Yahoo is building out a range of new AI-powered tools within its demand-side platform, or DSP, for mid-market, performance-focused advertisers. These include automated options for activating and managing media designed to make the DSP more accessible and easy to use for all kinds of advertisers.

The development signals an expansion beyond Yahoo DSP’s core business, which has historically serviced enterprise advertisers facilitating ad buys for brands like Kroger, Arby’s, and Planet Fitness. The new tools could help the platform extend its market penetration, attracting a wider variety of advertisers, such as ecomm platforms and direct-to-consumer brands. 

“AI is enabling us to better support existing customers while making our technology accessible to a broader range of advertisers, and we will share more when ready,” a Yahoo spokesperson said in a statement.

Yahoo is hiring a dedicated team to build out these offerings, according to a source familiar with the matter. 

A job posting for a head of growth accounts for the new project appeared on LinkedIn earlier this month. The range for the role is $217,905 to $473,710 annually, with a core mandate to “drive net-new advertiser acquisition across mid-market brands, with a strong focus on CTV and full-funnel programmatic solutions.”

The company is also seeking out talent to fill strategy and product development roles associated with the new features, the source said. 

Yahoo is in the early stages of building out these new features and is eyeing a launch date for later this year, according to the source. 

Yahoo’s core enterprise DSP business has grown substantially over the last year. The company strengthened its privacy-safe targeting, began testing AI agents within its DSP, and inked a handful of deals likely to bring more offsite retail media dollars onto the platform. Plus, Yahoo became a key beneficiary of advertisers’ disgruntlement with The Trade Desk, which lost millions of dollars last year to rival DSPs. Yahoo’s lower fees have proved particularly appealing to The Trade Desk defectors. 

Now, by folding in more performance-minded features, Yahoo could bolster its competitive edge with advertisers for whom automation, cost efficiency, and accessibility outweigh the sophisticated customization options offered by some other DSPs on the market. 

Spotify is rolling out interactive carousel ads, the company announced on Tuesday. The company is looking to attract more dollars across the marketing funnel from brand awareness down to generating sales—while also accommodating changing users preferences towards a more visual platform.

The new swipeable ads allow brands to spotlight up to six different products. Each slide in the lineup includes its own image, link, description, and optional pricing or promotional information. The ads will pop up in the app’s Now Playing view appearing on screen while users actively consume content.

Though the carousel ad format was pioneered by Meta in the mid-2010s, Spotify is only now rolling out the offering as users spend more time watching—and not just listening—to Spotify. This is thanks to the platform’s foray into music videos and its push for podcasts to be published with full video.

“The user experience is becoming a much more interactive, audio and visual experience,” Brian Berner, Spotify’s global head of advertising revenue and partnerships, told ADWEEK. “It’s just time for us to make sure that our ad strategy reflects the trends we’re seeing and the user engagement we’re seeing from our consumers.”

Priceline and GNC are among the brands piloting Spotify’s carousel ads.

The platform is also introducing a branded takeover of select Spotify playlists including some of its flagship selections like Rap Caviar, Today’s Top Hits, and New Music Friday.

Advertisers can pay to be the only featured brand on a given playlist where their name appears prominently on the playlist’s main page and their ads run exclusively during play. To improve the user experience, listeners hear fewer ad breaks throughout the duration of a sponsored playlist.

Both carousel ads and sponsored playlists are served to users of Spotify’s free tier. 

Meanwhile, the company has enhanced its performance tooling. It added A/B testing capabilities and automated bidding—which uses machine learning to optimize ad delivery and budgets—directly into its Ads Manager. Although, these features are considered table stakes for major advertising platforms. 

With the updates it’s clear that Spotify is positioning itself as a more full-stack ad platform—one capable of delivering upper funnel and mid to lower tier funnel offerings, in addition to performance tools that help marketers get more out of their media buys. 

“What we’re trying to build from an ad strategy is to challenge that preconceived notion of audio just being an upper funnel reach play and build a full-funnel suite,” Berner said. “Do I think overnight we’re going to go from upper funnel to suddenly driving bazillions of app installs? Not overnight. But when I think about the next five years…we are absolutely trying to challenge the status quo and show Spotify to be a full-funnel offering.”

To support that vision, the company is bulking up its ads infrastructure and increasingly investing in AI. Last spring, it launched a global ad exchange and began letting advertisers produce custom audio ads using generative AI tools at no additional cost. This year, it plans to roll out additional AI updates, Berner said.

Asked why a marketer would choose to shift more spend toward Spotify particularly in a crowded market with behemoths like Meta, TikTok, and Google vying for dollars, Berner said simply: “User engagement, user attention, time spent.” He might be on to something. On average, consumers spend about two hours a day on Spotify and 90% use Spotify as part of their daily routine, according to recent survey data the company collected from over 5,000 consumers. For marketers, he said, it’s that user attention and engagement that should prove appealing. “That’s advertising 101: Fish where the fish are.”

