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Key takeaways:
- Move cloud from migration to momentum. Prioritize the content libraries, production tools, and operational data that need shared access before AI can reshape workflows.
- Connect systems before scaling AI. Bring metadata, licensing, audience, and operational data into a more unified environment, so content is easier to find, govern, and monetize.
- Treat metadata as a revenue driver. Strengthen tagging, data quality, and content structure to power search, recommendations, ad targeting, and pricing decisions.
- Prove AI in controlled workflows first. Start with areas such as finance, production, and content operations before expanding into more visible creative use cases.
- Build Responsible AI into the workflow. Clarify data ingestion, vendor terms, IP ownership, human oversight, and disclosure before AI use cases expand.
Media companies sit on enormous content libraries—but most can’t fully use them. Years of mergers and streaming expansion have left many with disconnected systems, inconsistent data, and infrastructure that wasn’t built for AI. Meanwhile, a handful of industry leaders already use AI to power recommendations, personalize content, and optimize ad pricing—setting a standard the rest of the industry is racing to match.
The opportunity is real, but getting there requires a foundation most companies don’t have yet. We’ve put together a three-step roadmap to help get you there.
Step 1: Move to cloud.
Step 2: Connect your systems.
Step 3: Prove your AI use cases.
Get the sequence right, and your company can be positioned to move into more advanced AI-driven workflows. Those that skip steps will likely keep spending more to manage complexity they could have solved earlier.
The opportunity—and the gap
The media and entertainment industry is on track to exceed US$3 trillion in revenue by 2029. Digital platforms are scaling fast, while live events and cinema still drive 61% of global consumer spending, leaving companies to manage very different business models under one roof. And as subscriber growth slows, companies are turning to advertising and smarter pricing to help drive the next wave of revenue.
Media companies used to license their content to other distributors to extend their reach and bring in extra revenue. Today, after investing heavily in streaming and digital infrastructure, many are moving toward owning and controlling that content directly. That shift works only if the systems, data, and tools behind it are connected—and for most companies, they’re not yet.
Step 1: Migrate to cloud
Eighty-eight percent of senior executive respondents in PwC’s AI Agent Survey noted that they plan to increase their AI budgets in the next year, largely because of agentic AI—autonomous workflows that can help manage content creation, personalization, and monetization. For most media companies, that means getting out of on-premises infrastructure and into cloud. If you’re already using cloud, you may need to update your applications and data to support AI-enabled workflows.
Move content libraries, production tools, and operational data to a cloud platform where they can be accessed, integrated, and shared across your organization.
The payoff: Most top performers see profitability increase after cloud investments, and there's often a notable innovation boost in products and services.
Personalized experiences start in cloud.
A cable provider migrated its web content and asset management from legacy on-premises systems to cloud. The provider’s cloud foundation powers AI-assisted content creation, targeted promotions, and a more personalized customer experience. Returning visitors now pick up where they left off and get tailored promotions based on their prior interactions and location.
Key consideration
Get the sequence right.
Cloud migration works better when you start with the workflows that matter most, get teams working from the same data, and set things up so systems can connect. Simply transferring existing complexity to cloud only increases the cost of maintaining it.
Step 2: Connect your systems and make data accessible
Industry consolidation brings integration challenges. Media and telecom deal value rose 61% in the past year, and mega-mergers have created massive content libraries that are hard to manage.
Those merged libraries get added to an already sprawling set of disconnected systems and data. Content metadata, licensing records, and audience data often live in separate systems—and pulling them together takes enormous effort. AI can’t recommend what it can’t find, and your content can’t earn what it can’t surface.
The solution is to connect those systems so data can flow across your platforms. One connected platform brings production, distribution, licensing, and audience data together in a single environment.
Move from folders to findable.
A major studio replaced a legacy folder-based system with a cloud-based platform. It brought all its assets into one place and used AI to automatically tag and organize them.
