2026 will mark the beginning of the end for manual programmatic buying as genAI gives way to agentic AI and automation becomes the industry standard. Marketers must prepare now for AI to take on a larger role in the programmatic process; those that don’t may get left behind.

This shift fundamentally changes how programmatic works. As a result:

• Automated bidding is the default. GenAI can evaluate hundreds of campaign inputs to set the best bid. In real time, AI dynamically adjusts bidding strategies and spend allocation with minimal intervention needed.
• Targeting shifts from static to real‑time. Identifying and segmenting audiences is the top AI use case for brands and agencies, according to January 2025 IAB data. In 2026, genAI will be able to refine and update audiences based on instantaneous performance indicators or create audience personas from custom prompts.
• Creative becomes continuous. Keeping creative fresh in programmatic remains a consistent challenge. But with genAI, marketers can auto‑generate variants, tests, and swap assets daily, linking creative to real‑time signals.
• Measurement gets smarter. GenAI enables faster analysis of large datasets offering more predictive insights. AI also powers advanced measurement capabilities like multi-touch attribution (MTA) or marketing mix modeling (MMM), which are gaining traction as marketers seek better to measure performance across a complex digital landscape.

Now is the time for teams to build the skills and confidence needed to use AI-driven insights in daily decision-making. Marketers who start today will move into 2026 better equipped for what comes next: The shift toward agentic AI.

Laying the groundwork for agentic AI

As genAI becomes standard, agentic AI will take on a larger role within programmatic advertising, eventually automating end-to-end campaign workflows.

New protocols like the Unified Context Protocol (UCP), Advertising Context Protocol (AdCP), and the Agentic RTB Framework (ARTF) will accelerate adoption by giving AI agents a shared infrastructure to communicate and collaborate.

But marketers require more trust and transparency around how agents make decisions before handing over the reins. For example, 60% of US ad industry professionals say concerns about accuracy/transparency are a top barrier to AI adoption in media campaigns, per IAB.

Though it's unlikely programmatic will be fully agentic within the year, expect more parts of a marketer's process to be more automated, especially around performance reporting/analysis and customer journey operations. These are two of the most common applications of agentic AI among marketers worldwide, found data from Coleman Parkes Research and SAS.

Recommendations for brands and agencies

• Prioritize data integration and readiness for agentic AI. As agentic AI evolves, the focus shifts from simply having data to ensuring it's usable. Marketers must audit their data, ensure cross-platform interoperability, and establish governance rules.
• Invest in AI literacy and learning. Creative teams should focus on prompt quality and concept development while marketing operations should focus on translating AI-driven insights into outcomes. Setting guardrails will also be critical moving forward.
• Rethink measurement. Measurement must evolve into a live feedback system that informs decisions continuously. This foundation is essential for agentic AI, which will rely on trustworthy, always-on signals to operate effectively.

This was originally featured in the EMARKETER Daily newsletter. For more marketing insights, statistics, and trends, subscribe here.