Look Up
A few months ago, I gave a talk at a media conference. I opened by asking the audience how many of them had ever learned to race a car on a track.
One of the first things you learn is to look up. If you focus only on the next turn, you won't be set up for what comes after. You have no shot at being in the right position if you can't see where you need to go - and if you're in the wrong position, you won't be able to react in time.
That's what AI feels like for a lot of us right now.
The best leaders acknowledge that change is coming, but acknowledgment isn't enough. You're leading an organization through a transition, and this time much of your team will actively resist. That resistance isn't irrational - the old way worked just fine, and "we need to be more efficient" isn't a compelling reason to upend how people work.
Efficiency isn't the point. The requirements of the entire organization themselves are shifting. The game is changing, and AI isn't about doing the old job faster - it's the only way to attempt to play the new game at all.
When people understand that, something unlocks. They stop seeing AI as a threat to their role and start seeing it as the thing that makes an impossible job possible. AI typically absorbs the most tedious parts of the work while leaving people free to do what they actually came here for - exercise judgment, embrace creativity, and deliver more than they ever thought possible.
Your job as a leader is to paint that picture. Not "here's why you don't need to worry" but "here's the future we're building and why you're essential to it."
So let's look up and talk about where the track goes from here.
The Road Ahead
Storytelling is Evolving
The way stories get told is changing faster than at any point in living memory.
For decades, formats were relatively stable. You had your print piece, your TV package, your radio spot, your digital article. Each had conventions, expectations, and constraints that professionals spent careers mastering. The formats evolved, but slowly enough that expertise accumulated.
That stability is ending. Short-form vertical video was niche just a few years ago; now it dominates how a generation discovers and consumes content. Interactive formats, choose-your-own-path narratives, AI-generated personalized summaries - these aren't experiments anymore. They're expectations forming in real time.
The change isn't just about new formats appearing. It's about the cycle time of format evolution itself compressing. What used to take a decade now takes two years. Platforms rise and fall, audience behaviors shift, and the "right" way to tell a story becomes a moving target.
This rewards adaptability over mastery of any single form. The organizations that thrive won't be the ones that perfect one format - they'll be the ones that build systems capable of expressing ideas across whatever formats emerge, including ones that don't exist yet.
Amplification Opens New Territory
For most of media history, distribution constraints forced brutal choices. You could produce in one language or maybe two. You could target one market deeply or several markets superficially. You could create one format and hope it traveled. Every expansion meant proportionally more cost, more staff, more complexity.
Those constraints are dissolving. AI-powered localization doesn't just translate words - it adapts tone, context, and cultural reference. A single piece of source content can become native-feeling versions for dozens of markets simultaneously. Formats that once required dedicated teams can be generated as variations of a single production effort.
The result is that the addressable market for any given story just got much larger. Content that previously couldn't justify production economics now can. Audiences that were too small or too dispersed to serve profitably become reachable.
This sounds like opportunity, and it is. But it also means the job changes. You're no longer deciding what to make - you're deciding what not to make across a vastly expanded possibility space. The editorial challenge shifts from "can we reach this audience?" to "should we, and with what, and how does it fit with everything else we're doing?"
More content isn't optional. It's the natural consequence of constraints lifting. The question is whether you'll produce that content intentionally or let the possibility space overwhelm you.
Speed Becomes the Baseline
The time between event and publication is compressing toward zero.
This has been happening for years, but AI accelerates it dramatically. Automated monitoring, instant transcription, automated content analysis, AI-assisted drafting, AI-assisted video editing - each removes friction from the production pipeline. What once took hours can happen in minutes. What took minutes approaches real-time.
Here's what's easy to miss: speed isn't a competitive advantage for long. When everyone has access to the same acceleration tools, being fast just gets you to parity. The first wave of adopters gain an edge, but that edge erodes quickly as the tools proliferate.
This doesn't mean speed stops mattering. It means speed becomes table stakes - the minimum requirement to stay in the game, not the thing that wins it. If you're not fast, you're not in the conversation. But being fast alone won't differentiate you.
