Is the AI ‘manipulation engine’ here? How chatbots are gearing up to sell ads

Eighteen months ago, it was plausible that artificial intelligence might take a different path than social media. Back then, AI’s development hadn’t consolidated under a small number of big tech firms. Nor had it capitalized on consumer attention, surveilling users, and delivering ads.

Unfortunately, the AI industry is now taking a page from the social media playbook and has set its sights on monetizing consumer attention. When OpenAI launched its ChatGPT Search feature in late 2024 and its browser, ChatGPT Atlas, in October 2025, it kicked off a race to capture online behavioral data to power advertising. It’s part of a yearslong turnabout by OpenAI, whose CEO Sam Altman once called the combination of ads and AI “unsettling” and now promises that ads can be deployed in AI apps while preserving trust. The rampant speculation among OpenAI users who believe they see paid placements in ChatGPT responses suggests they are not convinced.

In 2024, AI search company Perplexity started experimenting with ads in its offerings. A few months after that, Microsoft introduced ads to its Copilot AI. Google’s AI Mode for search now increasingly features ads, as does Amazon’s Rufus chatbot.

As a security expert and data scientist, we see these examples as harbingers of a future where AI companies profit from manipulating their users’ behavior for the benefit of their advertisers and investors. It’s also a reminder that the time to steer the direction of AI development away from private exploitation and toward public benefit is quickly running out.

The functionality of ChatGPT Search and its Atlas browser is not really new. Meta, commercial AI competitor Perplexity, and even ChatGPT itself have had similar AI search features for years, and both Google and Microsoft beat OpenAI to the punch by integrating AI with their browsers. But OpenAI’s business positioning signals a shift.

We believe the ChatGPT Search and Atlas announcements are worrisome because there is really only one way to make money on search: the advertising model pioneered ruthlessly by Google.

Advertising model

Ruled a monopolist in U.S. federal court, Google has earned more than US$1.6 trillion in advertising revenue since 2001. You may think of Google as a web search company, or a streaming video company (YouTube), or an email company (Gmail), or a mobile phone company (Android, Pixel), or maybe even an AI company (Gemini). But those products are ancillary to Google’s bottom line. The advertising segment typically accounts for 80% to 90% of its total revenue. Everything else is there to collect users’ data and direct users’ attention to its advertising revenue stream.

After two decades in this monopoly position, Google’s search product is much more tuned to the company’s needs than those of its users. When Google Search first arrived decades ago, it was revelatory in its ability to instantly find useful information across the still-nascent web. In 2025, its search result pages are dominated by low-quality and often AI-generated content, spam sites that exist solely to drive traffic to Amazon sales—a tactic known as affiliate marketing—and paid ad placements, which at times are indistinguishable from organic results.

Plenty of advertisers and observers seem to think AI-powered advertising is the future of the ad business.

Big Tech’s AI advertising plans are shaking up the industry.

Highly persuasive

Paid advertising in AI search, and AI models generally, could look very different from traditional web search. It has the potential to influence your thinking, spending patterns, and even personal beliefs in much more subtle ways. Because AI can engage in active dialogue, addressing your specific questions, concerns, and ideas rather than just filtering static content, its potential for influence is much greater. It’s like the difference between reading a textbook and having a conversation with its author.

Imagine you’re conversing with your AI agent about an upcoming vacation. Did it recommend a particular airline or hotel chain because they really are best for you, or does the company get a kickback for every mention? If you ask about a political issue, does the model bias its answer based on which political party has paid the company a fee, or based on the bias of the model’s corporate owners?

There is mounting evidence that AI models are at least as effective as people at persuading users to do things. A December 2023 meta-analysis of 121 randomized trials reported that AI models are as good as humans at shifting people’s perceptions, attitudes, and behaviors. A more recent meta-analysis of eight studies similarly concluded there was “no significant overall difference in persuasive performance between [large language models] and humans.”

This influence may go well beyond shaping what products you buy or who you vote for. As with the field of search engine optimization, the incentive for humans to perform for AI models might shape the way people write and communicate with each other. How we express ourselves online is likely to be increasingly directed to win the attention of AIs and earn placement in the responses they return to users.

A different way forward

Much of this is discouraging, but there is much that can be done to change it.

First, it’s important to recognize that today’s AI is fundamentally untrustworthy, for the same reasons that search engines and social media platforms are.

The problem is not the technology itself; fast ways to find information and communicate with friends and family can be wonderful capabilities. The problem is the priorities of the corporations who own these platforms and for whose benefit they are operated. Recognize that you don’t have control over what data is fed to the AI, who it is shared with, and how it is used. It’s important to keep that in mind when you connect devices and services to AI platforms, ask them questions, or consider buying or doing the things they suggest.

There is also a lot that people can demand of governments to restrain harmful corporate uses of AI. In the U.S., Congress could enshrine consumers’ rights to control their own personal data, as the EU already has. It could also create a data protection enforcement agency, as essentially every other developed nation has.

Governments worldwide could invest in Public AI—models built by public agencies offered universally for public benefit and transparently under public oversight. They could also restrict how corporations can collude to exploit people using AI, for example, by barring advertisements for dangerous products such as cigarettes and requiring disclosure of paid endorsements.

Every technology company seeks to differentiate itself from competitors, particularly in an era when yesterday’s groundbreaking AI quickly becomes a commodity that will run on any kid’s phone. One differentiator is in building a trustworthy service. It remains to be seen whether companies such as OpenAI and Anthropic can sustain profitable businesses on the back of subscription AI services like the premium editions of ChatGPT, Plus, and Pro, and Claude Pro. If they are going to continue convincing consumers and businesses to pay for these premium services, they will need to build trust.

That will require making real commitments to consumers on transparency, privacy, reliability, and security that are followed through consistently and verifiably.

And while no one knows what the future business models for AI will be, we can be certain that consumers do not want to be exploited by AI, secretly or otherwise.

Bruce Schneier is an adjunct lecturer in public policy at Harvard Kennedy School.

Nathan Sanders is an affiliate at the Berkman Klein Center for Internet & Society at Harvard University.

This article is republished from The Conversation under a Creative Commons license. Read the original article.