From “Stage” to “Screen”: The Real AI Opportunity Most Companies are Missing

About a century ago, when motion pictures were invented, the first filmmakers did something entirely predictable. They pointed a camera at a stage.

One fixed angle. Actors entering and exiting from the wings. Performances delivered to invisible audiences. The technology was brand new, but the thinking was borrowed wholesale from the theater because that’s what people knew. It took decades before filmmakers began to realize what the medium could actually do, such as cutting between scenes, moving the camera, and telling stories that would have been impossible to do onstage. The technology was there long before the imagination caught up.

We’re living through this exact same moment with AI, but most companies haven’t realized it yet. While most companies are using AI to improve efficiency and customer experience, the real competitive advantage lies in using AI to create entirely new business models, which is something far too few organizations are prioritizing.

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Introducing: The stage play era of AI

There is a design concept called skeuomorphism. The idea is that when new technology emerges, we dress it up to look like whatever came before. Think about how digital calendars look like paper planners. Making something new feel like something we already understand is the natural human response to the unfamiliar.

AI is deep in its skeuomorphic era right now.

Ask most large companies how they’re using AI, and the answer is most likely a version of the same thing. They’re using it internally to “move faster” and “cut costs.” Maybe, if they’ve gone a step further, they’ll mention an improvement to customer experience. What you almost never hear is that they’re doing something genuinely new, be it a product, service, or business model, that couldn’t have existed before AI made it possible.

History is repeating itself: The technology has arrived, but the imagination hasn’t caught up yet.

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The hierarchy of AI applications in business

There are three main ways AI can be applied in an organization, and they are not created equal.

The first is efficiency, using AI to reduce costs, automate tasks, and do existing work faster and cheaper. This is where the overwhelming majority of corporate AI investment lives right now. It’s the easiest case to make in a boardroom, the easiest ROI to measure, and the most comfortable place to start. It’s also the least defensible long-term advantage you can build.

The second is customer experience, using AI to make your existing product or service meaningfully better for the people who use it. This is harder, more valuable, and still largely about improving what you already have.

The third, and the one almost no one is focusing on, is using AI to create entirely new business models. Revenue streams, products, and services that didn’t exist yesterday and couldn’t exist without AI. Not faster, not cheaper, not smoother. New.

The hierarchy here matters. Each application represents a larger opportunity and a bigger leap of imagination required to get there. Most organizations are pouring energy into efficiency, occasionally reaching customer experience, and almost entirely ignoring the potential for new business because they genuinely can’t see it yet. They’re still pointing the camera at the stage.

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Why big companies struggle to see past the stage

Large, scaled organizations are, by design, built to optimize. They have processes, incentives, reporting structures, and entire cultures oriented around protecting and improving what already works. That’s not a flaw; it’s how you run a large business. But it also makes it nearly impossible to imagine something fundamentally different from within.

When you ask a team inside a corporation to envision a new AI-enabled business model, not an improvement to an existing one, but something genuinely new, you’re asking them to do something their environment isn’t built for. The instinct is always to anchor to the existing business, and so the output is always some variation of what already exists, only faster or cheaper.

There’s also the seductive comfort of “wait and see.” It sounds measured. Prudent, even. But in a landscape moving this quickly, waiting isn’t a neutral position; it’s a losing one. The companies that are building AI-native business models right now aren’t waiting for the technology to mature or the strategy to crystallize. They’re building, learning, and establishing advantages that will be very difficult to replicate later.

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The new playbook

While incumbents optimize, a different group is doing something else entirely. Startups and venture builders, unburdened by existing business models, legacy systems, or the pressure to protect current revenue, are asking a fundamentally different question. Not “How do we apply AI to what we already do?” but “What becomes possible now that wasn’t possible before?”

The answers they’re arriving at are businesses that couldn’t have existed in any prior era. AI-native models built from the ground up around capabilities that are entirely new. They’re not filming stage plays. They’re learning what the camera can actually do.

The gap between these new entrants and the incumbents watching from the sidelines is widening, quietly and quickly, every day that the larger organizations stay in efficiency mode. So what does a large organization actually do with this?

The honest response is that you probably can’t solve this problem from inside your existing structure, and that’s okay, as long as you’re willing to build outside of it. Running AI experiments as ventures, such as distinct, startup-like entities with their own mandates, teams, and freedom to imagine, is one of the few mechanisms that gives a scaled company a real shot at genuinely new thinking.

The goal of those ventures isn’t to improve the core business. It’s to ask what the core business could look like if it were built from scratch today, with AI at its center. It’s to step outside the theater entirely and figure out what the movie looks like.

This isn’t easy. It requires organizational will, patient capital, and leadership that genuinely believes the biggest opportunity isn’t in the efficiency gains on next quarter’s earnings call. But it’s the only path to the kind of growth that AI actually makes possible.

The stage play era of cinema lasted until enough people had spent enough time with the new medium to understand what it could actually do, and then everything changed.

We are somewhere in the middle of that same transition with AI. The technology is here. The early adopters are mostly using it to do familiar things in familiar ways, only faster. And somewhere, the filmmakers who will define the next era are starting to move the camera. It’s time to focus on what could be possible that wasn’t before, and then build for that.

Because the stage play era won’t last. It never does.