California protects an individual’s right to sue when a company violates data privacy law. So privacy compliance means understanding what a jury of consumers will tolerate.
Everybody wants to make the most of agentic AI in advertising. The winners will do it with purpose. Here’s how to make a plan, step by step.
Where teens were once swept into the same cohort as 18-34, brands will have to have separate strategies and tactics to engage them. And this shift comes just as Gen Alpha comes of age.
While Eric Seufert’s “everything is an ad network” mantra keeps being proven correct, a new truism is also taking shape: “Wherever an advertising business emerges, the measurement challenge follows.”
The burden of understanding ad auction dynamics should not sit with buyers. Platforms built the systems, and only platforms can fully explain how they set the price.
Why does the buy side remain so smitten with handing control to autonomous systems owned by companies whose economic interests are not its own?
Per-token price for frontier models may go up or down, but the cost to solve complex problems is going to increase, writes Zefr’s Jon Morra.
What happens when you let an AI agent handle back-to-school shopping – and realize you may have outsourced the fun parts, too?
Marketing teams are getting faster with AI, but the real question is whether they’re actually getting better outcomes, writes Devart’s Margaret Lee.
The parts of AI that touch real money should always sit on deterministic infrastructure that’s been doing this long enough to know how to do it right, writers Fluency’s Eric Picard.
Will Walmart’s acquisition of Vibe.co create an AOL-esque walled garden – or a CTV platform advertisers actually want to use?
The FTC’s lawsuit that alleging Hims & Hers shared sensitive health data with advertisers is only the latest reminder that trust must be an operating principle, not just a marketing promise.
The Publicis/LiveRamp acquisition raises a stark question: Can shared identity infrastructure really stay neutral under competitor ownership?
The next internet will not be built by humans clicking buttons; it will be built by agents acting on behalf of people, brands, publishers, platforms and enterprises.
Somewhere between what the ad industry says and what the market rewards is often where the truth lives. Here are the three industry storylines most in need of debunking.
Agentic AI shows promise for direct deals. But if Google has its way, Buyer Direct could put an end to all sorts of agentic direct sales opportunities while they’re still in the cradle.
Historically, non-human traffic was viewed on a spectrum from benign to intentional fraud. But AI agents represent a legitimate audience that brands will have to understand and engage.
When an advertiser trains a model on its full organic converter base, it can better identify patterns that distinguish a casual browser from someone close to buying.
Advertising in AI-native destinations and experiences is already starting to look less like a series of experiments and more like an emerging market.
Instead of relying on rigid audience segments, modern systems can interpret a real-world moment in real time, combining layers of information to better predict what someone might actually care about right now.
The industry spent years building data verification frameworks for publishers and sellers. The buy side has no equivalent discipline. And it needs one.
In a world being agentically orchestrated at scale, human judgment is the indispensable guardrail preventing us from optimizing right over the cliff.
We must reject the fantasy of infinite creative variations tailored to individuals – not just because it is technically impossible but because it fundamentally misunderstands how advertising works for the vast majority of brands.
With deterministic data like cookies becoming less reliable, advertising’s real value comes from being able to predict where audiences will be and how and when to reach them.
The W3C’s proposed “Attribution Level 1” browser standard deserves far more scrutiny from the advertising and measurement community than it has so far received.
The real AI risk in digital advertising isn’t automation, it’s autonomous decision-making without clear accountability and sufficient oversight.
The programmatic intelligence layer is owned by the same parties that are extracting margin from it. That structure is now being dismantled by an AI-underpinned protocol that moves the intelligence layer into the open.
Binary measurement preserves margin and lets late-arriving impressions claim credit they may not deserve. We need a new measurement model for the AI era.
There is a myth that end-to-end platforms and sheer quantity of data yield efficiency and competitive advantage. But most clients need flexible, modular solutions that address their needs and work with their existing tech stacks.
Between signal loss, missing audience information and aging data, most of the data that companies have is spotty. But despite what you may have heard, agentic AI can deal with spotty data.
