As AI becomes more embedded in advertising and marketing, risks are shifting in ways brands aren’t always prepared for. AI promises scaled operations, better targeting and creative deployment, more comprehensive analytics, and more automated brand safety monitoring. The risks make themselves known when these systems fail, or are misrepresented, and the consequences can be substantial.
DoubleVerify, a leader in brand safety detection powered by ad analytics, recently faced this reality when a data error misrepresented X’s (formerly Twitter’s) brand safety score for nearly five months. The incorrect ratings likely raised a red flag for advertisers and led to a significant drop in DoubleVerify’s efficacy, and its stock. The question here is could this have been avoided with better monitoring of its AI tools, or more human hands in an oversight role – or both. If advertiser's base decisions on data – and that data is faulty, how confident can we be in the systems meant to protect brand reputation?
The risks of overreliance on AI isn’t just an ad tech issue. When Heathrow Airport suffered a major disruption earlier this month, it wasn’t just an AI failure—but a domino breakdown of automated systems. A glitch in one area bleeds into others. This example exposes just how fragile modern machine-driven infrastructure can be. In marketing, the same dependency on AI-driven tools, from automated ad placements to brand safety filters, can lead to similar crises. “When they fail, the consequences don’t just hit operations. They hit trust, customer experience and brand reputation”. Whether through a technical glitch, algorithm misconfiguration, or cyberattack, AI-powered system errors have real consequences for brand trust and customer relationships.
AI is the current industry arms race, with ad tech companies, publishers/platforms, marketers, and agencies all under pressure to stay ahead. “The AI hype cycle is moving so fast that companies risk looking outdated if they don’t claim an AI play.” Solutions promising to solve everything—brand safety, curation, optimization—often sound good - but require a good look under the hood. The challenge isn’t about adopting AI but making sure it can actually deliver. Brands need to ask the tough questions: Who controls the algorithm? How transparent is the data? What real value does AI add to operations.
AI will shape the future of advertising for certain, but it won’t fix everything – and we at the early stages. The key to keeping brands safe in an AI-driven world isn’t blind faith—it’s understanding emerging risks, continually asking the right questions, and ensuring that the technology as intended. Most of all, AI must work for brands, not against them.