The organizations that fixate on speed as the goal will find themselves in a commodity race, competing on timing while missing larger strategic questions. Speed toward what? First to publish what kind of content, for what audience, building toward what position?
Trust Becomes the Differentiator
When production is abundant and speed is universal, what's left?
Audiences aren't stupid, they already sense that something has shifted. Many encounter AI-generated content daily on social media. The uncanny valley of synthetic media is shrinking, but skepticism is growing to match. People are increasingly asking who made this and why should I believe them?
This is the new scarcity. Not content, not speed, not even reach. Trust.
Brand has always mattered in media, but it's about to matter in a different way. When anyone can produce content that looks professional, the production values themselves stop signaling quality. What signals quality instead is track record, transparency, consistency, and the institutional reputation behind the content.
Your audience will start asking harder questions: Where did this come from? What's the source? Is this a real person? Has this organization been reliable before? Can I see the provenance?
The companies that invest in answering those questions - through verification infrastructure, transparent methodology, consistent editorial voice, authentic human presence - will build moats. The companies that don't will find themselves competing on cost and speed against an infinite supply of content that's cheaper and faster than anything they can produce.
Authenticity isn't a marketing buzzword in this landscape. It's the whole ballgame.
Why Most Will Get It Wrong
Understanding the landscape is necessary but not sufficient. Every executive at every media company has heard some version of what I've just described - at conferences, in board decks, from consultants and vendors.
And yet most organizations will navigate it poorly. Not because they're unaware, but because awareness doesn't automatically translate into correct action. The instincts that served leaders well in the previous era could actively mislead them in this one.
Here's where the track turns in ways that aren't obvious.
The Speed Trap
When you see speed becoming essential, the natural response is to optimize for velocity. Faster production, faster publishing, faster everything. This feels like the right move. It isn't.
Speed is the most visible dimension of change, which makes it the most seductive to chase. You can measure it. You can show progress. You can point to cycle times dropping and feel like you're winning the transition.
But speed without strategic clarity just gets you to the wrong place faster. The companies optimizing purely for velocity will find themselves publishing more content, faster, into a void. They'll win the race to be first with commodity coverage that nobody values. They'll burn resources being fast at things that don't matter while being slow at things that do.
The question isn't "how do we go faster?" The question is "fast toward what?" What position are you trying to reach? What does your track look like three turns ahead? Speed is a capability in service of strategy. Mistaken for a strategy itself, it's a recipe for expensive irrelevance.
Your Pilots Will Fail
Right now, every major media company is running AI pilots. Small experiments. Proof of concepts. Innovation labs testing tools and workflows. Most of these will fail to produce meaningful transformation.
Not because the technology doesn't work - it does. Not because the teams aren't talented - they usually are. They'll fail because they're testing AI inside workflows that were designed for human constraints.
Think about what you're actually doing when you run a typical pilot. You take an existing process - say, producing a video package - and you ask "where can AI make this faster or cheaper?" You slot AI into the existing sequence of steps. You measure whether it reduces time or cost at that step. Maybe it does, and you call the pilot a success.
You've asked whether a car is better than a horse by making it drive on bridle paths.
The power of AI isn't that it just does your existing tasks more efficiently. It's that it enables entirely different tasks, different sequences, different approaches to the same underlying goal. When you test AI within the constraints of your legacy workflow, you're artificially limiting what it can show you.
The pilots that will actually transform organizations start from a different question: "If we had no legacy constraints - no existing workflow, no current team structure, no sunk costs in how we do things today - how would we approach this goal from scratch?" Work backward from that. Then figure out how to migrate toward it.
This is harder than slot-in-and-measure. It requires imagination, not just evaluation. It asks you to question the workflow itself, not just optimize it. Most organizations aren't structured to do this kind of thinking, which is why most pilots will produce incremental improvements while competitors who think differently leap ahead.
