About the Author
Josh Linkner is a five-time tech entrepreneur, New York Times bestselling author, and globally recognized innovation expert. He has founded or co-founded five tech companies that sold for a combined value of over $200 million, and is co-founder and Managing Partner of Muditā Venture Partners, an early-stage venture capital firm. As Chairman of Platypus Labs, Josh helps organizations across industries build cultures of innovation and creative problem-solving.
In This Article
- Five macro shifts reshaping the industry, from AI-powered content generation to the legal battle over who owns the raw material that AI models are trained on
- Real examples of AI at work: Netflix’s billion-dollar recommendation engine, Lionsgate’s first-of-its-kind AI production partnership with Runway, the Associated Press’s automated newsroom, and more
- Three developments to watch over the next 12-36 months
- Why human creativity and judgment still matter more than any algorithm
- A 90-day action plan for media leaders ready to move
The media industry has survived the collapse of print advertising, the rise of streaming, and the seismic disruption of social platforms. It will survive artificial intelligence too, but the industry on the other side will look fundamentally different from the one we know today.
AI has moved squarely into the daily operations of newsrooms, studios, streaming platforms, advertising networks, and content creators of every size. According to the Reuters Institute’s 2026 Journalism, Media, and Technology Trends report, 97% of media executives now rate back-end AI automation as important to their operations, and 82% consider AI-powered newsgathering a priority. Meanwhile, Deloitte’s 2026 TMT Predictions project that the agentic AI market alone will reach $8.5 billion in 2026 and potentially $45 billion by 2030, with media and entertainment among the sectors most aggressively investing.
However, the investment story only tells half the picture. AI is simultaneously the force disrupting media’s business models and the most powerful tool available to build new ones. It is reshaping how content is created, how audiences are reached, how advertising is bought and sold, and how the legal boundaries of ownership are defined.
Here’s what you need to know.
Five Ways AI Is Changing Media
1. Content Creation Has Been Democratized, and Disrupted
The most visible impact of AI in media is also the most disruptive: generative AI has made it possible for anyone with a laptop to produce text, images, audio, and video at a quality level that would have required a professional team just two years ago. Adobe reported that its Firefly generative AI models had been used to create over 24 billion assets by mid-2025, making it one of the most widely adopted creative AI tools in professional media workflows. Meanwhile, AI video generation tools from companies like Runway, Sora, and Pika attracted over $1 billion in combined funding by mid-2024, signaling massive capital flowing into the infrastructure of AI-generated media (though OpenAI recently announced it is shutting down Sora).
The implications for traditional media organizations are profound. According to the Reuters Institute’s 2026 report, nearly one in ten of the fastest-growing YouTube channels now feature only AI-generated video content, and TikTok hosts over one billion AI-generated videos. That’s what the current competitive landscape looks like, and every media leader needs to understand what it means for their content strategy, their cost structure, and their audience’s expectations.
2. Audience Personalization Has Become the Product
For decades, media companies distributed the same content to every viewer, listener, or reader. AI has inverted that model entirely. Personalization has become critically important for platforms that want to win the attention war.
YouTube’s recommendation algorithm drives over 70% of total watch time on the platform. Netflix’s AI-powered recommendation engine influences roughly 80% of the content watched by its subscribers and saves the company an estimated $1 billion per year in reduced churn. Spotify’s AI DJ, now available in over 60 markets, delivers a personalized radio-style experience powered by generative AI, while the platform’s recommendation algorithms influence a significant share of all listening.
The competitive implication is clear: media companies that cannot deliver personalized experiences at scale will lose audience share to those that can. This is not limited to streaming giants. Local publishers, podcast networks, and niche media brands are all facing the same pressure to move from one-size-fits-all to algorithmically tailored content delivery.
3. The Newsroom Is Being Rebuilt from the Inside Out
AI is changing journalism at every level, from how stories are discovered to how they are written, verified, and distributed. The Associated Press has been a pioneer in automated journalism since 2014, using AI to generate roughly 40,000 automated earnings reports per year, up from approximately 300 per quarter when journalists wrote them manually. That model has since expanded to sports recaps and other structured data reporting.
According to the Reuters Institute’s 2026 survey of 280 senior newsroom executives across 51 countries, 82% now prioritize AI for newsgathering, and 81% emphasize faster coding and product development. However, the results so far are mixed: 44% describe their AI initiatives as “promising,” while 42% say results remain “limited.” This gap between ambition and execution is one of the defining challenges for media organizations.
