The media and entertainment industry has always depended on infrastructure, but AI is changing what that infrastructure needs to do. For Samrat Bera, Vice President and New Business Acquisition Head, Media, Publishing and Entertainment, HCLTech, the shift starts with the sheer volume and longevity of content.

Media companies hold archives that stretch back decades while continuing to create new video, audio and digital experiences every day. The challenge is no longer simply storing that content. Infrastructure also needs to help companies retrieve it, understand it, reuse it and create value from it.

“You need a good infrastructure, a data center, but not just a plain data center or infrastructure,” said Bera. “You also need an Agentic AI infrastructure, something that will allow you to do certain things that were not possible before, in terms of searching, content creation, animation, graphics.” 

Turning content into a competitive asset

Bera sees AI infrastructure as an enabler for making media libraries more usable. Cataloging, categorization and search can help companies surface content on demand, whether the goal is monetization, audience experience or further content development.

That becomes increasingly important as content creation becomes more democratized. Individual creators, small businesses and global media companies can all produce and distribute content at scale. For larger organizations, the opportunity is to connect vast media libraries with AI workflows that make content easier to find, contextualize and deliver.

The competitive advantage comes from how quickly and effectively companies can turn those assets into experiences for audiences. 

Real-time experiences leave little room for latency

The infrastructure requirements become even more demanding when personalization happens in real time.

Bera pointed to sports, entertainment and live experiences, where audience engagement is immediate and highly personal. A fan watching a favorite team or a viewer immersed in a show expects relevant content while the moment is still happening.

“There’s no room for latency,” he said. “It’s got to be on demand, instant, immediate.”

That puts pressure on compute, networking and data proximity. The closer intelligence can operate to where an experience is being delivered, the easier it becomes to support the kind of responsive personalization audiences increasingly expect. 

This also increases the importance of edge infrastructure, where AI inference can happen closer to the audience and support faster, more responsive experiences.

Trust becomes part of the experience

As AI-generated and AI-assisted content grows, Bera said security becomes even more important.

Media companies need to protect their intellectual property, audience information and the rights attached to the content they produce and distribute. At the same time, consumers need confidence that the content they receive is intended for them and that their data is handled appropriately.

“In short, I think security, ethical AI, especially as we get into agentic workflows, trustworthy AI and Responsible AI are all critical and are of paramount importance,” said Bera. 

For media organizations, trust is closely connected with commercial value. Protecting content rights, controlling access and securing distribution all help protect revenue as content moves across a growing ecosystem of producers, distributors, platforms and audiences.

Moving beyond pilot purgatory

Bera described three broad groups of companies: those holding back from AI, those experimenting but struggling to move beyond pilots and those treating AI as a core source of differentiation.

For the companies that scale, the opportunity stretches across the entire media lifecycle. AI can support concept development, content creation, production, post-production, distribution, media asset management, rights management, marketing, publishing, distribution and monetization.

The challenge is connecting those capabilities rather than allowing them to remain isolated.

That is where infrastructure becomes the foundation for a more integrated operating model. Content needs to be ingested, cataloged, contextualized and made available to different workflows while security and governance remain consistent. 

The next generation of media experiences

Looking further ahead, Bera expects storage, compute, networks and inference capabilities to continue evolving together.

For media and entertainment companies, that could mean richer real-time analytics around sports and live events, faster access to archived content and the ability to distribute newly created experiences globally and in multiple languages.

It also creates the possibility of bringing older content back into active use. A memorable sporting moment or a film from decades ago can become immediately discoverable and relevant again when the infrastructure behind it can retrieve, contextualize and deliver it at speed.

As Bera put it, these are “key intimate moments that can be suddenly brought to you, enabled by all of the infrastructure behind the scenes.” 

The future of media will still be defined by the experiences audiences see. Increasingly, however, the infrastructure behind those experiences will become a strategic business enabler, helping media companies create, personalize, protect and monetize content at greater speed and scale.