TTD Cuts, PubMatic’s Truly Agentic Campaign, and (Oh No!) More Predictions from AdTechGod

An agentic OS for Publisher monetization. Our mission: win back lost traffic & revenue for Publishers by leveraging LLMs the same way the social media walled gardens & AI search LLMs do today; recommending relevant content based on who they are & what content they’re consuming: eCommerce, next article, polls, vertical video — your content optimized in our feed. Fight AI with AI & reclaim your lost traffic & revenue. Meet: Mula.

The Trade Desk has confirmed it is cutting less than 1% of its workforce, affecting a small portion of its roughly 3,900 employees. The move comes despite the company hiring nearly 1,000 people this year, including several senior leaders. Management is briefing staff in an all-hands meeting, framing the changes as part of an effort to ensure the company has the right skills in place as the ad tech market continues to evolve.

The layoffs follow a major company-wide reorganization last December that restructured client-facing teams after a challenging fourth quarter marked by the company’s first earnings miss. Since then, The Trade Desk has faced increasing competition from Amazon and Google, internal leadership departures, and growing scrutiny around programmatic transparency tied to its OpenAds initiative. As the company continues to invest heavily in its Kokai AI platform, the latest cuts signal an ongoing attempt to balance efficiency, growth, and investor expectations heading into 2026.

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PubMatic and independent agency Butler/Till have launched a fully autonomous, end-to-end agentic advertising campaign across connected TV, demonstrating a new operating model for programmatic media. Using PubMatic’s agentic application layer and the open Ad Context Protocol (AdCP), the workflow allows agents to interpret a natural language media brief, generate strategy, set up campaigns, and continuously optimize performance without manual execution.

The process runs inside the agency’s preferred generative AI environment, while PubMatic’s agents handle real-time decisioning across premium CTV supply. The activation highlights how standardized agent-to-system communication can enable live, in-market campaigns to be planned, activated, and optimized by autonomous agents rather than traditional buying teams.

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An agentic OS for Publisher monetization. Our mission: win back lost traffic & revenue for Publishers by leveraging LLMs the same way the social media walled gardens & AI search LLMs do today; recommending relevant content based on who they are & what content they’re consuming: eCommerce, next article, polls, vertical video — your content optimized in our feed. Fight AI with AI & reclaim your lost traffic & revenue. Meet: Mula.

I know you saw predictions from me a few weeks ago, but I’m expanding on my earlier outlook and have even reached out to people in the space for their own insights.

I’ve also been collecting perspectives from across the industry to capture how leaders are thinking about the next phase of transformation in AdTech, media, and marketing. What follows is a curated set of predictions from executives, operators, and strategists who are closest to the shifts already underway. Together, they reflect a shared sense that AI, data, and automation are moving from experimentation to impact, while long-standing economic, operational, and trust models are being actively reworked. These views don’t represent a single narrative so much as a mosaic of where the industry believes it’s headed next.

As we look to 2026, the digital media economy will enter a formative yet unsettled phase for AI-driven innovation. Although AI solutions will increasingly take shape, the industry should expect several false starts in deploying agentic solutions. The promise of agentic AI is real and meaningful, yet its practical application will require years of market experimentation, standardization, and alignment across platforms, agencies, and publishers.

In the near term, the most immediate and measurable efficiencies will arise in creative generation and copywriting. Generative AI is already reshaping these workflows, and leading global brands such as Coca-Cola and General Motors are demonstrating how AI-driven content production can dramatically accelerate creative cycles while maintaining brand integrity. In 2026, this will become the first area of true operational transformation across the broader ecosystem.

By contrast, agentic AI will be characterized by competing models, proprietary implementations, and a fragmented set of early solutions. While experimentation will accelerate across the industry, a unified approach is unlikely to emerge for several years as buyers, sellers, and technology partners test and iterate on divergent architectures.

In short, 2026 will be a year of meaningful progress tempered by uneven execution. Generative AI will deliver tangible value in creative production, led by pioneering brands already proving what is possible, while the broader agentic future will require continued investment, collaboration, and standardization.

In 2026, we will start to see media buying diversify beyond programmatic and direct-sold paths. Buyer and seller agents will begin handling full workflows from interpreting intent to generating executable logic. Instead of just automating what exists today, these agents open the door to new types of deals, new product formats that don’t fit into legacy pipes, and scale that humans simply cannot match.

Once these agents start talking to each other across systems, interoperability turns from a buzzword into the way work actually gets done.

AI is automating more marketing tasks than ever, and it’s also exposing how much of the industry still runs on siloed, disconnected, and incomplete data. The quality, measured in accuracy, depth, and scale, of the data behind these tools will determine whether predictions are accurate or misleading. Marketers who first ensure their knowledge about consumers is accurately underpinned through detailed identity resolution will teach AI to learn from genuine human behavior, not artificial signals. Market share winners will be those who address their data foundation before scaling with AI-enabled automation.

As platforms deploy AI-driven tools for targeting and measurement, they’re creating more contained systems that operate on their own logic. Marketers see better results, but less transparency. Independent measurement frameworks will be key to restoring validation, collaboration, and control.

As with other programmatic channels, programmatic audio has evolved from content and audience-based automation to intention-based optimization. In 2026, the most successful buyers will focus on curated supply that both reflects their brand identity and audience targets. Scale matters, but quality and alignment matters more. The platforms that make it easier to build curated, brand-fit plans will set the standard for how digital audio gets bought and sold.

Advances in AI will make 2026 a pivotal year for small businesses. Generative AI, automation software, and AI-driven ad platforms will dramatically reduce the time and money required to run marketing campaigns, create content, manage customer engagement, and analyze performance.

And voters agree on the importance of these tools. New polling from Internet for Growth and Echelon Insights shows that 94% of voters believe digital tools are essential to small business survival—a level of consensus that’s both rare and significant. For many small businesses, AI could deliver savings far beyond the $10,000 and 10 hours per week they already save through online advertising.

But unlocking these benefits depends on preserving affordable access to the data-driven advertising ecosystem that powers AI. If policymakers restrict the data needed to train and operate these systems—or layer on costly taxes and compliance requirements—the promise of AI could be diminished just as small businesses start to embrace it.

Generative AI tools rely on publisher content to train and respond, creating a new economy where publisher data is the sustainable, raw material for AI outputs. In this new economic ecosystem, we will see the rise of new data marketplaces where publishers license structured, rich content and data to AI platforms. 

These marketplaces will look different from traditional ad exchanges. Rather than selling impressions, publishers will be selling access to knowledge and meaning by monetizing the value of their content and its underlying audience and cultural intelligence. 

For publishers, this presents both risk and opportunity. Those who organize their data strategically—mapping topics, aligning with verified taxonomies, and profitably managing usage rights—will lead. Their content won’t just be scraped; it will be referenced, cited, and compensated.

Those who don't may find themselves fueling AI for free.

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