From time to time, Marketecture invites guest authors to weigh in with their unique insights on the media, marketing, and ad tech spaces. Today’s guest author, Karsten Weide, Principal and Chief Analyst at W Media Research, examines how autonomous AI shopping bots are reshaping the consumer journey, and what it means for advertising, publishers, and ad tech vendors when machines, not humans, make the buying decisions.
When Bots Buy, What Happens To Advertising?
A new kind of buyer is emerging — one that isn't human, but algorithmic. AI shopping bots act on behalf of consumers, identifying needs, researching products, and making purchases based on user preferences. Unlike familiar tools like Alexa and ChatGPT that respond to prompts, shopping bots operate with autonomy, assessing structured data like product specs and pricing history to complete tasks with minimal human input. For consumers, the appeal is clear: convenience, efficiency, and relief from decision fatigue in an overwhelming e-commerce landscape.
This shift is already underway. A 2024 survey found that 61% of U.S. shoppers use AI tools like ChatGPT for shopping-related tasks. As bots become embedded in smartphones and smart home devices, adoption could scale faster than past tech shifts like mobile internet or streaming. This transformation upends advertising, as traditional behaviors like browsing and viewing ads become less relevant. Bots aren’t swayed by banners or influencer hype; they care about specs, verified reviews, and cost-benefit ratios.
The Shopping Bot Purchase Journey
The rise of AI shopping bots is re-engineering the customer journey into a machine-mediated process where autonomous agents are the main actors. This journey breaks down into six steps:
Configuration: The consumer teaches the bot how to shop by setting preferences and constraints, such as brand affinities, dietary needs, or price ranges.
Need Detection: Bots proactively detect triggers like an empty fridge or upcoming birthday, or suggest purchases based on behavioral patterns.
Information Gathering: Bots conduct research by pulling structured data from websites and APIs. They compare specs, reviews, and prices and might negotiate terms using bot-to-bot communication protocols. Products lacking clean data might be downranked or ignored.
Evaluation: Using internal logic shaped by user preferences, bots rank results and offer a small set of recommendations with justifications.
Purchase: Bots complete the transaction, from logging in to applying coupons and arranging delivery.
Feedback Loop: Every interaction becomes a data point that trains the bot to become more personalized and predictive.
This journey is faster, more logical, and largely immune to traditional advertising. Brands must shift their focus from attracting human attention to meeting machine criteria. The new goal is not just to be seen but to be selected by the bots that will soon dominate purchasing.
What Happens to Advertising When Bots Buy?
As bots bypass human touchpoints, performance-driven ad formats that rely on human clicks and conversions will lose effectiveness. This includes retargeting, paid search, AI search overview ads, and a majority of social media ads.
Not all advertising is at risk, though. Budgets are likely to shift toward campaigns that shape consumer preferences before they're encoded into bots. That means renewed investment in emotionally resonant storytelling through formats like:
Display ads
CTV and video
Digital out-of-home
In-app and in-game ads
Traditional media like TV, radio, and print
This move from performance marketing to brand influence might feel like a return to traditional advertising, but it’s armed with new digital tools.
New Monetization Models for Publishers
The rise of AI shopping bots threatens the traditional business model for digital publishers. Once consumers delegate shopping to bots, there’s no one left to click on an ad or visit a branded landing page. That erodes direct-response revenue and undercuts commerce content like buyer’s guides.
To survive, publishers must pivot from attention economics to data economics. Bots rely on trusted, structured information, and publishers who adapt their content for machines can remain relevant.
New monetization models include:
Structured Data Licensing: Turning reviews, rankings, and comparisons into machine-readable feeds and monetizing them via usage, not impressions.
AI Training Content Licensing: Licensing archival content to AI platforms for training and real-time applications.
Subscriptions and Premium Content: As ad revenue falls, publishers must lean into subscriptions, memberships, and events (i.e., monetizing quality journalism and human stories bots ignore).
The winners will stop asking, “How do we get people to click?” and start asking, “How do we get bots to trust us?”
Consequences for AdTech Vendors: Adapt or Perish
The foundations of the AdTech industry are starting to show cracks. Declining human engagement and falling ad revenue for publishers weaken demand across the entire AdTech value chain. For legacy vendors, this poses an existential threat — but it’s also a major opportunity for those who adapt.
The opportunity lies in enabling bots, not targeting people. A new frontier — Shopping Bot Optimization (SBO) — is emerging. SBO platforms help brands structure product catalogs to be bot-friendly: clean metadata, compliance with new protocols like MCP and A2A, and machine-readable formats.
Beyond SBO, AdTech vendors can become commerce infrastructure providers. Business models will shift from CPMs and impressions to API access, metadata services, and premium placement in agent ecosystems. The next generation of tech will be built for bots, enabling transactions, choices, and brand visibility in a world where decisions are algorithmic.
The era of optimizing for human attention is ending. The autonomous consumer isn’t a futuristic vision. It’s already taking shape. The time to prepare is now.
This post is an excerpt of W Media Research’s research note “When Bots Buy – What Happens To Advertising?”, 7 figures, 27 pages, US$ 1,995.
Karsten Weide has 30 years of experience as a researcher, producer, and product manager in the advertising and media & entertainment industries. At his research company, W Media Research, LLC, he specializes in advertising technology, serving vendors, publishers, agencies, and brands with market intelligence and go-to-market work. Previous engagements include IDC, Yahoo, and Ziff-Davis. Weide is the two-time winner of IDC’s Research Quality Award as well as of the Research Innovation Award and the Excellence Award for Business Development.