Over the last few week, X eliminated over 20 nontechnical roles, and has laid off Angela Zepeda, the ad industry veteran who joined the social platform in 2024 as its head of global marketing, the Wall Street Journal reported Thursday.

Zepeda’s LinkedIn profile indicates she lost her job last month.

The company is trimming talent as its billionaire owner Elon Musk prepares to take his rocket company SpaceX public in an IPO targeting a valuation of around $1 trillion. SpaceX could reportedly file as soon as this week. X was folded into Musk’s AI company xAI in a $45 billion merger last year; then, early this year, SpaceX also joined xAI.

Zepeda was the first true marketing leader appointed at X in the Musk era, filling a role that had been vacant since 2022. 

Her priority at the platform was to distill X’s image and ethos to users and to advertisers, the latter who have historically generated more than 90% of the platform’s revenue. X has lost reams of advertisers, and, as a result, about half of its ad revenue since Musk’s takeover in 2022 (tallying $1.25 billion in 2025 compared to $2.43 billion in 2021)—largely over brand safety concerns sparked by Musk’s lax approach to content moderation.

Last spring, Zepeda told ADWEEK’s editor-in-chief Ryan Joe that X planned to roll out a major brand campaign later that year that would position X as the enduring digital town square. That brand campaign never materialized.

Now, X is hyper-focused on ramping up revenue, offering fresh financial incentives to lapsed advertisers, and bringing on a new chief revenue officer, longtime private-equity executive Jon Shulkin.

Neither X nor Zepeda could be reached by press time. 

Google is turning its demand-side platform for advertisers, Display & Video 360 (DV360), into an AI-powered media buyer backed by Gemini, the tech company’s flagship family of AI models. 

While Gemini tools have been baked into DV360 since at least last spring, they were primarily used to aid marketers in audience discovery, surface reporting insights, and offer tweaks to help optimize campaigns here and there. Now, Gemini will become the true operating layer of the DSP, moving upstream and taking on a larger role in media planning, the company explained at its NewFronts presentation in Manhattan on Monday.  

“Marketers can upload their media plan and automatically translate it into a comprehensive campaign setup,” said Bill Reardon, general manager of the enterprise platform at Google Ads, on a call with the press. 

In its presentation on Monday, the company also hyped up additional AI-powered updates for ad buyers: AI will be deployed within DV360 to help manage real-time fluctuations in live sports inventory across connected TV; and soon, marketers will be able to use Ads Advisor, an agent embedded in the Google Ads Console, to build custom reporting dashboards.

Beyond supercharging the buyer experience with automation, Google also indicated that it is investing more deeply in cross-channel measurement—specifically in connected TV attribution. The company is debuting Confidential Publisher Match, a new identity model that can link marketers’ first-party data with signals from streamers like Roku in a privacy-safe trusted execution environment.

“This shift empowers you with a cross-device conversion memory, connecting a CTV impression directly to a purchase,” Reardon said. 

The push could help Google level up its measurement capabilities on non-owned inventory environments in CTV, specifically, an area where it’s historically been weaker than rivals like The Trade Desk.

To further buoy its CTV measurement push, Google is turning to retail media data. 

The company is working with Kroger to integrate the retail giant’s first-party shopper data into YouTube and Google’s other partner inventory. The company will also roll out SKU-level reporting in DV360, “so brands can see the precise impact of their YouTube and display ads on Kroger sales,” Reardon explained.

“This really changes how brands think about YouTube and its direct impact on sales,” Christine Foster, Kroger’s group vp of commercial strategy and operations, said in a statement. “Now, advertisers can reach Kroger shoppers on the most-watched video platform in the world—and measure how their spend drives sales at the SKU level. The reach is massive, the ability to unify once-siloed efforts is profound, and the opportunity to connect with shoppers across the full customer journey has never been better.”

In fact, YouTube is the cornerstone of Google’s NewFronts pitch this year. It’s the company’s crown jewel, expected to bag nearly 12% of all CTV ad revenues this year, per Emarketer estimates.

While YouTube isn’t getting any new ad formats, Google is aggressively pushing for wider adoption of a select number of the platform’s ad offerings. Now, the company said Monday, YouTube’s pause ads and creator takeovers—which allow a brand to buy out all of a specific creator’s ad inventory for a select period—can be bought through DV360. 

Increasingly, the DSP is being designed to act as a buying environment that reinforces Google’s walled garden, encouraging buyers to transact on YouTube in particular. 

Reardon only underscored the notion that Google is more tightly binding its buy-side tool with its owned inventory and measurement capabilities. “Gemini, with [DV360] and YouTube, will be core to the success of the future of advertising,” he said.

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YouTube isn’t satisfied with serving one or two slices of brands’ creator marketing demands. It wants the whole pie. 