The Inversions You're Not Ready For
Here's what makes this transition particularly treacherous: the things that made you successful are becoming liabilities, and the things you've neglected are becoming essential.
The competitive advantage inversion. For decades, media companies built moats around production capability, distribution relationships, and speed to market. You invested in studios, equipment, talent pipelines, and platform partnerships. These were expensive, hard to replicate, and genuinely valuable.
In the AI era, production capability is commoditizing rapidly. Distribution is increasingly disintermediated. Speed, as we've discussed, becomes table stakes.
So what becomes the new moat? Things most companies have neglected or actively deprioritized: clean metadata and content architecture. Clear rights frameworks and consent structures - because AI systems need unambiguous permissions to train on, remix, and redistribute content at scale, and the companies that have this sorted will move faster than those still untangling decades of licensing ambiguity. Institutional voice and editorial identity that's genuinely distinctive. Deep audience relationships built on trust rather than algorithmic reach. Archives that are organized, accessible, and machine-readable rather than sitting in digital graveyards.
Most media companies are asset-rich and infrastructure-poor in exactly the wrong ways. They have vast content libraries that are functionally inaccessible. They have brand names that lack distinctive editorial voices. They have audience reach without audience relationship. The work ahead isn't building new capabilities - it's excavating and organizing what you already have, while building the trust architecture you've underinvested in.
The talent inversion. The skills that got people hired - fast production, technical editing expertise, format-specific mastery - are the skills most directly in the path of AI development. Whether AI handles them well today is almost beside the point; the trajectory is clear, and the gap is closing fast. Meanwhile, the skills that were "nice to have" or even dismissed as soft - creativity, taste, judgment, ethical reasoning, systems thinking, narrative instinct - are becoming the core of what humans uniquely contribute.
Look at your hiring criteria from the past five years. Look at your promotion decisions. Look at who gets rewarded and why. In most organizations, these structures were built for a different world. The people who thrived were the ones who could produce quickly and reliably within established formats. That made sense when production was the bottleneck.
The people who will thrive in the new world are different. They're the ones who can see the whole board, who can make judgment calls without clear precedent, who can direct and evaluate AI outputs rather than produce directly, who can hold editorial standards across infinite variations. These skills have always been valuable, but they've often been secondary to raw production ability.
Some of your best future performers are currently undervalued. Some of your current top performers will struggle with the transition - not because they lack talent, but because their talents are optimized for a world that's shifting beneath them. This is also an opportunity: the chance to elevate people who've been overlooked, to build teams around judgment and vision rather than just output velocity.
If you don't evolve your talent model intentionally, you'll discover the mismatch the hard way - through failed initiatives staffed with the wrong skills for what the work has become.
The Choice
At the end of that session, I told the audience: if you only paid attention to one thing I said today, let it be this.
Our industry is evolving and something new is coming. We don't know exactly what it looks like yet, but we have clues: hyper-personalization, massively expanded content output, new form factors, content that adapts to context and audience in real time. The building blocks are here. The shape is emerging.
The time is coming to decide whether you're going to continue operating the legacy business you've always had, or commit to building the new thing alongside it.
I want to be honest about both paths.
You can stay the course. You can remain solely a newspaper, a broadcaster, a digital publisher, whatever you are today. You'll be fine for a while. Your existing audience will stick around longer than the doomsayers predict. But that audience will shrink, and new people aren't coming. Your business becomes a fierce battle of customer retention, optimizing for a declining base. That's a viable strategy. It's just not a growth strategy.
If you want to build the new thing though, you have to commit. Halfway in is the worst place to be. You'll burn through an incredible amount of money, you won't move fast enough, and you'll watch fully committed players iterate past you and win what is likely a winner-take-most market. We've seen this movie before. A lot of legacy media companies got stuck in exactly this pattern with the early Internet, then again with social media. Many never recovered.
The middle path feels safe. It isn't. It's where resources go to die.
So look up. See where the track goes. And decide which race you're in.
This is part three of a series on the Media Singularity. Follow us to get notified about future installments.