Home Data-Driven Thinking Marketing To Machines: A New Performance Strategy In The Age Of AI Agents

Marketing To Machines: A New Performance Strategy In The Age Of AI Agents

SHARE:
Michael Lehman, President, Nativo

The traditional marketing funnel is quickly being rewritten – not by a consumer trend but by a shift in how machines process and recommend information. 

As AI agents like OpenAI’s Operator, Google’s Gemini and Amazon’s Rufus begin to mediate everything from search to purchase, marketers are being forced to confront the reality that they must treat machines as customers.

We have entered the era of agentic AI, where autonomous software agents are powered by large language models (LLMs) that research, evaluate and recommend products on behalf of consumers. These agents don’t “click” in the conventional sense. They don’t scroll endlessly. They don’t get seduced by banner ads. They read, compare, interpret and synthesize. And, increasingly, they decide.

From search rankings to narrative authority

Today, 86% of Google searches already include generative elements. Gartner predicts a 25% drop in traditional search volume as AI search ascends. In this new paradigm, ranking number one in search is no longer the goal. Instead, your brand must be embedded in the answer itself.

LLMs don’t surface blue links; they surface conclusions. When a user asks for “the best laptop for under $1,000,” the model returns a curated response based on its training data, reinforced by high-quality third-party content, product pages, reviews and more. That response may or may not mention your brand. That answer could be outdated, inaccurate or hallucinated.

And yet that response is what the user now trusts.

What AI agents actually “see” (and what they ignore)

While AI agents are already reshaping consumer behavior, their engagement with advertising is still nascent and fluid. But the early evidence is clear and revealing.

New research from the University of Applied Sciences Upper Austria, which tested AI agents across simulated hotel booking tasks, found that:

  • Text-based ads with relevant, keyword-rich copy influenced decision-making more than visual ads.
  • Agents like GPT-4o and Claude were significantly more responsive to structured, on-page content, like pricing, star ratings and location data.
  • Banner ads were often ignored or undervalued, as most agents are not yet reliably interpreting image-based or stylistic elements.
  • In contrast, semantic clarity and contextual alignment were shown to impact agent behavior.

Although still in the early innings, this study suggests something profound: Machines are engaging most with the kind of content they can parse – textual, structured, machine-readable content.

It also stands to reason that, as LLMs continue to evolve, they will be intentionally trained away from formats like banners, which are low-signal and easily gamed, and toward trusted, semantically rich content that aligns with their core competency: language understanding.

The rise of generative engine optimization (GEO)

This new dynamic is already catalyzing a shift from traditional SEO to generative engine optimization (GEO) – the discipline of ensuring your brand, product or service is favorably represented in AI-generated outputs.

GEO is not about keyword-stuffing or link-building. It’s about narrative authority: crafting and distributing high-quality, context-rich content that LLMs can confidently use to answer queries.

This is where content marketing becomes central to future brand visibility. Articles, explainers, product Q&As, comparisons, reviews – these are no longer just trust-building tools for human readers. They’re training and inference data for the agents shaping future consumer decisions.

A call for new expertise

The convergence of AI search and agentic AI marks a fundamental shift in the purpose of digital marketing from capturing attention to shaping perception. It’s no longer about being clicked. It’s about being chosen.

The best way to influence that choice? Become a source the AI trusts. And the best way to earn that trust? Credible, structured, optimized and consistent content.

In a world where AI agents are the new gatekeepers, content marketing is not just a brand builder. It’s the new performance engine.

Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.

Follow Nativo and AdExchanger on LinkedIn.

For more articles featuring Michael Lehman, click here.

Must Read

Shopify Wades Deeper Into Advertising, But Not Ad Tech

Shopify is slowly but surely making its way into the ads business. But the ecommerce leader maintains its laissez-faire approach to ad monetization.

Walmart Buys Vibe.co To Woo SMBs To Streaming

Walmart will buy Vibe.co, a self-serve video ad platform, in hopes of attracting more small and medium-sized advertisers to connected TV.

OpenAI's debut in Cannes

At Its First-Ever Cannes, OpenAI Says ‘We Are Clearly In The Advertising Business Now’

Bonjour, ChatGPT ads. OpenAI’s inaugural Cannes Lions appearance doubled as a coming‑out party for its baby ad business.

Privacy! Commerce! Connected TV! Read all about it. Subscribe to AdExchanger Newsletters
Friends high-five while watching a football soccer match

Fire TV Makes A Play For Its Share Of Home Screen Ad Dollars

Amazon is making a splash at Cannes by touting recent Fire TV interface upgrades designed to help viewers find relevant content more easily, including when they are watching the 2026 FIFA World Cup.

Comic: Overfrequency

Omnicom Can Now Measure Ad Frequency Across Multiple CTV Platforms

For the first time, Omnicom can directly compare ad frequency and performance across multiple major streamers, which typically prefer to keep data locked inside their walled gardens.

Inside The Trade Desk’s Pitch For Ventura TV OS

The Trade Desk is muscling its way into the TV operating system business with its Ventura OS – but the real story isn’t the product itself. It’s what TTD’s ambitions reveal about conflicts of interest within the industry and the inherent mismatch between consumer and advertiser needs.