind spot and a big problem.

I’ve written about quality before many times, like here and here. Below, I provide a more comprehensive framework for thinking about quality and discuss what incumbents can do when consumers’ perception of quality changes.

Tl;dr:

• People often think of quality as a value judgment. Instead, think of quality as the algorithm a consumer uses when choosing between similarly priced goods, in a similar context. Under this definition, quality is revealed preference.
• The goal is to create a framework for understanding why consumers make the decisions they do. This is especially important when the consumer definition of quality changes. It’s one of the most insidious causes of disruption and poorly understood.
• My experience at Turner showed that a changing consumer definition of quality is a blind spot for executives at incumbents. And even when they see it, it can be very hard to adapt. Many companies are optimized around a definition of quality; when it changes, it may cause entry barriers to fall; and company culture is often inextricably tied to it.
• It is clear today that consumers are redefining quality in media. Creator content usually has none of the traditional markers of quality, but it keeps taking share. You can see this empirically, especially in video and gaming. Consumers must be drawn by something else.
• What should incumbents do? They need to acknowledge this change, understand what is that “something else,” and figure out which of those attributes they can emulate.
• When the internet first emerged, it changed the way corporate content was distributed — but it was still the same content being distributed. If you think of it like a breakup, it was like consumers saying “I still love you, I just need to do this a different way. It’s not you, it’s me.” Something different is happening now. Today, the demand for that content itself is declining. It’s more like consumers saying “Actually, yeah, it’s definitely you.”

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Starting April 2025, all full posts, including archived posts, will be available on my Substack, The Mediator.

Imagine that from the time you were young, you worked hard to join a very exclusive, powerful club. Eventually, you made it, cementing your steadfast, lifelong belief that you, among very few, belonged there.

Then, another club opened next door. It let everyone in. It felt like a mockery of what you had achieved. But it kept growing, attracting more members, siphoning off more attention. Young people fantasized about joining that club, not yours. Your club now seemed stodgy and out of step. It would challenge some of your fundamental beliefs about yourself.

This describes how many in traditional media feel about so-called “creators.” They regard them as “less than,” crassly commercial, and certainly not artists. A recent dust up about The Hollywood Reporter christening a new Creator A-List is illustrative. As Justine Bateman tweeted at the time, this is a list “…of infomercial salespeople. It’s not Hollywood.”

Whatever one’s value judgments — whether the creator economy is a positive, democratizing force, or a bastardization of art and full of self-promotional hucksters, or something in between — numbers don’t lie. It is growing rapidly at the expense of traditional media and, as I explain below, will inevitably continue to do so.

Tl;dr:

• Let’s subdivide the media and entertainment (M&E) market into the corporate media economy and the creator media economy. Since M&E overall isn’t growing much, the relationship between the two is mostly zero-sum.
• Based on a bottoms-up analysis of the largest creator media outlets, I estimate that the creator media economy generated close to $250 billion in revenue last year, roughly 10% of the global M&E market. It is growing far faster and over the last four years accounted for almost half of global M&E growth. Conservatively, I estimate it will exceed $600 billion and 20% of global M&E revenue by 2030.
• There are very powerful technological, cultural, demographic and economic reasons it could grow even faster than this:
• 1) Even absent GenAI, the volume of creator content should grow much faster than corporate media as creation gets ever more accessible;
• 2) GenAI will trigger a tsunami of creator content across media. Just as bits became the atomic unit to distribute information goods, tokens are becoming an atomic unit for the creation of information goods;
• 3) The quality distinction between corporate media content and the best creator content will continue to narrow;
• 4) Falling trust in institutions and rising demand for authenticity structurally favor creators;
• 5) Monoculture is in decline as consumers atomize into microcultures, disadvantaging the traditional media business model;
• 6) Demographics are destiny, and younger demos spend much more time with creator content; and
• 7) The current monetization gap for the creator media economy (the delta between time share and dollar share) should narrow over time.
• All this is mixed news for creators and creatives. For traditional media, there are only two choices: figure out how to participate in the creator economy or accept a perpetually diminishing business.

This post is sponsored by WSC Sports.

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Reach out to WSC Sports to learn more.

To contact me about sponsorship opportunities for The Mediator, reach me here.

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Starting April 2025, all full posts, including archived posts, will be available on my Substack, The Mediator.

