Artificial intelligence offers media and entertainment organizations an opportunity to build faster, more personalized audience connections. At the same time, television, film, game studios and mobile giants need AI and Generative AI strategies that protect intellectual property, improve efficiency and empower creators and audiences alike. Here, our leaders share investment, adoption and risk management perspectives to help media organizations implement and scale AI confidently.
“Lights, camera, action!” for AI in the media and entertainment industry
Realizing AI potential in media and entertainment can present multi-faceted challenges, and GenAI adds even more complexity. Because the industry operates at the intersection of creative, legal and cultural dynamics, GenAI success depends on the alignment between the creators adopting it, the brands protecting and monetizing their intellectual property (IP), and the consumers wanting to interact with it.
Below, our industry leaders explore strategies that can help media brands achieve that alignment.
1. Where should media and entertainment organizations focus their AI investments to create real, lasting value?
Media and entertainment organizations can generate returns by focusing AI investments in two areas: extending and monetizing intellectual property and delivering more personalized audience experiences.
Intellectual property lifecycle extension and preservation for business efficiency
AI tools can automate content recognition and apply metadata to vast media IP libraries, efficiently preserving and categorizing thousands of hours of historically significant work.
Many media and entertainment organizations begin their AI journey with straightforward, high-impact use cases within their existing IP library such as content localization, translation, subtitling and closed captioning to realize rapid value and improve user experiences. This can empower bottom-line business value for media and entertainment brands and enable in-house creatives to easily access archival footage to reference for new projects.
CFOs can drive revenue through new IP monetization strategies around repackaging and reissuing classic content—for both new audiences and those hungry to relive nostalgia. AI can also help organizations manage legal terms and contract rights around important IP preservation and acquisition, creating additional bottom-line business value.
Audience experience personalization
Online fandoms, sports viewers and gamers want to feel seen by the media personalities, musicians, teams, and entertainment brands they love. Achieving this on a global scale requires sophisticated content localization and cultural intelligence based on where each fan lives and what the data shows they want from their favorite brands.
Agentic AI tools can help manage personalization at scale by streamlining and automating manual elements of the content supply chain and can optimize channel delivery for each fan based on customer data profiles, for example. This level of personalization at scale allows entertainment brands to deepen fan relationships and optimize cross-channel monetization.
But it is important to establish a steady foundation first, with smaller personalization use cases such as content recommendations and targeted marketing. From there, brands can grow their AI investments into higher value audience experiences such as real-time personalization during live events, augmented reality mobile app experiences and agentic-driven merchandise recommendations live onsite and online.
2. How can media and entertainment industry executives drive the strongest results from their AI innovation investments?
To lead the next wave of innovation, brands can embrace AI adoption strategies that focus on what to do in-house, what to do with collaborators, and what to do with audiences.
Democratize and evangelize experimentation
Innovation thrives when the barriers to technology adoption are removed. Media and entertainment organizations can empower all of their teams—not just creatives or data scientists—to embrace agentic tools by making them accessible, safe, low-stakes and engaging. By encouraging experimentation across many parts of the organization and using internal champions to evangelize high-value use cases, companies can foster a culture of democratized innovation. Over time, this test-and-learn approach helps employees identify practical applications to build confidence using AI in their day-to-day work.
Pursue strategic ecosystem relationships
No organization can navigate this shift alone. Finding the right alliances to pilot new technologies in a controlled manner can help brands scale their AI adoption and close gaps in their knowledge and reach. This includes working with creative guilds and unions to help shape the governance and guidelines that will collaboratively shape the future of AI for entertainment.
Launch new digital experiences
GenAI tools lower the barrier to entry for content creation and can inspire a new generation of independent creatives to experiment with new content formats. For established studios and media brands, it can help ideate and iterate on creative storyboards, 3D prototypes and design themes during the development process. Organizations that invest in emerging formats such as micro-series and podcasts, for example, can build lean, agile, AI-powered studio models and create more personalized content for targeted audiences, expanding their reach beyond legacy channels and content types.
3. What are the most pressing challenges facing media and entertainment organizations looking to expand and scale their use of AI?
Union and regulatory compliance
Successfully scaling GenAI in media and entertainment requires more than technical capability. Perhaps most crucially, it requires strong governance and stakeholder trust. Organizations must address copyright risk, union concerns around job displacement and creative integrity, and evolving regulatory expectations. Clear policies, trusted technology partners, and close collaboration among creators, tech providers, unions and regulators are essential to protecting IP and enabling responsible AI adoption.
Return on investment (ROI) uncertainty
Organizations often make substantial upfront investments in AI infrastructure, so business leaders must demonstrate value against core key performance indicators (KPIs). Since traditional financial returns can be challenging to forecast as AI pilots scale, the ROI often includes fundamental organizational change and sweeping productivity impact.
To accurately capture this value, leaders should approach measurement at the broad enterprise level, with KPIs such as...
...while simultaneously defining success at the granular level through KPIs such as:
Meaningful collaboration across the C-suite is essential to align these KPIs with overarching business goals and build the foundation to leap into the new agentic era.
Supporting artists in a changing landscape
At the heart of the media and entertainment industry lies the irreplaceable force of human creativity. Rather than approaching AI with apprehension, the industry has an opportunity to embrace these technologies as powerful extensions of artists’ visions. By reducing friction in the most resource-intensive aspects of media production, AI can create efficiencies for large organizations and empower small creators and independent artists to reach larger audiences.
While AI tools can create new ways for media and entertainment organizations to expand audience interaction, leaders must take a thoughtful and strategic approach that prioritizes human creativity and protects IP. By integrating tools that accelerate creativity while protecting creators' rights and securing intellectual property, the industry can enhance, preserve and properly credit human insights.
Your red carpet is waiting
In media and entertainment, the most effective AI investments are tied to practical use cases, clear business value and responsible governance.
The leaders who get this right will not treat AI as a shortcut to efficiency alone, but as a tool to strengthen creative collaboration, create new kinds of experiences, and build deeper, more valuable connections that surprise and delight new audiences now and in the future.
About the authors
Scott Pobiner is a managing director of AI, Data & Design at Deloitte, focused on creating exciting and practical applications for new technologies in the Technology, Media, and Entertainment fields. He specializes in areas where AI, machine learning, and human experience converge in technology and media sectors.
Laura Shact is a principal in Deloitte's Human Capital practice who develops and delivers people solutions to support strategic business objectives. She has more than 15 years of consulting experience at Deloitte and primarily serves clients in the technology, media and telecommunications industry.
Edward Coveyduck serves as Deloitte’s US Engineering leader for Telecommunications, Media & Entertainment. He specializes in driving large-scale, complex technology transformations across multiple infrastructure and cloud platforms.
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Sources
1. Jim Rowan, Nitin Mittal, Parth Patwari and Ed Burns, “The agentic reality check: Preparing for a silicon-based workforce,” Deloitte Insights, December 10, 2025.
