Fraudsters are constantly developing their tactics, with their latest trick attempting to disguise themselves as your best-performing user. By using AI-powered bots, they’re slipping past filters to drain budgets and stunt revenue growth without brands even noticing.
The result is traffic that looks human but is actually a bot, excessive clickers burning through Search budgets with no intent to buy, low-quality users inflating Meta engagement, and click injection misattributing affiliate conversions to the wrong partner. None of these clicks provide real value, and all of it corrupts the data your ad platform provider’s optimisation depends on.
The sophistication of AI has engineered invalid traffic (IVT) that appears undeniably human. Large Language Models (LLMs) powered bots can study and imitate real user behaviour so they can better hide themselves. These bots can be deployed at an unprecedented scale, and if marketers don’t act now, they’ll bleed revenue without realising till it’s too late.
Human Mimicry
IVT used to be much easier to spot, it followed obvious and predictable patterns. Bots could only repeat the same, simple actions as they were only programmed with static scripts. They would click at fixed intervals and were easily picked up by signature-based filters.
AI has changed the game, as bad actors can leverage adversarial AI models to send out traffic and test which clicks and impressions they can get past a brand’s defences. The fraudster will then be able to determine what behaviour will be seen as “normal” or flagged as “suspicious” so they can generate artificial engagement that sits within the normal range.
Bad actors then make use of residential proxies or headless browsers to disguise their location or where their bots originate from. This allows them to cover their tracks, as filters won’t realise traffic is all coming from the same place and therefore won’t flag it as suspicious.
AI-powered bots can effectively blend into regular user traffic by mimicking behaviour such as:
- Micro-movement simulation: If bots moved their cursors in simple, straight lines, they’d be easily identified. Instead, advanced bots will now replicate human users by changing the speed they navigate the screen, mimic organic tremors, and hover over buttons before clicking.
- Natural keystrokes and touch dynamics: Bots will now create and fix their own typos on forms and insert pauses to simulate a user hesitating on a form. They can also apply pressure and tilt on mobile screens just like a human would.
- Contextual browsing journeys: A human user typically wouldn’t go straight to clicking on an ad. Bots will imitate reading by scrolling and pausing, watching parts of videos or making search queries before clicking on the ad, making the journey seem more organic.
Fake clicks from bots are preventing campaigns from reaching new users by using up pay-per click (PPC) budgets. These campaigns have a set budget, and once it’s used up the ad is taken out of circulation. This means brands have lost valuable ad spend on bots instead of genuine users, but because engagement remains high brands don’t even realise their efforts have been wasted.
The even bigger problem however, is that bots are artificially inflating traffic numbers and distorting campaign data. A rise in false positives from bots will trick marketers into thinking an ad is performing well. Future decisions on strategy, spending and audience targeting will be made using incorrect information, setting brands up for future failure.
Also Read: Bringing Conversational Analytics into Your Company
Tackling AI with AI
Losses from ad fraud are rapidly building. AI fraud is corrupting conversion data and sending your campaign optimisation efforts in the wrong direction. When invalid interactions look human, your bidding algorithm learns from them, and every wrong signal does further damage across the campaign.
For marketers, prioritising the protection of campaign integrity is key. Strengthening identity verification methods is one of the first steps marketers can take. Bots may be able to trick simple CAPTCHAS or forms, but more complex ones can help to stop them.
Traffic audits should also become a regular habit for brands to ensure campaigns aren’t being filled with bots or low-quality sources. Bots can also leave fingerprints that can be used to identify them. Signs include sudden spikes in pageviews, high bounce rates or traffic from suspicious locations. Any of these should be investigated as they could signify fraud is happening behind the scenes.
Ultimately, however, manual checks can’t catch all IVT. Bot traffic is rising, Imperva’s 2026 Bad Bot Report found automated traffic accounted for 53% of all web traffic, with bad bots forming 40% of that. Marketing teams can only stretch so far, and they’re being rapidly outpaced by an opponent that is constantly evolving and growing.
To combat this, marketers need to deploy equally sophisticated tools. Anti-fraud platforms can utilise specialised AI agents to analyse metrics and user journeys to identify any IVT and block it in real-time. These agents can research new trends independently to evolve alongside fraud tactics to ensure marketers have control over their campaigns. AI has given fraudsters the ability to up their attacks, so marketers should be using it to develop their defences.
Ensuring Clean Traffic and Clean Campaigns
AI has upped the challenge for marketers significantly, as now fraudsters can cause damage on a much larger scale while not even raising the alarm. Campaigns are being filled with redundant traffic, draining resources and preventing growth.
Building bigger walls is no longer enough to ensure budgets are protected. Now, the challenge is to keep up with advancing fraud tactics and evolve faster than them.
The marketers that will come out on top won’t be the ones with the bigger budgets. It will be those that ensure campaign integrity and can prove their spend is actually reaching genuine human users.