When a lot of people ask me the same question, it’s usually a good indication it’s worth writing about. Over the last week, many have asked what I thought of Ben Affleck’s comments at the recent CNBC Delivering Alpha conference about the effect of AI on Hollywood.

Many pundits have opined about the implications of AI for Hollywood over the last year or two. Affleck’s comments struck a chord. Maybe that’s because we’re at that point in the AI hype cycle where the public is primed for a skeptical take. Maybe it’s because he’s Ben Affleck. Or maybe because he’s one of the few Hollywood luminaries who’s been willing to venture a specific view about AI, not just vague platitudes. But, whatever the reasons, they did.

Bilawal Sidhu, who posted a clip of Affleck’s conversation on X/Twitter, wrote that it was “[f]inally a grounded take on AI & filmmaking from a Hollywood A-lister.” Jori Lallo posted that he “[d]idn’t expect Ben Affleck to have the most articulate and realistic explanation where video models and Hollywood is going.” Affleck’s comments were also widely covered in the press, like here, here and here.

Below, I distill what he said, where I think he’s right and why his overall conclusion is probably wrong.

Tl;dr:

• Affleck essentially dismisses GenAI as a sustaining innovation in Hollywood, something that will enable Hollywood to create “more shows” for the “same spend” and could represent a “new revenue stream.”
• His logic is that AI can’t create art or replace actors, but will reduce costs by ~30% by eliminating “laborious” tasks like VFX. It will also enable fan creation and personalization, for which IP owners should be able to charge.
• I agree with many of his points but think his overall conclusion is wrong. GenAI is more likely to be a disruptive innovation than a sustaining one.
• The notion that “AI can’t make art” — and the implication that therefore anything made with AI can’t compete with Hollywood — is a red herring. Maybe AI can’t autonomously make art, but that doesn’t mean it isn’t an artistic tool.
• GenAI may not displace actors in many genres, but many of the most successful TV show and film genres make little use of (undoctored) actors, like animation, sci-fi, fantasy and horror.
• Moreover, GenAI doesn’t need to replace actors to dramatically lower costs. Above the line costs are less than 20% of most projects. Animation is the canary in the coal mine, where there is growing evidence GenAI will bring down costs by ~90%.
• Most important, Hollywood is not competing in a closed system, so the risk of lower entry barriers is not just “more shows.” It is already under assault from creator content and GenAI may accelerate that disruption.
• In other words, the risk is less that Hollywood will replace people with AI, it is more that AI will hasten the displacement of Hollywood.
• Affleck deserves credit as one of the few in Hollywood willing to go on record about a controversial topic. But Hollywood is already a place that resists change. Downplaying the potential effect of GenAI won’t help.

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Over the last year, I’ve given this talk, or a variation of it, a couple of dozen times, so I decided to post it to a broader audience. It’s an attempt to condense my recent writing into a 30-minute presentation.

Here’s a video of the presentation and here are the slides. In it, I discuss:

• Why four themes in media — fragmentation, disintermediation, concentration (of power and attention) and virtualization — represent the “low background hum” of operating in the media business today.
• How these themes will affect the distribution of value between creators, traditional intermediaries, new intermediaries and consumers.
• The two disruptions of TV: the disruption of content distribution over the last decade and the disruption of content creation over the next.
• Why all the current problems in Hollywood are a lagging indicator of the last disruption.
• Why the biggest threat for creatives is not studios replacing them with GenAI, but GenAI vastly increasing the supply of competitive content and undermining the economic foundation of the studios’ businesses.
• Why GenAI is not just a way to make movies more cheaply, but could change the bases of competition in video.
• Why this disruption could happen even faster than the last one.
• What becomes scarce as content approaches infinite and the opportunities that may present.

Alternatively, below is the transcript (lightly edited for clarity) and corresponding slides:

Transcript

There is a lot of noise in the media business day-to-day and, especially when you’re in the thick of it, it can be hard to know what’s important and what’s not. A key premise underlying my writing is that there are important structural changes underway in media and, if you can make sense of them, not only can you predict where the business is heading longer term, but you can also pick out the signal from the daily noise.

So, what I want to do over the next 30 minutes or so is take a step back talk about those structural changes, and I’m going to make the case that the media business is going to change more radically in the next five to 10 years than it has in the last decade.

