Pevita Pearce
The media industry is currently undergoing a structural transformation that promises to render the manual, spreadsheet-heavy workflows of the past century obsolete. At the heart of this shift is the emergence of "agentic" TV buying—a development that dominated the discourse at this year’s Upfronts and signals a move toward a fully automated, machine-led advertising ecosystem.
As major players like Fox and Netflix lean into artificial intelligence that doesn’t just assist but acts, the definition of a media buyer is evolving from a tactical operator to a strategic architect. But what does "agentic" actually mean in the context of the multi-billion-dollar TV advertising market, and how will it reshape the power dynamics between networks, agencies, and brands?
The Core Facts: What is Agentic Buying?
In the traditional media buying model, humans act as the primary interface. They interpret client goals, negotiate rates, manually input orders into Demand-Side Platforms (DSPs), and monitor campaign performance for manual optimization.
"Agentic" buying, by contrast, refers to the deployment of AI agents—autonomous or semi-autonomous software entities capable of executing complex workflows without constant human intervention. Unlike traditional "automation," which typically follows a rigid set of pre-programmed "if-then" rules, agentic AI utilizes Large Language Models (LLMs) and predictive analytics to make independent decisions based on real-time data inputs.
These agents can interpret a marketing brief, identify inventory that aligns with specific business KPIs, negotiate placement, and continuously adjust bids to maximize ROI. The transition from "tool" to "agent" represents a fundamental shift: the software is no longer just a calculator; it is an active participant in the marketplace.
Chronology: The Rise of the Machine Buyer
The path to agentic buying was paved by years of programmatic advertising, but the acceleration has been exponential over the last 24 months.
- 2022–2023 (The Generative Inflection Point): Following the public release of advanced LLMs, the industry shifted its focus from simple programmatic bidding to generative workflows. Media companies began exploring how to use AI to "chat" with their inventory data.
- Early 2024 (The Infrastructure Push): Tech giants and networks began integrating AI-native backends into their ad tech stacks. The focus shifted from internal efficiency to external-facing interfaces where buyers could interact with AI agents.
- May 2025 (The Upfronts Pivot): Agentic buying emerged as the defining theme of the Upfront season. Major networks publicly committed to roadmaps that move beyond dashboards and into autonomous decision-making.
- Mid-2025 to Present: The industry is currently in the "Proof of Concept" phase. Fox’s AdStudio and Netflix’s AI-driven ad business tools represent the first wave of enterprise-grade agentic products going live.
Supporting Data: Why the Shift is Inevitable
The move toward agentic buying is not merely a technological whim; it is a response to the crushing complexity of the modern convergent TV landscape.
- Fragmentation Metrics: In 2010, a national TV campaign could reach 80% of a target demographic through three major broadcast networks. Today, that same reach requires buying across linear, CTV, FAST channels, and niche streaming platforms. The sheer number of touchpoints has exceeded the cognitive processing power of human media buying teams.
- Efficiency Gains: Early pilot programs suggest that agentic workflows can reduce the time required for media planning by 60–70%. By removing the "busy work" of manual data entry and campaign pacing, agencies are projecting a shift in labor costs toward strategy and creative development.
- Optimization Velocity: Humans optimize campaigns on a daily or weekly cadence. Agentic systems perform "micro-optimizations" in milliseconds. Data from recent trials indicates that AI agents can increase ROAS (Return on Ad Spend) by 15–22% simply by identifying underperforming slots and reallocating budget in real-time, a feat impossible for human teams to replicate at scale.
Official Responses and Strategic Shifts
The industry leaders are moving rapidly to capture the "agentic" narrative, viewing it as the next great competitive moat.
Fox AdStudio’s New Era
Fox has been at the forefront of this transition, announcing the rollout of its new AdStudio. The platform is designed to move beyond traditional programmatic buying by allowing marketers to input a campaign objective—such as "reach 18-34-year-old sports fans during peak engagement windows"—and having the agentic system map out the media plan.
"We are moving from a world where buyers search for inventory to a world where inventory discovers the buyer," a spokesperson noted during the recent Upfronts. By automating the planning phase, Fox intends to lower the barrier to entry for smaller brands while increasing the precision of blue-chip advertisers.
Netflix’s Autonomous Ambitions
Netflix, having built a $3 billion advertising business in record time, is leveraging its data-rich environment to fuel its agentic play. The company is currently deploying AI agents that autonomously manage and optimize purchases. The logic is simple: Netflix knows exactly what its users are watching and when. By allowing an agent to manage the buy, the platform can ensure that ads are served against content with the highest affinity scores, dynamically updating those bids to ensure that Netflix’s inventory is always priced at the optimal market rate.
Implications: The New Media Ecosystem
The rise of agentic buying brings significant implications that will fundamentally alter the agency-client relationship.
1. The Death of the "Tactical" Media Buyer
The role of the junior media planner—historically responsible for spreadsheets and manual pacing reports—is in jeopardy. As agents take over execution, agencies will be forced to pivot their talent models. We will see a rise in "AI Orchestrators," professionals whose primary job is to train, oversee, and audit the AI agents rather than perform the buying themselves.
2. The Transparency Paradox
With autonomous buying, the "black box" becomes a major concern. If an AI agent decides to shift budget from a high-prestige news segment to a reality TV show because the data suggests higher conversions, how does the brand maintain its safety and sentiment guidelines? The industry will require a new set of "AI Guardrails"—software layers that sit on top of agents to ensure that autonomous decisions align with brand ethics and long-term positioning.
3. The Power of the Platform
Agentic buying gives platforms (Netflix, Disney, NBCU) more control over the marketplace. If a platform’s AI is the one "suggesting" the buys, there is an inherent incentive for that AI to prioritize the platform’s own inventory. Regulatory bodies may eventually need to intervene to ensure that agentic buying doesn’t devolve into a closed loop of self-serving algorithmic recommendations.
4. A New Definition of Value
In a market where buying is automated, the value of an agency will no longer be measured by its ability to secure a "good rate." Instead, value will be measured by the quality of the prompt. The agency of the future will be defined by its ability to teach an AI how to think like a specific brand, understanding the nuance of cultural relevance that an algorithm might otherwise miss.
Conclusion: The Path Forward
Agentic TV buying is not just another feature update; it is a paradigm shift. We are moving toward a "frictionless" advertising market where the gap between intent and execution is virtually eliminated.
However, as the industry embraces this new autonomous frontier, it must remain vigilant. The technology is here to stay, but the human element—the ability to understand culture, context, and brand purpose—remains the final frontier that even the most sophisticated agentic system cannot fully replicate. The winners in this new era will not be those who replace humans with agents, but those who build the most effective partnerships between the two.
As we look toward 2026 and beyond, the industry’s task is clear: define the guardrails, sharpen the strategic prompts, and prepare for a market that never sleeps.
Lina Irawan
Laily UPN
