Reinventing media: AI across the value chain
The media and entertainment industry is rapidly reorganising their entire value chain around heavy AI investment. Research shows that the dynamic post-pandemic media landscape has prompted changing ad models, accelerating content creation timelines, shifting distribution identities, and increasing customer experience expectations across streaming, sports, and in-person entertainment.
Yet, most companies are executing strategy in vacuums and deploying AI in isolated pockets, focused on implementing individual tools per department instead of utilising the technology as connective tissue across business operations.
For example, streaming platforms may use AI to personalise recommendations but lack the data integration to connect those insights to dynamic ad pricing. Or a content studio may use generative AI for asset creation but fail to pass insights to the CX team to manage customer engagement. In fact, only 28% of organisations have systems to ensure seamless transfer of context and conversations across channels. These siloed data systems give leaders an incoherent view of their business, resulting in missed opportunities and fragmented experiences.
To achieve a true competitive edge, companies need to modernise their AI workflows to unify three critical business areas that have historically operated in silos: ad sales, content creation, and customer experience.
Rethinking ad monetisation
Gone are the days of generic audience segments and fixed pricing models. AI is fundamentally transforming the advertising space across media and entertainment through enabling dynamic monetisation with real-time targeting and contextual pricing. AI-assisted ad campaigns have been shown to deliver a 28% higher ROI on average, with 74% of consumers preferring tailored advertisements and 68% reporting a greater trust for AI-personalised ads compared to non-AI counterparts. AI-supplemented advertising doesn’t just improve a brand’s bottom line; it enables brands to enhance precision and build deeper resonance among their customer base.
However, an AI model’s capacities are only as effective as the data it’s given. To scale these capabilities, organisations must provide AI systems with access to data across audience behavior and engagement patterns, demand and availability of inventory, and ROI of historical ad placements.
This data foundation, coupled with AI-enabled ad monetisation, strikes a balance that optimises engagement for advertisers and maximises revenue for media companies, creating a mutually beneficial outcome. This model also increases efficiency and saves time practitioners once spent on more analytical efforts, realigning priorities around what matters most: high-quality premium content for customers.
Content creation amplified
Content creation budgets and timelines continue to shrink as consumer demand exponentially grows. AI adoption resolves this tension by enabling production teams to do more with existing resources. The opportunity is not to replace creators, but rather to free them from repetitive work so they can concentrate on what differentiates their brands and drives engagement: creativity. Employees report saving five hours a week using AI-automated workflows, leaving time for them to focus on strategic work with high-stakes outcomes.
To maximise AI’s potential, content teams must incorporate past campaign information, production data, and audience performance insights, in addition to distribution requirements across platforms. For instance, creators can use audience feedback from a show’s first season to disseminate customised teasers and trailers across social and digital platforms for the next season, tailored to each audience and environment. With AI capabilities, teams of all sizes can ramp content creation while maintaining brand standards, quality, and authenticity.
The unified customer experience
The biggest untapped opportunity in media and entertainment is addressing customer experience fragmentation. Consumer expectations are no longer linear; they are dynamic and context specific. A customer might stream content at home, visit a theme park, attend a live event, dine at a branded restaurant, and book a hotel all in one week – but these experiences rarely connect. Decentralised data remains one of the main barriers to enhanced CX, with 78% of front-line staff noting they lack real-time access to customer data, limiting personalised engagement.
AI has the potential to unify customer journey data from all touchpoints across platforms, including digital engagements, live events, and real-world interactions. Predictive models can then use the data to anticipate customer needs and resolve emerging issues before they escalate. Not only do these measures lower operational costs, but it shifts the internal culture of media and entertainment companies from selling products and services to nurturing human relationships, empowered by AI. Consumers are 70% more likely to buy from brands after positive CX, and those who feel emotionally connected to a brand are 306% more likely to recommend it.
Consistently strong, personalised CX builds trust and emotional attachment, transforming one-off interactions into potential lifelong brand loyalty.
In a landscape where consumers have infinite entertainment options, the edge will go to companies that expand AI’s impact past gimmicks and standalone experience optimisation. Rather, they will have to transform the value chain to make the relationship seamless, personalised, and intelligent.
This transition from siloed to integrated AI represents the industry's next major competitive battleground. The companies that gain a competitive advantage in media and entertainment will be those that use AI to connect ad sales, streamline content creation, and unify customer experience into a single, intelligent ecosystem.
[Editor's note: This is a contributed article from Capgemini. Streaming Media accepts vendor bylines based solely on their value to our readers.]