As I said, I’ve given this talk (or a variation) a bunch of times and here are a few of the places I’ve spoken.

I’m going to try to tee up and answer three questions.

1. How will value be redistributed in media over the next five to 10 years?
2. To drill a little bit further into the TV business. It’s been disrupted. So what happens now?
3. A lot of this is going to be pretty bearish for the traditional media industry. So, I think a good place to end is what opportunities emerge out of all this.

I discuss all these topics in more depth in my Substack, The Mediator. Here, I’m trying to distill what is tens of thousands of words into 30 minutes. If you want to go deeper into any of these topics, I encourage you to check it out and sign up. It’s free.

Tectonic Trends in Media

Let’s start with the tectonic trends in media.

To set the stage, it’s important to understand that on an inflation adjusted basis, media is not growing. That’s the orange line there. And this is all media. This is video, print, social, gaming, everything.

Why is that? Fundamentally, the media business, of course, is about monetizing attention and engagement.

But the problem is that there really is not a lot more attention to go around.

What you can see here on this top chart is that the average U.S. adult spends 13 hours a day with media. That’s 60% of waking time. And although this is a different source, the bottom chart shows a time series of time spent. What you can see here is that it grew with the advent of mobile. Then we got a nice bump — I guess not much about COVID was nice — but we got a bump with COVID, and then it really has been stagnant since.

If total time spent is not growing, it’s also very hard for value to grow and that’s why this is the most important question: how value will be redistributed along the ecosystem among these kids all sitting around, fighting for their piece of the pie.

To answer this question, earlier this year, I wrote a series of four posts (here are 1, 2, 3 and 4) about what I’m calling the tectonic themes in media. By tectonic, I mean that they are mostly unnoticeable day to day, but very powerful, and I think inevitable.

They are:

1. The fragmentation of attention.
2. The waning power of intermediaries.
3. The tendency of networks to concentrate both power and attention.
4. What I call virtualization, which is this idea that the increasing blurring of the lines between the digital and the physical will potentially open up new ways to use media.

But I think collectively, these four themes represent the low background hum of operating in the media business today. So, let me talk about each of these.

The first is fragmentation. Everybody knows that attention is fragmenting, but let’s talk about why. It’s happening for two reasons. The first is that barriers to entry are falling along the entire media product development process: production, marketing, distribution, monetization. To varying degrees, all are being democratized by technology.

As a result, there has just been an explosion of stuff, as we all experience directly every day. But let’s put some numbers on it.

In TV and film, I estimate that Hollywood, generously, produces about 15,000 hours a year of TV and film, but there’s 300 million hours a year uploaded to YouTube.

In music, there are 200,000 professional and “professional aspiring” musicians on Spotify, as Spotify defines it, but there’s 11 million total artists on Spotify. So, that means that less than 2% of all the artists are considered professional or “professional aspiring.”

And, in games, you have 3,000 games on a platform like Xbox, but you have 100,000 games on Steam, and it’s on track for 17,000 new games this year.

And these numbers are all only going to get more dramatic as GenAI evolves.

This explosion of content is what Clay Christensen would have called a low-end disruption. New entrants come in with a low quality product — as measured against the traditional definition of quality — the incumbents ignore it, but it keeps getting better and eventually it challenges the incumbents. And, to be clear, a lot of the stuff is very low quality. A lot of it, if not the vast majority, is not stuff you’d want to watch or listen to. It is what you could call crap. And most of the stuff that’s going to be created with GenAI will also be crap.

But this takes us to the second reason that fragmentation is happening. I think it’s a little bit less well understood than the first. Another facet of disruption is that new entrants don’t only compete on the traditional measures of performance, they introduce new attributes. If those attributes or features take hold with consumers, then they change the consumer definition of quality.

The example I always think about here is Airbnb, which, when it came out, I thought it was just about the worst idea I ever heard, paying to stay on someone’s couch. But as it has evolved, it has introduced all kinds of new features to lodging, things like having a full working kitchen or a driveway, being in a quaint neighborhood, having more closet space or whatever. In the process, it has changed the consumer definition of quality in lodging for a lot of consumers.

The same thing is happening in media, right? When you find a underground artist on SoundCloud or an indie game on Steam, or some creator that you find very relatable or authentic on YouTube, that’s a fundamentally different experience than consuming professionally-produced content.

