Media Excel CEO Narayanan Rajan ponders whether AI will be the catalyst for medias future, and suggests that companies need to embrace AI today or risk falling behind tomorrowBy Contributor
Published: December 19, 2024 Updated: December 20, 2024
Media Excel CEO Narayanan Rajan ponders whether AI will be the catalyst for media's future, and suggests that companies need to embrace AI today or risk falling behind tomorrow
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Artificial intelligence (AI) is emerging as a transformative force in the media and entertainment industry. By enabling companies to streamline multi-channel operations, reduce latency, and harness data-driven insights, AI is not only optimising workflows but also redefining competitive strategies. As media companies face increasing complexity and rapidly evolving market demands, maturing AI solutions provide a new set of tools to facilitate adaptation. However, AI's adoption also presents challenges, from ethical considerations to integration complexities.
Streamlining multi-channel operations The proliferation of platforms, including traditional TV, streaming services, and social media, has created a fragmented operational landscape for media companies. AI-driven tools are uniquely positioned to unify and optimise these operations, reducing redundancy and increasing efficiency.
For example, Comcast's AI-powered access network integrates real-time telemetry with self-healing functions through its massive network feature virtualisation (NFV) project, Janus. By eliminating human error in core network operations, Comcast ensures seamless delivery of real-time content, even during high-demand periods. chief network officer Elad Nafshi explains, Data usage continues to skyrocket primarily due to the rapid increase in streaming high-quality live sports.
AI also helps to automate routine tasks Netflix uses AI algorithms that dynamically adjust streaming quality based on viewer location and network availability, a feature particularly valuable in emerging markets where mobile streaming dominates. This adaptability improves user experience and minimises operational costs by reducing the need for constant human monitoring. According to a report by Deloitte, companies adopting similar AI-based optimisations see up to 20 per cent savings in operational costs, highlighting the cost efficiencies that AI can deliver.
Boosting system performance and reducing latency AI's ability to monitor, predict, and adapt to real-time demands is transforming media performance, particularly in latency-sensitive applications like live streaming and interactive media.
During high-traffic live sporting events or major news broadcasts, Amazon Prime Video's AI algorithms dynamically allocate resources to maintain streaming quality, avoiding interruptions without manual intervention. Beyond streaming, AI-powered compression tools are proving essential for new formats like VR and AR. For instance, some companies are developing AI-enhanced codecs that reduce latency while maintaining immersive visual fidelity.
While live streaming often dominates latency discussions, AI's role extends to optimising content delivery networks (CDNs), reducing delays for on-demand content. For example, Akamai uses AI-driven analytics to predict demand spikes and proactively optimise server usage, reducing latency and avoiding bottlenecks, and Netflix employs AI to optimise its Open Connect Appliance to pre-position popular content closer to reduce delivery time to end users and ensure smooth playback.
AI-driven insights for market competitiveness In a crowded media landscape, understanding audience preferences and responding to market trends is critical. AI-powered analytics enable companies to extract actionable insights from vast datasets, ensuring their content and strategies remain relevant.
For example, Disney and Hulu use AI to analyse viewership data, enabling targeted advertising and content recommendations. McKinsey reports that companies adopting personalised AI strategies can increase revenue by up to 10 per cent, driven by improved customer retention.
Netflix's recommendation engine not only enhances user engagement but also supports strategic content investments by predicting audience demand. Beyond established players, smaller platforms are leveraging similar AI capabilities through third-party analytics services, levelling the playing field in audience retention and monetisation.
Navigating technological shifts and market demands The media industry is no stranger to technological disruption. Companies that quickly adapt to new tools often gain a competitive edge, while those that lag behind risk competing with an increased operational burden. AI offers media companies the flexibility to navigate these shifts effectively.
Warner Bros Discovery is using AI for precise ad targeting, improving relevance and user engagement. Disney has established an Office of Technology Enablement to ensure there is a considered approach to technologies like AI and AR/VR to ensure alignment with the company's broader strategy. This will allow Disney to take a phased integration approach without disrupting broader operations.
Emerging AI technologies like generative AI for content creation are also reshaping the industry. Startups like Runway are enabling video production using text-to-video AI for ad creation, offering new opportunities for low-cost content generation.
Challenges and ethical considerations While AI offers immense potential, its integration is not without challenges. High implementation costs, the need for specialised expertise, and ethical concerns over data privacy and algorithmic biases present significant hurdles. Media companies must navigate these issues carefully to ensure AI adoption is
