IAB Tech Lab and Kochava Partner to Standardize Agentic AI in Advertising

The advertising technology sector is currently undergoing a fundamental transition from the 'generative' era of artificial intelligence to the 'agentic' era. While the past two years were defined by using large language models (LLMs) to create copy and imagery, the next phase focuses on autonomous agents capable of executing complex workflows without constant human intervention. The recent partnership between the IAB Tech Lab and Kochava, which makes the latter's StationOne platform available to the standards body’s members, represents a definitive step toward codifying how these agents will operate within the global ad ecosystem.

At the heart of this development is the need for interoperability. In the current programmatic landscape, the fragmentation of data and platforms creates significant friction for automated systems. Agentic AI—AI that can set goals, use tools, and complete multi-step tasks—requires a unified language to interact with supply-side platforms (SSPs), demand-side platforms (DSPs), and measurement providers. By bringing Kochava’s StationOne into the IAB Tech Lab fold, the industry is effectively building the 'rules of the road' for AI-to-AI commerce. StationOne acts as a foundational layer that allows these agents to navigate ad tech's complex plumbing with a degree of standardization that was previously missing.

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By bringing Kochava’s StationOne into the IAB Tech Lab fold, the industry is effectively building the 'rules of the road' for AI-to-AI commerce.

For industry stakeholders, the implications are profound. For media buyers, the standardization of agentic AI means a reduction in the manual overhead required to manage cross-channel campaigns. Instead of humans manually adjusting bids or shifting budgets based on performance dashboards, autonomous agents can be empowered to make these decisions in real-time, guided by standardized protocols. This shift promises to increase the velocity of the ad market while potentially reducing the margin for human error. However, it also raises significant questions regarding transparency and accountability. If an autonomous agent makes a sub-optimal buying decision, the industry needs a standardized framework to audit that decision—a role that the IAB Tech Lab is clearly positioning itself to fill.