You can see this evidence of fragmentation occurring across media.

In video, I estimate that about 1/4 of all time spent with video today is social video, YouTube, TikTok and Reels, mostly.

In music, the majors have been really resilient, but their share of streams on Spotify falls every year. It was close to 90% in 2017, now we are closing in on 70%.

And in gaming, the same thing is happening. A decade ago, casual, mobile, hyper casual, really barely existed and today, it’s half of the business.

The second theme, which is directly related to the first, is the idea that the role of traditional intermediaries is diminishing. What this chart shows is the historical value chain in media, which goes from creators to publishers to distributors to consumers.

Here’s another way to look at it, namely that the household names in media historically have really been intermediaries between creators and consumers. And they have extracted most of the value in the media ecosystem because they have done things that are really hard for creators to do themselves. They finance production, they assemble talent, they do the marketing, monetization, distribution.

But as I mentioned, technology is systematically making it easier for creators to do those things themselves. And if you look at this chart of the emerging media value chain and compare it to the prior one, you can see creators are moving down the stack.

What that means in practice is that they have either more bargaining power over the intermediaries, or in some cases, they can circumvent them altogether. So, you take an example like Taylor Swift, producing and distributing the Eras Tour movie by herself. Or, recently, Ryan Coogler negotiated with Warner Bros. to get back the master to his movie in 25 years. That’s pretty common in music, but it is almost without precedent in the movie business.

The third theme is about what happens when so much consumption moves to networks. Historically, most media distribution was one-way. It was delivered to consumers and there wasn’t much of a feedback mechanism. But of course, today, most consumption happens on two-way networks. And the most important thing about networks is that they’re subject to these really powerful positive feedback loops that make the strong, stronger. There’s both a supply-side and a demand-side dynamic here.

On the supply side, this results in these really powerful network effects which have created massively powerful platforms. We all know this, but the point on this chart (on the left) is that the market cap of the smallest platform, META, is bigger than the entire media industry combined. Then this chart (on the right) is showing you global ad revenues. It’s a little dated, because it’s for 2022, but the red bars are, again, media companies. The point here is that the biggest companies in media today are no longer media companies.

On the demand side, what’s happening is that networks tend to amplify popularity. The popular becomes more popular, and that’s partially because consumers use popularity as a signal of quality, and there’s also an element of social currency involved in consuming popular stuff. In any case, without going too deeply into it (see Power Laws in Culture for an in depth analysis), the point is that you end up with these really big hits. You end up with these big cultural touchstones, again, Taylor Swift or Barbenheimer or GTA 6, if and when it comes out. So even though the tail is getting longer because of fragmentation, the head is getting ever higher, and you end up with these really big hits and these power law or power law-like distributions.

This slide shows an analysis I did for box office in the U.S., demand for Netflix shows, Patreon patrons and streams on Spotify. What it shows is that in all cases, these distributions are very extreme, and in some cases, becoming even more extreme.

There are a couple of of negative implications for traditional media companies.

One is that the middle is going away. The middle is getting hollowed out and it’s historically been a very lucrative part of the business. Another problem is that the business is getting riskier because the distribution of returns is becoming more extreme. And the third problem is that the artists — the creators or creatives — at the very tippy top, of course they know they’re at the tippy top, and so they use that knowledge to extract more leverage than ever, as I was just discussing.

The fourth theme is the most hopeful for the media industry, but also the vaguest and furthest out. The idea is that there are going to be new media modalities, enabled by technology. In the essay, I talk about three categories of new modalities: more immersive experiences, more engaging experiences and those that create more time. The Apple Vision Pro has been a bit of a disappointment, but in theory, maybe eventually VR opens up a new software upgrade cycle for movies? Or could autonomous vehicles free up 40 or 50 minutes of commuting time for other uses? The problem here, of course, is that all of these things are unclear, pretty far out, and really hard to underwrite today.

To sum this up, the idea is that more attention will perennially shift into the tail, especially with the advent of GenAI; the bargaining power of traditional intermediaries is declining; you have this rising concentration of power in a handful of platforms and attention in a handful of hits; and you have this very vague hope of a brighter future.

