Opinion

We can’t simply trust AI to make up for bland creative with sheer volume. The real performance shift happens when we use AI to push creativity further.

Brands have gotten adept at finding and following their audiences across the media landscape. Today, that means everywhere: linear TV, CTV, YouTube and the open web, often in the same evening.

When it comes to identity, most marketers moved past third-party cookie concerns a long time ago. Identity today is not about a single technology or solution; it is about learning how to combine different signals in ways that allow campaigns to reach real people across channels while respecting privacy and maintaining performance.

Data brokers will need to process consumers data-deletion requests every 45 days starting August 1, 2026, or face heavy fines. 

In the rush to scale globally, US brands are often content with “accidental attention.” But attention isn’t a lottery; it’s a strategy that requires a deep familiarity with context in real time.

A proposed standard under discussion at W3C aims to redefine how ad effectiveness is measured across the web. This proposal would centralize measurement of ad effectiveness under the control of Google, Apple and Meta.

For years, programmatic advertising has operated on the assumption that most buyers didn’t really want to know how the system works. That’s changing. More advertisers are asking harder questions about where their media dollars actually go, and those questions are increasingly come from mid-market agencies that would historically rely on DSPs to manage the complexity of supply for them.

AI is only as good as the data that fuels it. In advertising, however, that foundation is often flawed.

CTV never fit cleanly into campaign execution models built for RTB-based trading. Whether agentic AI solutions can simplify the complicated CTV landscape for publishers will be their first real test case.

When Apple launched AppTrackingTransparency (ATT) in 2021, access to deterministic identifiers fell sharply as roughly 80% of users opted out of tracking. User-level feedback loops became sparse and biased, and iOS performance marketing shifted into a different measurement environment under SKAdNetwork (SKAN). Apple’s AdAttributionKit (AAK) later delayed postbacks, compressed conversion values and set privacy thresholds that made signal availability dependent on campaign structure and scale.

We now have plenty of evidence that AI can be an incredibly useful tool. But proof is also piling up that it erodes our creativity.

The industry has spent years debating third-party cookies, but AI has settled the debate. First-party data isn’t just preferred; it’s structurally necessary. And the capital is already moving.

Machines can now flag anomalies, surface trends and spin insights in seconds. Yet, even with its speed, AI still can’t decode the “why” behind the “what.”

No one in programmatic advertising needs another reminder about fragmentation. This complexity stands in sharp contrast to the original promise of the open internet. Programmatic was supposed to give marketers the freedom to reach audiences anywhere online by combining data, automation and inventory from across the web.

It’s widely reported that anywhere from 20% to 30% of programmatic video spend is lost due to supply-side misrepresentation, invalid traffic and low-quality inventory. That’s billions in wasted ad spend – not to mention billions in ad revenue siphoned away from premium publishers – further eroding high-quality video inventory.

Retail media is booming.
Spend is climbing, new networks are launching and every platform seems to deliver strong returns. And yet many marketers are asking the same uncomfortable question: How do we know what’s actually driving growth?

In 2011, three media devices captured 87% of consumer attention. Today, that figure has dropped to 65%, according to McKinsey. The fragmentation isn’t slowing down; it’s accelerating. Streaming services, social media, podcasts and gaming now compete for eyeballs, making traditional media planning feel like navigating with an outdated map.

If you want to protect your margins, your data and your long-term strategy, here are five questions worth asking before you sign anything.

The play “Data” sparks conversations about AI, surveillance, data tracking and predictive modeling. The ad tech world should be paying attention.

As we head further into 2026, the biggest risk for marketing orgs isn’t choosing the wrong AI – it’s letting “AI perfectionism” delay decisions so long that no decision gets made at all.

Should businesses start advertising on AI media platforms? Yes. But it depends on how consumers in your category are already using AI and how quickly your organization can respond.

Customers don’t need perfection. But they do need to know that a brand will make it right when something goes wrong.

When Truthset revealed that IP-to-postal matches are accurate only 13% of the time, it exposed an uncomfortable truth about connected TV advertising: The industry has been optimizing for the wrong metric.

If you buy CTV advertising, you’ve likely encountered two approaches to securing premium inventory: programmatic guaranteed (PG) and buying direct, also referred to as direct IO (DIO).

Marketers are projected to have invested nearly $400 billion in US media in 2025, based on estimates from MAGNA and eMarketer. About half of that will go toward finding new customers. Yet, as marketing investment grows, clarity on what actually drives ROI and growth continues to shrink. The loss of third-party identifiers, rising privacy restrictions and closed ecosystems have made it harder to see what’s working.

If a buyer wants real control, “domain rationalization” alone will never be enough. Buyers need “bid rationalization,” shaping the supply at the bid-request level so they see fewer, better, more outcome-relevant opportunities.

Many organizations are encountering a paradox: Performance appears strong, while durable growth remains elusive. How should performance be evaluated when the strongest signals no longer align cleanly with growth?

Complexity hasn’t made the CTV supply chain difficult to trust. This is a transparency problem and, more specifically, an ads.txt problem.

The advertising industry is full of noise about AI making buy-side and sell-side processes more efficient. That framing is convenient, but it misses a broader point, writes Snowflake’s Dennis Buchheim.

When marketers get too fixated on measuring short-term performance, they miss opportunities to capitalize on TV’s strength as a brand-building channel.