What Agentic Browsers Mean For Marketing: The Good, The Bad, And The Ugly

In digital marketing, the “who’s actually looking at what” problem is entering a new phase.

Agentic browsers like ChatGPT’s Atlas and Microsoft’s Copilot can now surf the web on behalf of users, helping them research and make purchases. This promises a productivity boon, certainly, but also raises questions about whether ad engagement is driven by bots or buyers. The agentic era therefore calls into question things like campaign impact, user legitimacy, and retargeting value. Further, agentic browsers are potentially susceptible to prompt injection and hijacking for black-hat fraud.

The time to answer these questions is now. E-commerce is rapidly moving toward “agentic commerce” with the release of Google’s Universal Commerce Protocol (UCP), the tech giant’s new back-end infrastructure that lets shoppers complete purchases without even visiting a retailer’s site. Microsoft rolled out Copilot Checkout with similar functionality and Shopify announced its “Agentic Plan” to integrate with both platforms. We’re witnessing commerce rails being rebuilt around agents rather than users while fraud detection struggles to keep pace.

Os varejistas são já raising concerns about what gets lost when transactions move to black boxes and marketers should be equally worried. After all, AI-powered automation is already creating new attack vectors for ad fraud (see: ghost click farms) and less visibility into the customer journey threatens turning analytics into guesswork. Let’s take a deeper look at the arrival of agentic browsers and what it means for marketing: the good, the bad, and the ugly.

The good: Higher conversion rates and signals

Let’s start with the upside: agentic browsers may improve marketing efficiency by filtering out low-intent traffic. If an AI agent only clicks ads when a user has genuine purchase intent, advertisers would theoretically see:

• Taxas de conversão mais altas: No more casual browsers inflating CTR without buying
• Better attribution signals: Agents acting on explicit user commands create clearer intent trails
• Reduced wasted spend: Fewer “just looking” clicks that don’t convert

The keyword here is “could.” This optimistic scenario assumes that agents declare themselves, platforms track them accurately, and users actually trust agents to make purchase decisions on their behalf. But there are currently no guarantees or guidelines on how agents self-report.

As A16Z’s recent report noted, we likely need “Know Your Agent” protocols similar to “Know Your Customer” rules to address this. But, at the moment, marketers can’t quickly tell when a session is from an agent or a user, and that’s when we start to see potential issues.

The bad: Human vs agent traffic is largely indistinguishable

There’s a lot marketers don’t know here. For example, if an agent researches products overnight, those browsing sessions trigger remarketing pixels. Days later, the human sees retargeted ads and converts. Should advertisers pay full price for that agent activity? Half? Nothing? We can’t yet determine how to price agent traffic, nor can we easily identify it. A user instructing their agent to browse and a fraudster hijacking an agent to commit ad fraud look nearly identical to marketers: they see the same device, IP, browser, and session. This visibility issue adds salt to the wound of invalid clicks.

Invalid clicks have duplicou over the past 15 years thanks to increasingly sophisticated bots that mimic human behavior. As a result, advertisers are increasingly partnering with third-party fraud detection services to identify fake clicks before charges hit their budgets. Now, with agentic browsers in the mix, the industry is bracing for even less insight into who is interacting with campaigns, making it much harder to pinpoint performance and weed out fraudulent interactions.

Finally, it’s worth considering data exposure with agentic browsers. Elements such as active web content, browsing history, and open tabs are typically sent to the cloud-based AI, which, in turn, increases the risk of data exposure unless security and privacy settings are deliberately hardened and centrally managed. It’s for this security question mark, and a few other nefarious possibilities that we’ll get into below, that Gartner suggests enterprises block AI browsers for the moment.

The ugly: Bad actors using browsers to do their bidding

Ad fraud is a much bigger and more expensive issue than many realize – accounting for a scam that’s 8x the size of credit card fraud – and bad actors can do more damage with better tools. In Setembro, for example, malware turned unwitting smartphones into “ghost click farms” that secretly interacted with ads over and over again, hitting 2.3 billion bid requests per day at the height of the scheme. The fake ad views on pages controlled by the fraudsters generated countless micro-payments that went straight into their pockets.

The concern is that agentic browsers will make such scams only harder to detect and more common. Compromised via prompt injection, rogue agents become perfect vehicles for scaled click fraud, form spam, and fake reviews, all while looking identical to users. Gartner backs this up by highlighting other dangers such as flawed agent reasoning leading to harmful actions and credential theft when AI browsers are tricked into navigating directly to phishing sites.

Today, it’s easier than ever to spin up a sophisticated click farm with agentic AI. You used to need entire teams of people and now you can do it from home with bots. Mainstream agentic browsers don’t create this problem but they do make it a lot easier to scale.

The Truth: Agents can be helpful and harmful to marketers

The introduction of agentic browsers isn’t binary for marketers. Rather than being all good or all bad, the truth is somewhere in the middle. Whether the future tips one way or the other will be decided by how well solution providers and marketing technologists can build in safeguards.

Rules that identify and declare agents are essential, as is building visibility and trust into these browsers before they go mainstream. After all, good marketing depends on good data, and good data depends on transparency.