This chart tries to answer the question that I posed at the very beginning, how value will be redistributed along the ecosystem. Without reading it, the bottom line is these themes are good for the very top creators. It’s really uniformly not good for the traditional intermediaries. They’re good for the platforms, although the question here is whether the size of the prize is big enough to move the needle for them. And they’re good for consumers in the form of more choice and lower costs.

Another way to look at it is this. Traditional media is getting squeezed on the one side by platforms that don’t really need to make money in media. A lot of them are using media to cross-subsidize some other part of their business. On the other side, there’s this infinite army of creators.

The Two Disruptions of TV

Now, I want to move to the second question I raised and talk about TV in the U.S. TV is going through those same kinds of dynamics I mentioned, but I want to talk a bit more about the ideas of fragmentation and disruption.

The one sentence summary here is that the last decade in TV and film was defined by the disruption of content distribution, and I think the next decade will be defined by the disruption of content creation.

Let’s walk through a quick history lesson. This is the video value chain, which is a more specific version of the generic media value chain that I showed earlier.

The value in any value chain is a function of the moats in the value chain, or the barriers to entry. That is a very basic economic concept, namely that if you have a business with no barriers to entry, then new entrants will come in and compete away profits. So, the moats are very important. And historically, there were two big moats in TV and film, one around distribution, because it is very capital intensive and expensive, and the other one around content creation — or what’s called here production — because it is also very risky and expensive.

Because of those moats, the TV business was a great business, one of the greatest businesses ever, but it was also ripe for disruption, if those moats fell.

In this slide, you can see (on the left) that it was one of the most profitable businesses ever and was arguably overearning. Cable Network margins were amongst the highest in the economy. On the upper right, you can also see that people were paying for stuff they didn’t use. This is data from Nielsen that that shows that in any given month, people were watching less than 10% of the networks that they paid for. And, on the bottom right, you see that cable price increases dramatically outstripped the CPI.

What happened, of course, is that internet came in, it unbundled information from infrastructure, and it caused the cost to move bits around to plummet. This graphic is meant to show the distribution moat getting shaky.

Netflix, as a proxy for all new video entrants, ran the whole disruption playbook. It started with deep library and then picked off kids and then unscripted, and today it is, I would argue, the most powerful company in Hollywood.

Let’s talk about the aftermath of that disruption, which the industry is struggling with today. This is a snapshot of the video business in the U.S.: traditional, streaming, box office and home entertainment, all indexed to $1. I think a surprising thing here is the relative resilience of traditional TV. Despite all the talk about Netflix and Hulu and Disney+ and FAST and CTV and Roku and all that stuff, linear TV still represents 66 cents of every dollar that is spent on video in the United States.

But, as is well understood, the linear business is under tremendous pressure. So, I won’t dwell on this. This chart on the upper left is a bit of an eye chart, but the purple line is the important one. It shows you pay TV penetration, which peaked near 90% a decade ago, which is before this chart starts, is now headed toward 50% of households. Linear viewing obviously has declined, as you can see on the right, other than sports. And the bottom chart shows that those declines have been the most dramatic among the youngest cohorts, which is obviously not a good leading indicator.

To offset this pressure on linear, all the big media companies launched their own streaming services, Disney+, Max, Peacock, Paramount+, and they have spent very heavily on content. You can see here content amortization is up a lot over the last five years, there’s been an explosion of originals.

But streaming has not proved to be the silver bullet a lot of people hoped. On the upper left, you can see that sub growth has been slowing. The reason it’s slowing is because of this chart on the upper right. Consumers seem to be kind of maxing out around four services per household, on average. That’s partly because some of them are using churn proactively, as a budget management tool. And so, as you can see on the bottom, churn is quite high and keeps going up. And that puts a lot of pressure on unit economics.

The most important and fundamental problem is this one: streaming just monetizes a lot less than pay TV. What this chart shows is the average pay TV household generates 3X as much subscription revenue and 7X as much advertising revenue as the average streaming household. On the ad side, that gap will close somewhat, because Netflix, Amazon and Disney have all added a lot of streaming advertising inventory, but even so, it will be very challenging for the gap to close all the way. This is something I’ve been writing about for the last, three, four years. The profit pool of streaming is just structurally smaller than pay TV.

