Almost everything in AI feels big. But are you looking at the next Gangnam Style or the birth of a new industry? Here’s how to assess whether an AI vendor is likely to matter in two years.
Marketers used to wait for obvious signals, like a product page view, a cart add or a keyword search, before triggering campaigns. But in today’s fractured landscape, those signals can arrive too late.
For years, MFA was a mostly web-based problem. Now, generative AI has supercharged the made-for-advertising model, and it’s infecting social media feeds and vertical video platforms.
Mobile apps are now at the center of the consumer relationship. They’re where customers browse, buy, stream, check balances and redeem loyalty rewards. However, app measurement remains one of the weakest links in modern marketing.
There’s a paradox at play in how marketers are adopting artificial intelligence.
Eighty-seven percent of US advertisers say they plan to increase AI usage over the next 12 months. But only 45% feel confident in their understanding of how AI-powered technologies work. That 42-point gap is an indicator of early friction in AI adoption.
Broadsign may actually be building a platform that will make an attractive acquisition target down the road. And one of the major cross-platform Big Tech players feels like the most likely buyer.
CTV spending is flattening, performance is plateauing and buyers are hesitant to push budgets further. The reason is not complicated. When buyers cannot see what they are buying, they cannot commit their spend with conviction.
As artificial intelligence transforms advertising analytics, many organizations are rushing to adopt AI tools, hoping for a “magic button” that instantly democratizes data access.
Performance marketers are turning to AI to navigate rising costs, data loss and increasingly complex shopper journeys – and it’s working. Creative is more personalized, targeting is sharper and optimization happens in real time.
Generative AI is the new ad land obsession: a shiny promise of a fully autonomous world of self-driving advertising. But behind the hype lies the costly delusion that automation can replace judgment and more content somehow means better marketing. We’ve entered the age of machine-made abundance, where content can be generated faster than it can […]
Take a moment to think about how your day sounds. Maybe you start with the sound of your alarm, followed by a quick news briefing from your smart speaker while you scroll through emails. Your favorite podcast keeps you company during your commute. Your to-go playlist helps you get in the zone at the gym.
With privacy under unprecedented attack by data brokers and social media, it is the wrong time to weaken CIPA’s private right of action protections, as has been proposed in California Senate Bill 690.
AI has raised the bar for what qualifies as “good data.”
The conversation is no longer about how much data marketers can collect but how well that data reflects reality. In this new era, success depends on data that is accurate, fresh, consented and interoperable – principles that ensure AI models learn from accuracy.
When it comes to complex techniques like media mix modeling, the field is awash with false promises about the benefits that AI can offer.
Every conversation about addressability eventually lands on the same word: fragmentation. But the real symptom of that fragmentation isn’t just operational complexity; it’s also declining match rates. That single number explains why marketers are struggling to make their data work.
Most of what’s sold as “contextual” today still runs on the same keyword logic we used a decade ago. The industry didn’t reinvent contextual targeting; it simply replaced one keyword with a cluster.
Consumers don’t experience media in silos. They might stream a live game on their TV, scroll social feeds during halftime and research products on their mobile device later that night.
Confusion in CTV isn’t a natural byproduct of a maturing market; it’s an outcome of how distributors protect their pricing power.
The real challenge is drawing a clear line between the AI-generated content that adds value and the kind that erodes trust and leads to significantly lower ad effectiveness.
As the digital advertising industry enters a new phase of maturity, so does its relationship with data. Going into 2026, marketers’ long-standing obsession with scale is giving way to something more grounded: a push for smarter, actionable, owned data.
Social CPMs have risen. The ability to find incremental audiences on social platforms has declined. Add the growing brand-safety concerns, and the equation looks even worse.
It won’t fail because the protocol is bad; it will fail because you’ve been sold a simplistic dream – a “universal API” for ad tech – and that’s what you’re budgeting for.
Artificial intelligence has become marketing’s favorite headline. Every platform, publisher and technology partner now promises “AI-powered” solutions that will make campaigns smarter, faster and cheaper.
Our industry has done a terrible job rewarding publishers for monetization choices that align their supply to quality and outcomes vs. short-term yield bumps. But is it overly optimistic to think The Trade Desk’s recent moves prove that’s changing?
Understanding where AI agents make financial sense today is the difference between building a sustainable competitive advantage and burning through your margins in pursuit of buzzwords.
Publishers, brands and agencies today are navigating a new landscape. With rising consumer expectations and evolving regulations, delivering personalized campaigns requires a fresh approach.
To get to the heart of the TID debate, you have to understand the definition of a healthy marketplace and how our tendency to limit transparency for the other side of the supply chain is holding us back.
Viamedia has transformed into Viamedia.ai, a next-generation ad tech company built to solve the challenges of today’s fragmented media ecosystem. The firm has rebranded as Viamedia.ai while also introducing a fresh AI-powered platform built from the ground up to effectively manage campaigns and represent providers across traditional linear, streaming and digital channels. New capabilities available […]
As the pendulum swings hard toward 1:1 personalization, a critical question emerges: Just because we can personalize every interaction, does it mean we should?
A quarter of all Connected TV (CTV) bid requests can’t be trusted.
That doesn’t mean fraud every time. Sometimes, it’s incomplete data. Sometimes, it’s oversimplified or mislabeled content. And sometimes, it’s more intentional misrepresentation. But the effect is the same: Advertisers don’t know if they’re getting what they paid for and publishers can’t be sure they’re getting fair value for their inventory.
Meta’s Q1 call sounded like an AI and hardware pitch, but under the hood it was still about one thing: investing in AI to squeeze more money out of its ads business.
Alphabet earned $109.9 billion in Q1 this year, up from $90.2 billion a year ago. And that’s not even the truly gobsmacking number.
Omnicom is rebuilding its media machine around Acxiom and agentic AI in a bid to push more spend to publishers and sidestep the “messy middle.”
The two longest-standing names in the affiliate and partnership marketing category, Rakuten and Impact.com, have decided to stop fighting each other and will instead fight together.
The Trade Desk announced that it will begin allowing mutual clients to use its DSP within the Pacvue or Skai platforms.
As AI chat starts to double as a shopping channel, the race is on to build an ad model that doesn’t undermine user trust.
