The growing influence and accessibility of artificial intelligence (AI) has significantly transformed society over the past three years, though not always in the ways many had anticipated.
While the widespread unemployment some feared has not materialised, workers are increasingly using AI as a powerful tool to enhance creative ideation and optimise workflows. However, the technology’s ability to generate content has also led to drawbacks, especially with the proliferation of certain AI-generated content on digital platforms. Often referred to as ‘AI slop’, this term describes digital content that is typically low in quality or created with malicious intent.
For digital advertisers, who are already well-versed in AI the technology’s continued advancement has brought both opportunities and challenges. On the one hand, it has enhanced the efficiency of media buying, but on the other, it has introduced a host of new challenges. Fraudsters, for example, are using increasingly sophisticated AI-based tools to divert ad spend from legitimate publishers to poor-quality inventory. Recent research predicts that the cost of fraudulent ads could jump from £64 billion in 2023 to £131 billion by 2028.
Yet, even as bad actors exploit AI’s rapid advancements, the technology also offers robust defences. In particular, algorithm-driven tools are readily available to safeguard media from low-quality content while improving overall efficiency and outcomes.
AI slop is on the rise
Along with falsifying impression data by mimicking human engagement, fraudsters use AI to rapidly generate websites that imitate major news brands, plagiarising and reworking material from these legitimate sites. Using URLs designed to look like the brands they are impersonating, such as “ncbsport.co.uk” and “bbcsportss.co.uk”, many of these sites purposefully focus on sport, capitalising on the perception of sports content as ‘safer’ or ‘more suitable’ than traditional breaking news.
The content often includes articles on real stories, creating a veneer of authenticity. However, it can be poorly made and untrustworthy, which can damage a brand’s reputation if it advertises on these sites. Additionally, these sites overwhelm users with excessive ads, which further degrades campaign performance.
AI protection
Manual exclusion lists are increasingly ineffective in combating this issue, as fraudsters continuously launch new domains filled with numerous subpages. That’s why advanced AI and machine learning are essential for identifying them. Tools are available that can detect patterns—such as repetitive cookie-cutter formats, generic chatbot-generated text, and placeholder content—that signal ‘AI slop’ sites. While no tool can prevent fraud completely, AI assistance can help brands respond quickly to threats, preemptively exclude these sites, and save large sums in wasted ad spend.
For the most comprehensive approach to media authentication, advertisers can also leverage pre-bid controls, which screen content before media purchases take place to root out poor-quality sites. Alongside post-bid measurement, this analyses the content of sites after impressions are bought. What’s more, it provides insights that can help brands optimise future campaigns and make informed decisions about media investment.
AI for successful outcomes
Even among high-quality, legitimate sites, some are worth far more to an advertiser than others. Effective AI tools can be invaluable in powering strong bidding strategies, ensuring advertisers buy the impressions that maximise brand-specific outcomes. For example, there are algorithms for customisable ad decisioning, which analyse data signals and can optimise media plans to a range of business-specific KPIs. This includes brand suitability, attention, viewability, frequency, budget, etc. In the past, optimising these business goals would have been near impossible for a human team, but algorithmic bidding enables this to be achieved at scale and in real time.
This capability is increasingly important in a media ecosystem experiencing greater volumes of ad fraud, low-quality inventory, as well as unsafe and unsuitable content generated by users using AI. Brands must navigate these challenges while also being able to drive toward metrics aligned with their business goals and continue to support legitimate publishers.
As AI’s potential for advertising grows, the need for marketers to remain vigilant grows with it. However, by effectively utilising AI-driven tools, brands can feel confident about propelling success over slop.
By Anna Forbes, Regional Vice President of Northern Europe for DoubleVerify
The convergence of tech and brands 