The result of all of that is that video profits are down for the big media companies. What this chart is showing you is video revenue and EBITDA, for the largest media companies. In 2018, that was seven companies. Today it’s five companies, but it’s the same assets reconstituted.

So, this is all video — linear, streaming and studio, combined. Revenue is up a little bit, but profits are down 40%.

And of course, the big media companies’ stocks have suffered as a result.

So, let’s talk about what happens next.

As I said, historically, there were these two big moats, a moat around distribution and a moat around content creation, or production. All of the things we’re talking about are really the result of the distribution moat falling. When barriers to entry fell in distribution, new entrants came in and squeezed out excess profits. But all of the problems that exist in Hollywood today, in the broader entertainment business — whether it’s reduced production, the RSNs failing, the writers and actors strike, why did Paramount sell itself? Why did Bob buyer come back? — all of these things are lagging indicators of the last disruption. All of the current challenges in the business are occuring essentially because there is just less money to go around.

Because even as the barrier to entry around distribution fell, the moat around content creation actually got deeper and wider.

The reason is that even as the cost of distribution fell, content costs actually went up. You can see here that the cost for the median tentpole film doubled over 20 years. You can’t quite see it here, but the cost for an hour of premium scripted TV doubled over about 10 years.

Or, another way to look at it is this, is that distribution was on a downward sloping, technology-driven cost curve, and content creation wasn’t an upward sloping, labor-driven cost curve.

To put it differently, the left is Moore’s Law, and the right is medical insurance premiums and sushi. And so the question becomes, what happens if Moore’s Law comes for content creation, too?

That brings us, of course, to generative AI. I’m sure you’ve all seen the evolution of these models from the horrific images of Will Smith eating spaghetti 18 months ago to Sora and Minimax and Runway Gen-3 and Luma Dream Machine and all of the models that exist today, a new one of which seems to come out on a daily basis.

So, I’m not going to show you that, but I do want to show you some of the early commercial deployments, which I think are really interesting.

This is an ad for Toys R Us that was made using Sora, by an agency called Native Foreign. I will just play a part of it quickly. The point is that nothing here is real, it is all AI, and it shows how far we’ve come in such a short time.

This is a movie called Where the Robots Grow. It is billing itself as the first AI-enabled feature length animation, created by a studio called AiMation, and is 87 minutes long. They say that the team is only nine people, and it only cost $8,000 per minute. Of course, those are fractions of the labor and cost of a traditional animated production. One thing they very cleverly did is they use robots, so lip syncing is not that important. Is it Pixar? No. But might it be really entertaining if you’re five or six? Yeah. And clearly we’re getting closer. It’s streaming for free on YouTube, and I encourage you to check it out.

And so, again, the big question is that you you have already have an industry that is back on its heels from the last disruption, and what happens if this other moat also comes down.

Just to be clear, I’m not arguing that we’re going to see an AI generated blockbuster movie anytime soon. What I am saying is that if GenAI democratizes high quality content creation, it would just exacerbate the low-end disruption that’s already happening from creator content. On the left, you can see data that I think a lot of people have seen before. It shows you that YouTube is by far the largest streaming service in the U.S. to televisions. So, this doesn’t even capture PC and mobile. But you can see here that its share of streaming is larger than Disney+, Hulu, Peacock, Max, and Paramount+ combined.

On the right, what you can see here is a comparison of the viewership of Mr. Beast compared to the most popular shows on Netflix in the first half of last year. So, if you thought about Mr. Beast as a show, you would see that it is actually the most popular show in the world.

This is a redux of the disruption chart I showed before, for the next disruption.

Now you can see that Netflix goes from disruptor to disruptee. You see a visualization of the low-end disruption of professionally-produced content by creator content. It has already picked off the least demanding customers, kids. The most popular kids show in the world is CoComelon — on YouTube. The next least demanding customer is unscripted viewers, and the most popular unscripted show in the world, or maybe just show in the world, is Mr. Beast — on YouTube. And so the question is whether these tools (Runway, Sora, Flux, etc.) throw gas on the fire and enable creator content to continue moving up the performance curve?

I’m not saying that the sky is falling. I’m not saying that Hollywood is going away. What I am saying is that there is a risk that these models undermine the economic foundation of the business. I think for creatives, there’s less of a risk that Hollywood replaces you with AI; there’s a much greater risk that AI undermines the economics of Hollywood and pressures their budgets and ability to pay you.