A new portal verifies users, checks their contract rights, and shows only the content each partner is allowed to access. Internal teams and external licensees search, filter, and download assets from one secure platform. No more manually checking access and sending files to people based on their contracts.
Key consideration
Your metadata is your monetization engine.
Good metadata is what helps your content get found—both on the web through search engines and on streaming platforms. It’s what enables search engines and recommendation algorithms to understand your content, directly affecting viewership and revenue. Eighty percent of Netflix viewing and up to 50% of TikTok views are driven by algorithmic recommendations.
Reliable metadata helps you target customers better and charge more for ads—and that matters more as subscriber growth slows. To make metadata a true monetization engine, you require more than tags. You should have a connected, cloud-based foundation that structures content for AI. That means pulling assets together from disconnected systems, cleaning up duplicate and outdated records, and building a consistent tagging structure so content can be found. With that foundation in place, AI can do the heavy lifting—surfacing the right content, driving recommendations, and informing pricing decisions.
Step 3: Prepare for AI-enabled content use cases
AI works better when it’s applied with discipline—and when people are still reviewing what it produces. Start with areas like finance and production where AI can show clear results before moving into content creation—where talent rights and labor concerns require more careful handling.
Once you prove value, strengthen data models, and build internal confidence, then you can look to expand AI into more visible creative workflows.
From there, your organization can test additional AI-enabled content use cases such as:
| Production monitoring | Preproduction planning |
| AI-powered dailies to help producers and studio executives monitor progress, evaluate story development, and make faster creative decisions | AI-assisted preproduction to pressure-test shooting schedules, flag bottlenecks, and accelerate timelines before cameras roll |
| Content library management | IP protection and distribution |
| Frame-by-frame tagging that makes libraries searchable and editable at scale | Embedded AI-driven forensic watermarks at the pixel level during distribution so assets can be traced |
| Finance and reporting |
| AI-powered title-level finance tracking to manage revenue and costs across film, TV, podcasts, short-form content, and live events so finance systems can keep pace as content formats multiply. |
The goal is to deploy specific, pointed, AI-enabled content use cases. Pick a single workflow, prove it works, then build from there.
Use AI to personalize at the speed of live.
Months before a major global sporting event, a streaming platform wanted to offer personalized short-form recaps to casual viewers. A backend content pipeline was built to ingest, sort, and categorize thousands of daily clips by user preferences. AI generated the voice-over scripts and voice output.
The result: Highlight reels packaged in millions of unique combinations, delivered daily. Voice talent humanized the experience while any AI-generated content was clearly labeled.
Key consideration
Embed Responsible AI governance from the start.
For media and entertainment companies, the goal is to govern AI effectively without slowing down the creative process or losing trust from consumers who value authenticity. Build guardrails directly into how content is made, reviewed, and distributed so teams can move fast without introducing risk around talent rights, IP ownership, or brand trust.
PwC’s 2025 Responsible AI survey found that business leaders who embed Responsible AI governance early can expect to improve external trust by 32% and internal stakeholder trust by 30%. Fifty-eight percent of business leaders also saw an improved return on their AI investment.
The legal foundations matter, too. Licensing terms and copyright protections weren’t designed for a world where AI can create new versions of existing content at massive scale. Before piloting any AI-enabled workflow, get clarity on what data is being ingested, who owns the output, and if your AI vendor terms of service create exposure for your most valuable assets.
One studio took a walled garden approach in line with its broader AI governance strategy. It restricted AI tools to an enterprise-controlled environment and moved services into production only after formal governance contracts were in place, meaning AI couldn’t generate or distribute protected IP outside approved workflows.
Write the foundation before the sequel
Agentic AI is reshaping media—that’s no longer up for debate. The real question now is how companies will deploy agentic AI on a foundation strong enough to sustain it over time. In many ways, agentic AI is the sequel. But no sequel succeeds without a strong first act.
The foundation comes first. Agentic AI follows. If your company can get the order right—with connected data, integrated systems, and AI you can trust—you’ll be positioned to compete wherever your audiences go.
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