The stakes extend beyond efficiency. Google search traffic to news sites fell 33% globally between November 2024 and November 2025, and publishers expect a further 43% decline in search engine traffic over the next three years. AI-powered search summaries are replacing the click-through traffic that has sustained digital journalism for two decades. Media organizations that don’t adapt their distribution strategies will find their audiences captured by AI intermediaries rather than their own platforms.
4. Advertising Has Entered the Autonomous Era
Advertising has long been the economic engine of the media industry, and AI is fundamentally reshaping how it works. Google’s Performance Max campaigns, which use AI to automatically generate ad copy, images, and video assets, have been adopted by a majority of Google Ads advertisers, with Google reporting increased conversions at similar cost per action. Meta’s Advantage+ suite automates ad targeting, creative generation, and placement, delivering what Meta reports as a 32% higher return on ad spend compared to manual campaigns.
The shift toward autonomous advertising is accelerating. Deloitte projects that podcast and vodcast ad revenue will reach approximately $5 billion in 2026, a nearly 20% year-over-year increase, driven in part by AI-enabled dynamic ad insertion and targeting. The ad-selling media platforms that can offer AI-powered targeting, measurement, and optimization will capture a growing share of ad budgets. Those still relying on traditional sales models will find themselves competing for a shrinking pool.
5. The Copyright Battle Is Defining Who Owns the Future
Perhaps the most consequential development in AI and media is not technological but legal. The question of whether AI companies can train their models on copyrighted media content without permission or payment is being litigated right now, and the outcome will shape the industry for a generation.
The landmark case is The New York Times v. OpenAI. Filed in December 2023, the lawsuit alleges that millions of Times articles were used to train GPT models without permission. In March 2025, a federal judge rejected OpenAI’s motion to dismiss, allowing the main copyright infringement claims to proceed. In January 2026, a judge affirmed an order compelling OpenAI to produce 20 million anonymized ChatGPT logs in discovery.
Separately, an EBU study cited by the Reuters Institute found that AI-generated content from platforms like ChatGPT and Gemini misrepresents news approximately 50% of the time.
This isn’t simply a legal footnote. The resolution of these cases will determine whether media companies are compensated for the content that makes AI systems valuable, or whether their intellectual property becomes free training data for competitors. Every media leader should be paying close attention.
How AI Is Actually Being Used Today
Netflix’s AI-Powered Recommendation Engine
Netflix’s recommendation system remains one of the most impactful examples of AI in media. The platform’s AI algorithms influence approximately 80% of the content watched by subscribers, personalizing not just which shows are suggested but which thumbnail artwork is displayed to each individual user. Netflix estimates that this system saves the company roughly $1 billion per year by keeping subscribers engaged and reducing the likelihood they will cancel. The company runs hundreds of A/B tests simultaneously to refine its personalization, making the recommendation engine one of the most continuously optimized AI systems in the media industry.
Lionsgate and Runway’s AI Production Partnership
In September 2024, Lionsgate announced a first-of-its-kind partnership with Runway, the AI video generation company, to build a custom AI model trained on Lionsgate’s library of more than 20,000 film and television titles. The model is designed to help filmmakers, directors, and creative talent with storyboarding, background creation, and special effects. Lionsgate’s Vice Chairman told Variety that the technology could save the studio “millions and millions of dollars” on pre-production and post-production work. By November 2024, filmmakers at the studio were already using the AI tools in active productions. This deal represented the first major collaboration between a Hollywood studio and an AI video generation company, and it set the template for how the production side of the industry may evolve.
The Associated Press and Automated Journalism at Scale
The Associated Press has been at the forefront of AI-assisted journalism for over a decade. Using AI systems originally developed through a partnership with Automated Insights, the AP generates roughly 40,000 automated earnings reports per year, a roughly 12x increase in output compared to the approximately 300 stories per quarter that journalists wrote manually before AI adoption. The AP has since expanded automated coverage to minor league baseball game recaps and other data-driven reporting. In parallel, the AP signed a licensing deal with OpenAI, granting access to its news archive while exploring how generative AI tools can assist newsroom operations. This dual approach, using AI to scale output while licensing content to AI companies, may represent the most pragmatic model for news organizations navigating the current landscape.
Spotify’s AI-Driven Personalization
Spotify’s AI DJ, launched in 2023 and powered by OpenAI’s generative AI technology, delivers a personalized radio-style experience with a realistic AI voice that introduces songs and explains why they were selected. The feature is now available to Premium users in over 60 markets. Spotify has also expanded into AI-generated playlists in 40+ markets, where users describe a mood or moment in natural language and the system builds a custom playlist in seconds. The company also piloted AI-powered podcast translation using voice-cloning technology to translate podcasts into multiple languages while preserving the host’s original voice. These features represent a shift from static content delivery to dynamic, AI-curated media experiences that adapt to each listener in real time.
