The Negotiated Future: Ethan Settel on Newton Research, Agentic Media Buying, and the Reinvention of Media Operations

What happens when AI stops assisting media teams and starts acting on their behalf?In this episode of Signal & Noise, we sit down with Ethan Settel, Head of Sales & Accounts at Newton Research, to explore one of the most important developments in advertising today: the emergence of agentic media buying.While much of the industry remains focused on AI tools that summarize dashboards, generate briefs, or automate reporting, Newton Research is pursuing something far more ambitious. The company is building specialized AI agents that can connect data, execute advanced analytics, build forecasting models, recommend optimizations, and increasingly interact directly with media platforms to support planning, buying, and activation. At the center of our conversation is a provocative thesis: the future of advertising may be negotiated by machines.Rather than relying on human teams to manually interpret reports, adjust budgets, and coordinate across dozens of disconnected systems, agentic platforms like Newton are creating teams of AI specialists that can work together to analyze campaign performance, simulate scenarios, and execute media decisions with unprecedented speed and precision. These agents can communicate with DSPs, publishers, clean rooms, and planning tools, transforming what has historically been a fragmented and labor-intensive process into an increasingly automated operating model. We also discuss Newton’s groundbreaking work with NBCUniversal, FreeWheel, Yahoo, and Locality, where buy-side and sell-side AI agents collaborated to support premium video buying across linear television and streaming. The initiative offers a compelling glimpse into a future where software agents negotiate inventory directly with one another, potentially reshaping the role of DSPs, SSPs, and other intermediaries throughout the advertising ecosystem. Along the way, Ethan explains why measurement and analytics are the foundation of any effective agentic system. Without trusted data, consistent models, and full transparency into how decisions are made, automation simply amplifies errors. Newton addresses this by combining its proprietary marketing science knowledge base with each client’s unique methodologies, creating a repeatable and highly customized intelligence layer that becomes more valuable over time. We also explore some of the biggest questions facing the industry:How AI agents differ from generic tools like OpenAI ChatGPT, Anthropic Claude, and Google GeminiWhy data normalization has historically consumed most of a data scientist’s timeHow agentic systems can democratize advanced analytics for planners and buyersThe role of protocols such as MCP and AdCP in enabling agent-to-agent communicationWhether DSPs and SSPs become strategic platforms or simply “dumb pipes”Where liability and accountability sit when AI begins making media decisionsWhy human oversight remains essential, even as automation acceleratesEthan also shares his perspective on the organizational impact of agentic AI. Rather than replacing media professionals outright, he argues that the technology frees analysts, planners, and buyers from repetitive manual work, allowing them to focus on strategy, experimentation, and innovation. The result is not fewer insights, but potentially unlimited analytics applied to every campaign and every decision. This conversation offers a rare and highly practical look at what applied AI actually looks like inside advertising. It moves beyond hype to examine how real systems are being deployed today to transform measurement, planning, and activation.If Ethan is right, the future of media will not be defined by faster reporting or prettier dashboards. It will be defined by intelligent agents negotiating with one another across the buy-side and sell-side, continuously optimizing outcomes in a market that becomes more automated, transparent, and data-driven than ever before.The negotiated future has already begun.