The excitement surrounding artificial intelligence is fundamentally simple to understand: AI represents a transformative platform, similar to the personal computer, the internet, mobile devices, and cloud computing before it. If we could return to the early days of the web or mobile computing, most of us would invest far more heavily than conventional wisdom suggested at the time. AI is driving a similar super-cycle of evolution, with unprecedented investment and attention because we now understand how these platform shifts reshape industries. This evolution will be outsized in the media industry.

The Evolution of Platform Innovation

We're currently in a phase where most executives and organizations are simply reimagining existing processes with AI technology. This mirrors the early days of mobile, when companies rushed to convert their existing operations into apps. While this phase brings exciting capabilities, the true transformation comes later, when innovators break free from conventional thinking to create entirely new paradigms. Uber didn't merely add mobile technology to traditional taxi services—it reimagined transportation entirely. Similar revolutionary changes came from Instagram, Pokemon Go, Waze, DoorDash, TikTok, and Venmo.

Addressing AI's Impact on Copyright and Employment

The transformative potential of AI has naturally sparked concerns about its impact on copyright and jobs in the media industry. Copyright concerns are real, and it will take time for leading legal minds to untangle them.

On jobs, Evan Shapiro astutely noted: "The conversation about AI in entertainment focuses too heavily on job replacement rather than job enhancement. While some positions will be displaced by AI, and our lives will generally improve through its implementation, most AI-driven changes in media will be neither as dramatic nor as revolutionary as current rhetoric suggests. AI's greatest contribution to media will be both ubiquitous and remarkably practical." Well said, Evan.

5 Areas Where AI Will Change Media

With all that in mind, I’d like to discuss five areas where AI will change the media industry.

1. Generative AI (Production)

Let’s start with generative AI, since so much of the heat, light, energy and fear in media is focused here. Generative AI is revolutionizing content creation, not by replacing creators but by empowering them with new tools. We're already seeing impressive examples, such as Michaela Ternsky-Holland's The Christmas Recipe, created using generative AI. Companies like ElevenLabs and Deepdub are transforming localization by scaling dubbing and subtitle production across languages. Organizations like Adapt are making these capabilities accessible to traditional Hollywood workflows.

Generative AI applications extend beyond areas like video generation and localization to include:

• Screenwriting and story development

• Storyboarding and pre-visualization

• Cinematic universe expansion

• Cross-medium adaptations

• Marketing and promotional content

I'm excited to see how the next generation of creators use the full spectrum of generative AI tools to create compelling new content.

2. Content Operations

A truly staggering amount of work is done to prepare media for global distribution… Slate and language validations. Metadata cleanup, hydration, and prep. Media quality control on many levels. Deduplication. Conformance and alignment. Sidecar management. Image prep, QC, and packaging. Compliance assessments, editing, and management. Ad marking and segmentation. Dub card processing. Fulfillment packaging.

AI is transforming these traditionally manual processes by augmenting human operators with powerful automation tools—like giving these operators a specialized Halo suit. This enhancement will help media companies improve efficiency and reinvest in content creation. AI will also enable legacy media players to restore and optimize valuable, but highly fragmented, content libraries that bear the scars of decades of independent distribution models.

There's much to explore around content operations and AI, so I will write a dedicated post on the areas where content operations teams can best leverage AI and enhance their output significantly.

3. Hyper Enrichment

AI-powered content analysis tools from companies like Coactive and Twelve Labs (not to be confused with ElevenLabs referenced above) enable unprecedented depth of understanding of media assets. This technology can analyze content frame-by-frame and scene-by-scene, generating rich metadata that extends far beyond traditional IMDb-style information.  This level of detail will be incredibly powerful on multiple levels, supporting advanced optimization strategies, enhancing how content libraries interact with large language models (LLMs), and creating new business models and revenue streams.

Worth noting: Simply amassing a mountain of detailed info alone is not particularly useful. That data must be normalized and standardized so others can use it predictably. (This gap presents an opportunity for a media ecosystem supplier to fill that void.) Data normalization will be key to how content holders expose info about their libraries to LLMs, large and small. The Hollywood players who figure that out early will be best able to control their economics, outcomes and destinies for what’s ahead.

4. Performance Optimization

Hyper enrichment can enable entirely new levels of optimization both upstream and downstream of media supply chains. It’s easy to understand that the next level of consumer recommendations could be powered by expanding the “surface area” of content details to better understand what a consumer responds to. It’s also valuable to identify precise correlations between key events (like information about a scene where a user stopped watching or details about the last scene they watched before canceling a subscription.)  Or, to identify, with deep precision, the scene clips that will entice a consumer to watch a title.

Advertising engines could use hyper enrichment information to bring content context to optimize ad decisioning in new, automated ways. Imagine if an ad engine could know that an ad break follows a scene with high positive correlations to air travel, alcohol, and sunglasses. Negative correlations could also be conveyed for placement avoidance, like perhaps a car crash for automotive. If the conveyance of that detail can be automated and standardized, it will power new levels of ad relevancy.

Optimization opportunities also exist upstream. Financial analyses for greenlighting and investment decisioning can incorporate new levels of precision and sophistication. Content development can also use such information for scene selection decisions, with a better understanding of “what works” and what doesn’t, with even greater target audience specificity.

5. Interfaces

One of the most underappreciated aspects of AI's impact on media is its potential to revolutionize how consumers interact with content. Just as the web enabled Netflix and YouTube, and mobile enabled Spotify and TikTok, AI will likely spawn new disruptive players in the media ecosystem. Consider whether you expect to spend 10 more years sifting through carousels of shows, movies, artists, and playlists to find something. The carousel paradigm is useful, but it can be cumbersome and often not all that satisfying. I can imagine new interaction models where you tell your TV what you’re in the mood for and let a guided tour evolve conversationally from there.

We’re just now seeing the start of it. Google announced that Gemini AI will be integrated into Google TV devices. Google plans to deploy far-field microphones to enable ambient conversational interface. That’s notable, and it’s fodder for a dedicated post or two on the evolution that AI may bring to user interfaces.

Looking Forward

The transformation of media through AI extends beyond these five directions. As we move past simply recasting existing processes with new technology, we'll see entirely new paradigms emerge. The most successful organizations will embrace AI not just as a tool for enhancement, but as a catalyst for reimagining what's possible in media creation, distribution, and consumption.