AI in Ad Tech: Promise, Hype, or Just Another Cash Grab?

Is AI in ad tech really all it's being promoted to be? Shirley Marschall takes a look...

AI is being sold as the ultimate solution to ad tech’s biggest challenges. Privacy? Solved. Fraud? Eliminated. Performance? Optimised. Fragmentation? Gone.

But what happens when we actually look under the hood?

AI is advancing at warp speed, and with it comes AI-anxiety, the fear of missing out on the next big breakthrough. Over 70% of professionals feel pressure to adopt AI, fearing they’ll fall behind. But instead of making smarter decisions, the industry is making faster ones.

Instead of asking hard questions, we’re blindly following the hype.

Here’s the truth: No one is going to miss out on anything by taking a beat, a breath, and a critical look before jumping in.

You have to slow down to move fast. AI promises acceleration, but speed without direction is just chaos.

AI is in the Experimentation Phase and That’s OK

Let’s be fair: Ad tech companies are under pressure just like everyone else. The AI hype cycle is moving so fast that companies risk looking outdated if they don’t claim an AI play.

Some experiments will lead to real innovation. Others will be rushed just to check a box.

Instead of blindly buying into the hype, decision-makers should expect AI solutions to evolve and demand proof, not just promises.

Promise vs. Reality: Looking Under the AI Hood

AI is being positioned as a fix for everything: brand safety, sustainability, curation, performance optimisation.

But if a solution checks every single industry buzzword, it’s time to ask questions. When we inspect the engine, do these claims actually hold up?

Brand safety at scale? AI can analyse sentiment and context, but false positives and negatives are still common. And who defines “safe” content? Brand safety is subjective, AI can’t universally determine what’s acceptable for every brand.

AI-powered sustainability? Carbon-aware optimisation sounds great, but sustainability data isn’t standardised across the industry. If emissions tracking isn’t consistent, can AI really make reliable decisions? And what about the carbon footprint of AI itself? If every ad decision involves AI processing, emissions will skyrocket.

Curation and performance optimisation? AI models often reinforce biases in supply path optimisation. If one exchange is consistently deprioritised, is that an efficiency gain or just another black box decision?

Fully automated decision-making? AI is great at optimisation, but balancing brand safety, sustainability, and performance all at once without trade-offs? That’s like saying you can optimise for reach, frequency, and ROI simultaneously. Something always has to give.

AI Red Flags: If it’s Too Good to be True…

AI conveniently solves today’s hottest challenges. We’ve seen this hype cycle before - blockchain, personalisation, privacy-first tracking. If AI is the answer to everything at once, is it really solving anything?

• “Custom AI” with no real explanation. If a vendor can’t clearly explain how their AI works beyond “it’s AI-powered,” it’s probably just ML rebranded.
• Overnight AI expertise. Every ad tech startup suddenly has “AI-powered solutions,” but real innovation takes time. If a solution appeared out of nowhere, how advanced can it really be?
• The full-automation fantasy. AI can optimise, but removing human oversight entirely is a black-box waiting to fail. Who’s responsible when things go wrong?

The False Choice: AI vs. Human Decision-Making

AI is framed as inevitable, but does blind trust in AI remove necessary strategic oversight?

AI is great at automation, but are we making smarter decisions, or just faster ones?

Instead of asking AI “What’s possible?”, we should be asking “What’s responsible?”

We don’t need AI to make decisions for us. We need AI to support better decision-making. But that only works if we stay in control instead of handing over the keys.

AI and the Next Wave of the Ad Tech Cash Cow

Every ad tech startup is slapping “AI-powered” onto their decks. Every platform is pivoting in the AI direction. One might wonder:

Is AI the next ad tech cash cow?

Are these solutions providing value, or are they just riding the funding wave before investors start asking hard questions?

Remember, we’ve seen this before:

• “Blockchain will revolutionise ad tech.” (It didn’t.)
• “Third-party data is the answer to personalisation.” (Then it got regulated.)
• “AI will solve all inefficiencies.” (Will it, though?)

Slow Down to Move Fast: AI Adoption vs. Digital Resilience

Just because AI is advancing at breakneck speed doesn’t mean businesses should adopt it blindly.

AI’s effectiveness is only as strong as the digital foundation it runs on. If a company lacks robust infrastructure, data governance, and risk management, AI won’t fix its problems, it will magnify them.

The AI paradox: Everyone wants frictionless, automated solutions but friction exists for a reason. A fully automated system with zero human oversight is a black box waiting to fail.

Final Thought: If it’s Too Good to be True… It Probably is

AI will transform ad tech. But not overnight, and not without trade-offs.

Instead of chasing the latest AI buzzwords, companies should:

• Ask tough questions.
• Demand transparency.
• Make decisions based on real business value, not just industry hype.

Because in AI, promise vs. reality will always depend on who controls the algorithm.