What’s Coming Next: Three Moves to Watch (12-36 Months)
1. AI-Generated Video Will Move from Novelty to Production Infrastructure
AI video generation tools have improved dramatically over the past 18 months, and the next phase is integration into professional production workflows. Deloitte’s 2026 TMT Predictions forecast that studios will adopt generative AI for dubbing, translation, script evaluation, location scouting, and virtual production to enable cheaper and faster workflows. The Lionsgate-Runway partnership is the first proof point, but expect more studio deals in 2026 and 2027. Meanwhile, Deloitte projects that microdramas, short-form AI-friendly serials, will more than double in revenue from $3.8 billion in 2025 to $7.8 billion in 2026. For media executives, the question is not whether AI-generated video will become a standard production tool, but how quickly your organization will develop the capability to use it effectively.
2. Agentic AI Will Reshape Media Workflows
The concept of agentic AI, systems that don’t just answer questions but independently execute multi-step tasks, is moving from research labs into media operations. According to the Reuters Institute, 75% of media executives expect agentic AI tools to have a “large” or “very large” impact on the news industry in the near term. Deloitte projects that as many as 75% of companies will invest in agentic AI by the end of 2026.
In media, this means AI agents that can monitor breaking news feeds and draft initial coverage, optimize content distribution across platforms in real time, manage ad inventory dynamically, and handle routine editorial workflows without human intervention. The organizations that build the infrastructure for agentic AI now will have a significant operational advantage as these systems mature over the next two to three years.
3. The Copyright Question Will Set the Rules for a Generation
The legal battles currently working through the courts will determine the economic relationship between media companies and AI platforms for decades to come. The New York Times v. OpenAI case is the bellwether, but it is one of over 50 copyright lawsuits filed against AI companies as of late 2025. No summary judgment decisions on fair use in AI training are expected until summer 2026 at the earliest.
In parallel, regulation is moving forward. The EU AI Act’s transparency requirements, which mandate clear labeling of AI-generated content including deepfakes, take effect in August 2026. The FCC has already ruled that AI-generated voices in robocalls are illegal, and the SAG-AFTRA contract negotiated after the 2023 strikes requires studios to obtain consent and provide compensation for AI-generated digital replicas of performers. Media leaders who proactively build licensing frameworks and governance policies now will be better positioned regardless of how the legal landscape settles.
The Human Factor: Why Creativity Still Wins
With all of this technological change, it’s tempting to conclude that the future of media belongs to whoever has the best algorithm, but it doesn’t. It belongs to whoever combines the best tools with the most creative, adaptable human thinking.
In my work with leaders across industries, I’ve seen a consistent pattern: the organizations that thrive in periods of disruption aren’t necessarily the ones with the biggest technology budgets. They’re the ones that cultivate what I call a Find A Way™ mindset, an organization-wide commitment to creative problem-solving that prioritizes agility over brute force and improvisation over perfect planning.
In media, this matters enormously. AI can generate a news article from structured data in seconds, but it takes a human to recognize the story behind the data that readers actually care about. AI can recommend content with 80% accuracy, but it takes a human to greenlight the unconventional show that creates an entirely new audience. AI can produce a synthetic voice that sounds remarkably real, but it takes a human to build the trust and authenticity that keeps audiences coming back.
The Coca-Cola AI holiday ad controversy in late 2024 is instructive here. The company used generative AI to recreate its iconic “Holidays Are Coming” commercial, and the result drew widespread backlash for its uncanny, artificial quality. The technology was impressive. The creative judgment was missing. That gap between what AI can produce and what audiences actually value is where human creativity remains irreplaceable.
Start small and start now. Maybe it’s your editorial team running a 90-day pilot on AI-assisted content tagging and metadata generation. Maybe it’s your ad sales team testing an AI-powered campaign optimization tool for one advertiser before rolling it out across the portfolio. Maybe it’s a cross-functional workshop where journalists, product leads, and audience analysts work together to identify the three AI use cases most likely to move the needle in the next 12 months. The breakthroughs accumulate, but only if you start accumulating them.
