Key Points
- A Gracenote report says AI and large language models will reshape how audiences discover and engage with entertainment.
- Streaming platforms are adopting AI tools to deliver faster, more personalized and real-time content recommendations.
- Grounded AI systems using external data are expected to improve accuracy and become key to next-generation viewing experiences.
Artificial intelligence is poised to reshape how audiences discover and engage with entertainment, as platforms increasingly adopt large language models (LLMs) to power more personalized and real-time user experiences, according to a new report from Nielsen’s metadata company Gracenote.
The report released on Wednesday makes the case that consumer expectations around immediacy and tailored recommendations are accelerating as AI becomes more embedded in daily life.
In entertainment, that shift is translating into demand for faster discovery tools, contextual recommendations and the ability to act instantly on content, such as locating a live sports event or selecting programming based on mood or preferences.
To meet those expectations, publishers and streaming platforms are expected to rely more heavily on LLMs as foundational technology for next-generation interfaces. Last month, Samsung announced a new partnership with Gracenote to utilize the company’s metadata solutions as the foundation for various AI-powered search and discovery tools for its Tizen-powered smart TV sets.
That partnership is critical, Gracenote proffers, because LLMs by themselves are not enough to provide reliable information, since they can generate inaccurate or fabricated responses, commonly known within the industry as “hallucinations.” That becomes less of an issue if LLMs are supplied with good external data, like the type Gracenote is providing to Samsung for its AI-powered search and discovery tools.
Other companies are increasingly implementing similar “grounding” techniques that connect LLMs to real-world information sources. The report highlights two primary approaches: retrieval-augmented generation (RAG) and the Model Context Protocol (MCP).
RAG, which has been in development since around 2020, enhances LLM responses by injecting relevant information from external document repositories into a query before it is processed. This approach allows systems to remain current without requiring constant retraining, making it well-suited for unstructured, document-heavy use cases such as background information or historical context. However, because RAG enriches prompts in advance, it limits the model’s ability to dynamically reason across multiple data sources during execution.
By contrast, MCP, introduced as an open-source protocol in late 2024, enables real-time connections between LLMs and external systems through standardized interfaces. Often described as a universal connector for AI, MCP allows models to query multiple data sources simultaneously, validate responses and execute actions based on up-to-date information.
That capability is particularly relevant for entertainment platforms that depend on current, structured data, including program availability, live sports scores and dynamic recommendation engines. MCP’s architecture allows LLMs to access and act on real-time inputs after a query is made, improving both accuracy and responsiveness.
While both RAG and MCP are designed to improve LLM reliability and contextual relevance, they serve different functions. RAG is more effective for retrieving static or archival information, while MCP is better suited for applications requiring live data and interactive decision-making, Gracenote said.
As streaming services and connected TV platforms evolve, the ability to integrate real-time context is expected to become a competitive differentiator. The report points to use cases such as dynamically curated content rails that incorporate factors like location and weather, enabled by LLMs connected to multiple external data sources.
Ultimately, the analysis concludes that grounded LLMs will play a central role in the future of entertainment discovery, enabling more sophisticated search, deeper personalization and more accurate results.
Gracenote offers a free white paper on its MCP servers, which can be accessed after registration by clicking or tapping here.
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