Lights, Camera, AI: Modernization for Media & Entertainment
It’s time for AI’s next act. The release of ChatGPT to the public stage in 2022 raised the curtain on experimentation and POC development in 2023 and 2024. AI is now focusing on use cases with broad impact. For media and entertainment (M&E) companies, the stakes are particularly high. With AI investment projected to increase by 14% year-over-year by the end of 2025, M&E organizations must act quickly to stay competitive, streamline processes and meet evolving consumer expectations. Read this post and learn about the role AI has played in M&E, the challenges in modernization and the opportunities waiting in the wings.
The Current State of AI Modernization
Maturity Levels Across Industries
Many organizations are at different stages of the generative AI maturity curve and there’s much disagreement about what maturity looks like. The M&E industry is viewed as leading the charge in AI advancement, with 54% of companies identifying as “advanced” in AI adoption. However, as only 7% consider themselves “disruptors,” it’s clear that most are not making the game-changing leaps promised by AI. To realize these transformative features, many organizations need to advance through the experimental phase, showcasing the need for innovative, strategic and scalable approaches.
Investment Priorities in AI
M&E companies are funneling significant resources into several key areas. AI is revolutionizing the content supply chain by enabling precise and efficient personalized and targeted content.
- Streaming Technology: Leveraging AI for smarter content recommendations, adaptive streaming quality and interactive, personalized user experiences. Personalized discovery is offered on direct-to-consumer platforms (sports, live or filmed entertainment) making it easier for fans or audience to find content relevant to their interests. Easy access to content they like to view, including interactive elements such as shopping while they watch, are key elements AI can easily provide driving subscription growth and churn reduction.
- Content Production Technology: Advancing workflows with AI-driven tools to streamline video editing, animation and special effects. AI simplifies and automates production across every stage — from generating pre-visualizations and storyboards, to assembling rough cuts, to assisting with color grading — helping creators bring their visions to life more efficiently.
- Content Management and Processing: Simplifying metadata tagging, media indexing and distribution logistics using machine learning (ML). AI provides powerful metadata tagging capabilities while facilitating greater content discovery across the archive, enabling content reuse, monetization and distribution to new channels.
- Content Distribution: Leveraging user data, content performance and market trends to make better decisions. AI identifies the most effective channels, formats and timing for content distribution, connecting relevant content with the right audience, on the right device at the right time.
These priorities spotlight the industry's drive to modernizing workflows and integrating AI into core operations — but not without hurdles.
Challenges in AI Modernization
Addressing Data Security Concerns
Security remains the most critical factor in AI development and deployment. Nearly 48% of our M&E respondents identified data security as their top data-related concern, with data exfiltration highlighted by 46% as the most pressing security issue.
Hybrid environments, which combine cloud and on-premises systems, exacerbate these concerns. Gaps in security during data transfers and storage create vulnerabilities that require robust solutions to build trust in AI-driven initiatives. According to one study, 91% of organizations have admitted making risky compromises in their hybrid cloud environments to keep pace with AI. As AI adoption escalates and hybrid infrastructures continue to grow, security remains deeply fragmented.
In addition to secure systems, shadow AI is becoming problematic as adoption increases. Shadow AI occurs when employees are using the tool in an unregulated or ungoverned fashion without company awareness or approval. Therefore, AI governance and education are crucial across all business units to ensure compliance and secure data.
Navigating Regulatory Compliance
AI must align with evolving regulatory frameworks to ensure compliance. For M&E companies, this includes safeguarding intellectual property, managing user data responsibly and adhering to consumer privacy laws. However, regulatory landscapes shift constantly, making compliance an ongoing challenge for businesses eager to deploy advanced AI systems. Across all industries, 18 months is the average time estimated to roll out an effective AI governance model. But, of course, new regulations and regulatory rulings can change the landscape week over week.
Infrastructure and Modernization Needs
To implement AI effectively, organizations must also overhaul their technology stacks. For M&E, this means:
- Investing in cloud-native applications that offer efficiency and scalability.
- Upgrading media workflows and legacy applications so that AI-powered tools operate seamlessly within existing ecosystems.
- Prioritizing flexible, hybrid infrastructures to accommodate growing data and processing demands.
Respondents from EPAM’s recent AI research report identified “not having a single source of truth data” as their top challenge specific to AI infrastructure modernization. Clean data is essential for the effective adoption of AI and ML systems.
Opportunities and Strategies for AI Modernization
Generative AI’s Momentum
Generative AI, which powers tools for content creation, has captured significant interest across industries. Companies in the M&E sector ranked highest in having piloted new AI programs with customers. M&E is in a unique position to capitalize on the growing adoption and incorporate the practice into tangible assets. These include opportunities for automating scriptwriting, creating visual effects and generating personalized content at scale.
The Role of Cloud in AI Integration
Cloud infrastructure remains the backbone of AI integration for M&E businesses. Moving to the cloud not only supports operational efficiency but also enables businesses to pivot quickly in response to new technological challenges or market shifts. However, the escalating cost of the cloud has led many businesses to adopt a type of cloud-agnostic, hybrid approach to mitigate costs and allow them to maintain greater control over their infrastructure. Cloud -cost optimization, careful monitoring of resource use and negotiations with cloud service providers are essential components of keeping a cloud efficient and creating a balanced AI strategy.
Focused Investment Areas
M&E companies are strategically investing in AI-powered advancements in content creation, personalized and interactive experiences, monetization and distribution. It can significantly reduce operational costs in that it can support every phase of content production, from story development to post-production to consuming relevant content at all distribution channels. This includes automation technologies that rely on AI/ML for tasks. Through these focused efforts, the industry seeks to capitalize on AI’s ability to fuel growth, enhance creativity and deepen audience engagement.
Future Outlook for AI Modernization
The push for AI adoption is only accelerating, with experts predicting it will become foundational to competitive advantage across industries. For M&E, the future holds exciting possibilities:
- Enhanced Audience Experiences: AI will power more personalized and immersive viewer experiences, from customized streaming recommendations to sophisticated virtual reality environments. It can help streamline advanced features for live events, such as instant slow-motion replays, deepening audience engagement in real time. For scripted content, AI helps users discover shows and movies tailored to their preferences, while also supporting interactive experiences — like shopping for merchandise or playing games — through second screens or connected TVs.
- Smarter Content Strategies: Predictive analytics will help companies determine which types of content will resonate most with audiences, empowering them to allocate resources more effectively. AI tools can help content creators stay relevant and develop ideas aligned with audience interests and industry movements.
- Streamlined Operations: AI will simplify traditionally labor-intensive workflows, such as editing, post-production and distribution, thus allowing providers to focus on creating and delivering higher-quality content.
As AI increasingly becomes a necessity rather than a luxury, M&E companies that invest in modernization now will be better positioned to innovate and thrive in an increasingly digital-first world.
Unlock the Power of AI in Media and Entertainment
AI is making dramatic changes to the media landscape, offering unparalleled opportunities for innovation, efficiency and growth. But modernization doesn’t happen overnight. To succeed, companies must act directly, dealing with everything from data security concerns to infrastructure optimization.
Is your organization ready to star in the drama of AI-driven transformation? Connect with our team of experts to explore tailored AI solutions that align with your unique challenges and goals.
Contact us today to prepare for next stage of AI.