A 90-Day AI Action Plan for Media Leaders
1. Pick One High-Friction Problem and Solve It Well
Don’t attempt to “do AI” across your entire operation simultaneously. The Reuters Institute found that while 97% of media executives rate AI automation as important, only 13% describe the impact of their AI initiatives as “transformational.” The organizations converting AI ambition into operational results are the ones going deep on specific use cases rather than spreading themselves thin. Choose one workflow, whether it’s automated content tagging, AI-assisted audience segmentation, or predictive scheduling for social distribution. Define your success metrics before you start, prove value, then scale.
2. Audit Your Data and Distribution Infrastructure
AI is only as good as the data it runs on. In media, this is particularly acute: content management systems often run on legacy architectures with poor metadata, and audience data is frequently siloed across editorial, advertising, and subscription systems. Before purchasing another AI platform, invest in getting your data foundation right. With Google search traffic to news sites down 33% in a single year and publishers expecting a further 43% decline over the next three years, the organizations that understand exactly where their audience comes from and how to reach them directly will have a structural advantage over those still relying on search referrals.
3. Train for Judgment, Not Just Tools
The biggest mistake media leaders make with AI adoption is treating it as a technology initiative rather than a people initiative. Your team needs training not just on which AI tools to use, but on when to trust AI outputs, when to apply human editorial judgment, and how to communicate AI-driven decisions to audiences who may be skeptical. The Reuters Institute found that 67% of news organizations report no job reductions from AI efficiencies, which suggests the technology is augmenting rather than replacing human work. Build a change management framework for your AI rollout. It will pay dividends long after the current generation of tools is obsolete.
Metrics to Watch
As you execute, track operational efficiency improvements in the specific workflow you’ve targeted, and track AI adoption confidence among your team. If your people are using the tools but not trusting them, you have a governance and training problem. If they’re trusting them without questioning outputs, you have a different but equally serious problem. The goal is informed, confident, human-led AI integration.
The Bottom Line
The media industry isn’t being replaced by AI. It’s being reorganized around it. The leaders, firms, and professionals who strategically and creatively engage with this shift will define the next era of the industry. Media sits at a unique inflection point: it is the sector whose core product, content, is both the raw material AI needs to function and the output AI is now capable of producing. That is the tension today’s media leaders need to lead through.
The best time to start was yesterday. The second-best time is today. Find a way.
Frequently Asked Questions
How is AI currently being used in the media industry?
AI is being deployed across the full media value chain: algorithmic content recommendation on streaming platforms, automated news reporting, AI-powered ad targeting and creative generation, content personalization, and production tools for visual effects and video generation. According to the Reuters Institute’s 2026 report, 97% of media executives rate AI automation as important to their operations, and 82% are prioritizing AI for newsgathering.
How is AI changing content creation for media companies?
Generative AI has dramatically lowered the barriers to content production. Adobe Firefly has been used to generate over 24 billion creative assets, and AI video tools are moving into professional production workflows through partnerships like the Lionsgate-Runway collaboration. However, the technology raises significant questions about quality, authenticity, and audience trust that media leaders must navigate carefully.
What is the copyright dispute between media companies and AI firms?
The New York Times filed a landmark copyright lawsuit against OpenAI in December 2023, alleging that millions of articles were used to train AI models without permission. The case’s main copyright claims survived OpenAI’s motion to dismiss, and the court has ordered OpenAI to produce 20 million ChatGPT logs in discovery. This is one of over 50 active copyright cases against AI companies. The outcomes will define whether media organizations are compensated for the content that powers AI systems.
How is AI affecting jobs in the media industry?
The impact is nuanced. The Reuters Institute found that 67% of news organizations report no job reductions from AI efficiencies. However, McKinsey estimates that generative AI could automate 26% of tasks in the arts, entertainment, and media sector. The 2023 SAG-AFTRA and WGA strikes established important precedents around AI use in entertainment production, requiring consent and compensation for digital replicas of performers. The pattern emerging across the industry is task reallocation rather than wholesale replacement.
Where should media leaders start with AI?
Pick one high-friction, measurable workflow and deploy an AI solution with clear success metrics. Simultaneously, audit your data infrastructure to ensure you have clean, well-organized content metadata and integrated audience data across editorial, advertising, and distribution systems. Then invest in training your team not just on tools, but on the judgment required to use them responsibly and effectively. The organizations seeing the strongest results are the ones combining focused use cases, strong data foundations, and deliberate change management.
Learn more about Josh Linkner’s keynote speaking in Media.
Josh Linkner speaks to media organizations and content industry leaders around the world about innovation, navigating disruption, and building cultures that thrive in an era of rapid change. To explore how Josh can energize your next event, schedule a call today.