Just to hammer home the point, here’s a recent movie made by just one guy, a five-minute short. His name is Dave Clark. I won’t play the whole thing. But I think the the key to keep in mind here, and the thing I always think about when watching these kinds of films, is that these are the worst that these tools are ever going to be. This is called Battalion and I would also encourage you to take the five minutes and watch this on YouTube.

One more thing to consider is that GenAI won’t only be used to make movies less expensively. It also has unique properties that will open up unique applications.

This is something I wrote about in my most recent post Gen AI Video as a New Form. Typically, when there’s a new medium, the first thing it’s used for is to imitate old media. The first radio broadcasts were just vaudeville and the first magazines online were just basically PDFs. But what happens over time is that the creatives learn to exploit the unique properties of the medium and do unique things, and I think that’s going to happen with GenAI as well.

So, when you start to think about what GenAI can uniquely do, obviously it’s going to be much less expensive, and so you’re going to have much more risk and more experimentation with formats and storylines, you’ll have broader representation, it’s going to open up fan creation in video. And then you get to a bunch of stuff that’s kind of hard to get your head around, at least it is for me. Questions like, what does it mean that video can be rendered real time? What does it mean that all video is inherently three dimensional? What does it mean that it’s unconstrained by physics?

I think it’s going to take a while for creatives to figure out how to exploit those things, to see what actually takes hold with consumers. But the bottom line here is that just as social video changed the definition of quality in video, I think GenAI will do the same thing. And that will just open up a yet another new vector of competition with professionally-produced content, new bases of competition.

When you draw the parallel between this disruption and the last one, you see that this one could happen a lot faster.

One reason is just simply internet scale. As I mentioned before, Hollywood put out 15,000 hours of content last year, and there were 300 million hours uploaded to YouTube. What that means is that only a very small percentage of that needs to be competitive with Hollywood. I’m not saying comparable, just competitive for time, to be really impactful. Consider that if just 0.01% of that 300 million hours is considered competitive with Hollywood, that’s 30,000 hours a year. That’s twice Hollywood’s annual output.

Another issue is that the last disruption required a huge lift in terms of infrastructure, both wireless and wireline broadband infrastructure. Consumers had to adopt broadband, they had to adopt streaming, they had to get connected devices to their TVs. All those things are now in place. So, if there was a great AI-enabled TV show released for free on YouTube, that could be the most popular show in the United States the next day.

The last point is that I think it’s very hard for the studios to adapt to this. That’s not a criticism of the studios, it’s really a commentary on the structural challenges. Maybe most important, when you draw these parallels — between the disruption of content distribution and content creation — creating content is much more core to what they do than distributing it. That’s just going to add to the complexity. They’re also very leery of any talent backlash, particularly after the strikes last last year. They’re very leery of running afoul of some of these unresolved legal questions. And so I think it’s just going to be a really, really challenging thing for the studios.

What Opportunities Will Emerge?

So, to finish up here and try to look at the at the light at the end of the tunnel. I think an important question is, well, okay, if you believe all this is happening, what opportunities will emerge? There aren’t easy answers here. But I think as a generality, the good news is that when one input into the production process becomes abundant, other things become scarcer and more valuable.

So what is scarce in a world of infinite content?

• Obviously, good ideas are still quite scarce.
• Distribution and curation will be more valuable than ever.
• Proprietary technology, which is a very broad topic.
• Consumer, time and attention is even more valuable. And keep in mind, linear TV still commands a lot of that.
• First party data.
• The ability to cut through the noise with with marketing.
• Human authenticity and provenance, the backstory of content, I think, is going to become more important than ever.
• The ability to create fandoms and community premium.
• IP.
• Libraries.
• IRL experiences, especially sports.
• And having talent relationships.

And, as shown, many of these things are accessible to traditional media companies.

So, I think this really is the challenge for everyone in the media business, to figure out what are the core competencies that they can lean into that become even more valuable as content becomes more abundant.

So, I will stop there. Typically, if I was giving this presentation live, we would now be able to discuss this, tease apart some of these issues and dig in deeper.

But even in the absence of that, I hope that you found this a good use of time.

Thank you.

Starting April 2025, all full posts, including archived posts, will be available on my Substack, The Mediator.

