Insights from IBM, Microsoft, Deltatre, and Evergent reveal how smart media platforms are turning AI into their biggest competitive advantage

The media and entertainment industry is experiencing its most significant transformation since the advent of streaming. At the center of this revolution lies AI-powered personalization—tech-fueled activity that's reshaping how audiences discover, consume, and engage with content.

Through a series of executive conversations on recent episodes of The Monetization Show podcast, industry veterans explored how artificial intelligence is revolutionizing media and entertainment business models. Host Vijay Sajja, CEO of Evergent, was joined by Steve Canepa (Managing Director at IBM), Andrea Marini (CEO of Deltatre), and Simon Crownshaw (Microsoft's Worldwide Lead for Media & Entertainment), each bringing unique perspectives on this transformation.

From Disruption to Differentiation

The personalization wave didn't originate from traditional media companies. As IBM's Steve Canepa explained, this “wave of personalization” was really “driven more from the outside in by the large technology companies than it was driven by the media companies." Tech giants understand data and algorithms better than content creators, he said, forcing established players to play catch-up.

The results speak for themselves. As Crownshaw noted, Microsoft's work with the NBA, which also counts Evergent among its tech vendors, demonstrates the stakes, noting their team is "really seeing three, four, five times the amount of engagement," he said.

This wasn't incremental improvement—it was transformational growth driven by understanding user preferences and delivering personalized experiences.

Beyond the Hype: Real Business Impact

While AI dominates headlines, industry leaders maintain balanced perspectives. Canepa noted, "I think it's equal parts hype and reality probably at the moment." However, Crownshaw offered a more definitive view after extensive implementation experience: "I think it is the greatest force multiplier we've ever had at our fingertips."

Industry analysts echo this sentiment. A recent Q&A published by Gartner on the topic emphasized that marketing leaders can unlock commercial value by rethinking personalized digital interactions, leveraging customer-permissioned data to drive meaningful engagement and long-term loyalty. Media companies are clearly turning the corner from experimental AI to enterprise-grade deployment.

The key lies in practical application rather than technological novelty. AI's true value emerges in efficiency gains and capability enhancement. As Marini, of Deltatre, explains it, "In our world, the biggest drivers are efficiency…if you do it well, there are some areas where you have incredible efficiency."

Twin Pillars of Success

Successful AI implementation centers on two fundamental capabilities, as Canepa identified: "The two core pillars in the AI world are do I understand my content as well as I can? And do I understand my audience as well as I can?"

This dual focus manifests in sophisticated applications. IBM's implementation for the U.S. Open tennis tournament, as Canepa noted, put into play generative AI that took all the digital content from every match in order to “separate that into slugs and then put automated commentary," enabling personalization. “You can scale and personalize now in a whole other order of magnitude for your audience members,” he said.

A recently published study on the ROI of personalization by Forrester Consulting, in partnership with Adobe, reinforces this dual-focus approach, noting that leaders in personalization combine first-party data, AI-driven content intelligence, and real-time orchestration to dramatically improve customer understanding and content alignment. Findings from the study, titled “How to Improve the ROI of Personalization at Scale in the Era of AI,” underscore how this approach unlocks both operational scale and emotional relevance—key to thriving in a fragmented digital environment.

Microsoft's NBA strategy, per Crownshaw, demonstrates similar principles in understanding and tailoring the league’s content specifically to users. He stressed the importance of this as “really fundamental because the minute you get something wrong, they leave the platform, they go somewhere else.”

Their approach, he said, involved "leveraging the data in real time, augmenting it with their own data from the games themselves."

Solving the Discovery Crisis

Content discovery represents AI's most immediate value proposition.

Despite unprecedented content libraries, platforms struggle with user engagement. Marini identified the core issue: "A lot of people are talking about spending time searching for something on Netflix or Amazon, even if you have this huge amount of content."

The solution involves hyper-personalization that fundamentally reimagines audience interaction. "We really see big innovation is in the ability to hyper-personalize the content," Marini explains. "If we are able to take this data, massage it properly, and feed it into our front-end, our apps, and with the player, then we can really create an experience that matters for the user."

This evolution enables interactive experiences where users "can ask questions, pull up clips, customize the content that you see in a way that you couldn't before," as Crownshaw described Microsoft's latest implementations.

The Critical Foundation of Data

All these leaders emphasize that AI's effectiveness depends entirely on data quality and strategy. Crownshaw notes a critical industry awakening: "In our industry, media and entertainment, it (data) was not looked after very well for a very long period of time. And now organizations are realizing the importance of their data, what it means and how they're going to leverage it” in today’s AI world.

This data advantage creates two critical applications, as highlighted throughout the podcast discussions: customer acquisition ("what's the right product to offer?") and retention ("how do you keep them?"). Sajja noted his experience at Evergent, which has had proven success with AI tools, with more than 920 million users onboarded globally, offered a great example of how companies with robust data strategies can predict user behavior and proactively address churn risks.

The Profitability Imperative

The industry's focus has shifted dramatically toward sustainable business models. "Monetization and profitability really are the lifeblood of where we land," Crownshaw observes. The challenge, he said, lies in legacy technology constraints creating a situation with “media companies’ inability to play offense.”

AI offers solutions through operational efficiency, automated processes, and new revenue streams. Companies, per Crownshaw, are exploring "retail media" opportunities and connecting content to commerce, creating "real value drivers" beyond traditional subscription models.

Looking Forward

The personalization revolution's trajectory is clear: AI will dramatically enhance the ability to deliver the right content to the right person at the right moment. As Marini predicts, "In the next…12, 18 months, personalization is going to be king."

Success will depend on balancing technological capability with brand trust, automation with authentic experience. Companies that master this balance, supported by robust data strategies and strategic partnerships, will define the next era of media and entertainment.

The future isn't about replacing human creativity but amplifying it through intelligent systems that understand both content and audience at unprecedented scales. In an attention economy where time is the ultimate scarce resource, that capability represents the difference between thriving and merely surviving.

This analysis draws from The Monetization Show podcast hosted by Vijay Sajja (CEO, Evergent), featuring conversations with Steve Canepa (Managing Director, IBM), Andrea Marini (CEO, Deltatre), and Simon Crownshaw (Worldwide Lead for Media & Entertainment, Microsoft)—four leaders at the forefront of AI implementation in media and entertainment.