The Interoperability Imperative: How AI Agents are Redefining the Agency-Tech Partnership

Date: October 8, 2026
Subject: The Evolution of Agency Operations in the Age of Agentic AI
Perspective: Insights provided by Patricia Clark, VP of Go-To-Market at Nexxen

Introduction: The Decade of the AI Agent

Artificial Intelligence has transcended its status as the industry’s "topic du jour." As we move through late 2026, AI has firmly established itself as the defining theme of the decade for the advertising and marketing sectors. For media agencies, the promise of AI—specifically the rapid ascent of "agentic" systems—is transformative. These aren’t just generative text tools; they are autonomous entities capable of orchestrating multi-step workflows across fragmented data, media, and technology stacks.

However, as the sophistication of these tools grows, so does the complexity of the digital ecosystem. The ability to integrate these agents into existing, heterogeneous environments has moved from a technical "nice-to-have" to an operational mandate. According to Patricia Clark, VP of Go-To-Market at Nexxen, the industry is approaching a critical juncture where the choice between flexibility and innovation is becoming a false dichotomy.

Main Facts: The Shift Toward Open Ecosystems

The core challenge facing modern agencies is no longer access to data, but the ability to synthesize it. The current advertising landscape is characterized by a "spaghetti" of platforms, supply paths, and measurement tools.

The Rise of Agentic Workflows: Unlike static AI models that require constant human prompting, agentic AI can take a high-level natural language request—such as "optimize this campaign for mid-funnel conversion across CTV and mobile"—and execute a series of actions across multiple platforms.
The Interoperability Mandate: To function effectively, these agents require interoperability. They must be able to communicate with DSPs, data warehouses, and creative management platforms seamlessly.
Open Standards: The industry is coalescing around open standards, such as the Model Context Protocol (MCP) and Agent2Agent frameworks. These are not merely technical specifications; they are the connective tissue that prevents "vendor lock-in" and allows agencies to build bespoke stacks that suit their unique operational DNA.

Chronology: From Automation to Autonomy

To understand the current state of agency operations, one must look at the trajectory of digital advertising technology over the last five years:

2021–2022 (The Foundation): The focus was on automated bidding and programmatic efficiency. DSPs began integrating basic machine learning to improve ROAS (Return on Ad Spend) through predictive modeling.
2023–2024 (The Generative Explosion): With the arrival of Large Language Models (LLMs), agencies rushed to adopt generative AI for creative iteration, copywriting, and basic reporting.
2025 (The Integration Gap): Agencies faced "tool fatigue." With dozens of disparate AI tools in their arsenal, teams spent more time "swiveling chair" between platforms than actually strategizing.
2026 (The Agentic Era): The focus has shifted from using AI to orchestrating AI. The current market trend is the move toward unified ecosystems where agents act as the central nervous system of an agency’s tech stack.

Supporting Data: Why "One-Size-Fits-All" Fails

While the narrative of "AI replacing human effort" is prevalent, the reality of agency operations is far more nuanced. Research suggests that the value of interoperability is not a constant; it is highly variable based on the agency’s business model.

The Four Pillars of Agency Operations

Nexxen identifies four distinct operational archetypes that define how agencies handle technology today:

The Managed Service Model: These agencies prioritize speed and simplicity. They rely heavily on the platform’s proprietary "black box" intelligence. For them, interoperability is less about deep integration and more about dashboarding.
The Self-Service Model: These power users demand direct, granular control. They require APIs that allow them to pull raw logs and manipulate bidding algorithms directly.
The Hybrid Approach: The most common model. Agencies leverage a tech partner’s core expertise while maintaining a "visibility layer" that allows them to audit and adjust AI decisions.
The Architect Model: A small but growing cohort of elite agencies is building its own proprietary "agent ecosystems." They treat their tech stack as a product, using interoperability to swap out DSPs or data providers as market conditions dictate.

Analogy: Patricia Clark likens these choices to the culinary world. One can hire a personal chef (Managed Service), dine at a high-end restaurant (Partner-led), prep one’s own ingredients (Self-service), or master the art of fine dining at home (Building an ecosystem). Each has inherent trade-offs regarding cost, control, and convenience.

Official Perspectives: The Nexxen View

Nexxen emphasizes that the goal for any agency should not be the creation of the most complex system, but the resolution of the most pressing client problems.

"Agencies shouldn’t have to choose between flexibility and innovation," Clark notes. "They shouldn’t be locked into a single provider’s architecture. The right partners are those who provide a transparent, secure, and reliable foundation."

This foundation is built on three requirements:

Transparency: Agencies must be able to see the "why" behind an agent’s decision.
Security: As agents interact with proprietary agency data, the risks of data leakage or model poisoning must be mitigated through robust, secure API environments.
Future-Proofing: Partners must be willing to evolve. If a new industry standard emerges, the tech partner must be agile enough to pivot, ensuring the agency isn’t stranded on legacy tech.

Implications: The Future of the Advertising Agency

The emergence of agentic AI and the subsequent push for interoperability have profound implications for the talent and structure of advertising agencies.

1. From Doers to Architects

The role of the media planner or account manager is shifting. As agents handle the heavy lifting of campaign activation and optimization, the human role moves toward "architecting." Humans will define the goals, set the guardrails, and audit the outcomes.

2. The Power of Choice

The era of the "all-in-one" platform that does everything poorly is ending. In its place, we are seeing the rise of a "best-of-breed" ecosystem. Agencies will increasingly choose a DSP because it plays well with others, rather than because it promises a total, closed-loop solution.

3. Sustainability of Innovation

There is a danger in the "feature race." Agencies that focus on adopting every new tool without a clear strategy for interoperability will find themselves buried under technical debt. The winners in this market will be those who use technology to simplify the client experience, not complicate it.

Conclusion: Solving the Right Problems

As we look toward the remainder of 2026 and into 2027, the focus must remain on the client’s bottom line. Agentic AI is an incredibly powerful tool, but it is only as effective as the environment in which it operates.

An open, interoperable ecosystem allows agencies to leverage the best the market has to offer without sacrificing control. Whether an agency chooses to be a builder, a buyer, or a hybrid of both, the success of their AI strategy will ultimately depend on the partnerships they forge. The goal is not complexity; it is the responsible, sustainable, and effective application of technology to solve real-world marketing challenges.

By prioritizing open standards and selecting partners who view interoperability as a strategic priority, agencies can ensure they remain at the forefront of the advertising industry, no matter how fast the technology evolves.