Twenty years ago, I wrote a research report arguing why internet video wasn’t a threat to traditional TV. Besides being wrong, it suffered from a failure of imagination. It equated the internet with being a new way to transport packages of cable networks. Among other things, I didn’t anticipate that the internet would birth new forms, notably including social video and live-streaming, which now represent ~25% of all video viewing in the U.S.

In Hollywood today, much of the discussion about GenAI centers around how you can use it to make movies and TV shows more efficiently:

• Which jobs are the most vulnerable to being replaced?
• When will it be possible, both technically and legally, to use it to replace some principal photography, as opposed to just used in pre- and post-production?
• How much will it really reduce costs?
• Will consumers embrace it and, if so, in what genres?

These are important and valid questions, but they all implicitly suffer from the same failure of imagination. They assume that the primary application of GenAI video is making the same old stuff in a new way. Over time, all new media move beyond mere imitation of older forms. Creators come to understand the unique properties of the new medium and use it to make entirely new things. The same will happen with GenAI video.

It’s hard to predict precisely how the technology will evolve or what will take hold with consumers. It will take time to figure it out. But by exploring the unique properties of AI video models, we can make some educated guesses.

Tl;dr:

• Viewing a new medium as merely a way to imitate an old form — also called skeuomorphism — is a common mistake in media.
• Most of the discussions about GenAI in Hollywood today also narrowly regard it as a new way to make TV shows or movies for less.
• But GenAI will birth new forms too. It’s impossible to predict these with precision, but by exploring the unique properties of GenAI video, we can make educated guesses.
• Cheap: GenAI will be orders of magnitude cheaper than traditional production, which will enable far more risk and experimentation; broader representation; A/B testing at scale; and fan creation.
• Dynamic: It can be rendered dynamically and, eventually real-time. This will open up contextual, personalized, interactive and possibly emergent or infinite stories.
• 3D: It isn’t tethered to the fixed perspective of each still frame, meaning that it will be possible to experience video from an unlimited number of perspectives, including within the action itself. Every viewer can be the cinematographer.
• Unconstrained: It also isn’t bound by physics or reality, meaning it will be capable of impossible shots, alternative realities, physics-defying environments and a lot of other stuff that’s hard to conceptualize.
• The scarcest resources in media are consumers’ time and attention. These new forms will inevitably compete for both. That’s an opportunity for those who understand it and a risk for those who don’t.

Click here to continue reading the full post on my Substack, The Mediator.

Starting April 2025, all full posts, including archived posts, will be available on my Substack, The Mediator.

Sports is one of the only bright spots in media today. Sports franchise valuations keep rising. NFL ratings are up so far this season. The NBA is basking in a successful rights renewal that saw new bidders emerge. Viewership of this summer’s Paris Olympics marked a huge rebound from the record-low numbers in Tokyo three years ago. More generally, sports are one of the only TV genres that still attract younger viewers.

Meanwhile, the talk of every boardroom and investor meeting is increasingly consumed with GenAI. What, if anything, does GenAI have to do with sports programming? The concept may seem like a contradiction in terms. GenAI is synthetic. Sports features real people doing real things in real life.

As I explain below, there are important applications of GenAI in sports that could enhance the fan experience, maybe boost revenue and, as a result, add another tailwind to the value of sports rights.

Tl;dr:

• The implications of GenAI for scripted entertainment and sports programming are very different. For Hollywood, it could prove a disruptive threat; for sports it’s an opportunity.
• Since the main appeal of sports is its authenticity, most GenAI use cases in sports programming relate to the creation of derivative or supplementary programming that enhances the sports viewing experience, not replaces it.
• These include real-time translation/localization; multi-modal conversion between combinations of text, audio, images and video; video augmented with GenAI, like dynamic real-time graphics and even virtual commentators; and the ability to create personalized feeds.
• Another (eventual) opportunity for the leagues is licensing footage for model training, which might be among the most valuable data licensing deals struck so far.
• An elephant in the room is the complex rights dynamics between leagues, teams, distribution partners, players associations and players. “AI rights” would need to clarified and codified for much of this to move forward.
• There isn’t much forcing the leagues to act, since GenAI is more opportunity than threat. But progressive leagues will figure it out.

This post is sponsored by WSC Sports.

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