On Monday, ahead of YouTube’s NewFronts presentation this week, the Google-owned video site announced that it is repackaging BrandConnect, its tool for connecting YouTube creators with brands for sponsorship deals, into what will now be known as Creator Partnerships—and giving it an AI makeover. The platform will be backed by Gemini, Google’s suite of frontier AI models, to intelligently pair advertisers with creators that suit their needs. 

“It’s historically been challenging for advertisers to find the right creator to work with and then scale their efforts globally,” said Melissa Nikolic, director of product management for YouTube Creator Ads, on a call with press. Now, she said, the company is integrating Google’s AI spine into YouTube’s suite of creator tools—a change that she expects will “make it easier for brands to discover and work with creators at scale.”

Creator Partnerships will also be integrated with YouTube Studio for creators, Google Ads, and Google’s demand-side platform Display & Video 360 (DV360) into one centralized hub for advertisers.

Within Google Ads or DV360, users can generate a target list of YouTube creators through simple natural language queries.

“You can say, ‘Find me us tech creators reviewing sports gear with high Gen Z retention,’ and our AI will surface creators who match, and will include insights about their channel, their audience, sample videos, and more,” Nikolic explained. 

Gemini analyzes billions of data points on everything from brand mentions to subscriber growth to surface these recommendations. 

“It’s designed to save time for brands who traditionally have had to manually sift through eligible creators in the YouTube Partner Program, and may have missed some really great creators. It also gives creators of all sizes more opportunities to be discovered,” Nikolic said.

When possible matches are identified, advertisers can then filter down to a shortlist of top picks and reach out en masse to multiple creators at once. Within the platform, advertisers can track and manage their creator deals.

With the overhaul, YouTube aims to eliminate the need for laborious influencer discovery that has historically required agency planning and resources paired with manual keyword- or tag-based searches. 

In the near future, the process will be even easier, Nikolic suggested: “In the coming months, advertisers will be able to simply input their campaign brief. Our AI will recommend the ideal creators to drive a marketer’s goal.”

YouTube has also embedded a unified measurement feature into Creator Partnerships. Here, paid ads and organic creator content performance data come together in one workflow, in theory making it easier for marketers to get a clean, deduplicated look into the material impact of their creator partnership investments.

The company is making Creator Partnerships available to some partners via API, enabling marketing agencies or SaaS companies to plug the discovery and matching capabilities into their own tools.

“Creator marketing has matured into a core growth channel, but the industry has lacked the depth of measurement needed to scale with confidence,” said Tim Sovay, the chief business development and partnerships officer at influencer marketing platform Creator IQ, in a statement. He said that the rollout of the Creator Partnerships API will help give advertisers “trusted, first-party insights that help unlock deep creator audience understanding within their existing workflows,” whether on YouTube or on another platform like CreatorIQ.

On the whole, however, YouTube is now positioning itself as a comprehensive operating system for creator marketing—compared to a platform that simply aids in influencer partnerships. In the process of that transformation, YouTube could threaten the businesses of third-party creator platforms. 

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X is imploring advertisers who’ve abandoned the platform to return, promising some a sweetheart deal of up to $200,000 in extra value, according to a leaked pitch deck viewed by ADWEEK. 

On one slide, presented to an ad agency with many clients that have not invested in the platform for a number of months, X suggested it would toss in 50% of added value for every dollar spent, up to $200,000 per advertiser. 

Details of what constitutes “added value”—whether discounts, free ad credits, rebates, or something else entirely—were unspecified.

The incentive was framed as a “return-to-platform incentive” in the slide.

The incentive structure is the same as a promotion X ran last year for Omnicom specifically, though the company’s pitch to the holding company also included additional financial incentives like 15% in media credits for spending on X’s inventory via auction, excluding revenue-sharing products.

The platform ad revenues were roughly halved after Elon Musk’s $44 billion takeover in 2022. Last year, it brought in about $1.25 billion compared to 2021’s $2.43 billion from ads, per Emarketer estimates. Many advertisers dialed back their investments or exited the platform altogether over brand safety concerns posed by X’s lax approach to content moderation and misinformation under Musk’s leadership. 

More than 20 slides of the leaked deck were dedicated to promoting X’s brand safety credentials, transparency practices, and built-in controls for advertisers that help them avoid “sensitive content.” 

In one slide, X explained how Grok—the AI chatbot operated by X’s parent company xAI and integrated natively into X—is being deployed to aid brand safety. “ALL (sic) posts on X are reviewed by xAI’s Frontier model Grok for Brand Suitability,” it read. It also claimed that profile ads will only show up on X profiles that have been “fully vetted by Grok, which evaluates all compliance with X’s Rules and policies and Brand Suitability.” 

The push aligns with a broader pattern for X, which is increasingly positioning Grok as a cornerstone of its brand safety practice, as reported by ADWEEK earlier this month. The push arrives just weeks after Grok users filled X with a deluge of nonconsensual sexualized deepfakes of real users—a scandal that has prompted a handful of regulatory investigations and lawsuits.

In the slides, X also pitched the platform as an ideal advertising environment for high engagement and high performance. It purported to be “#1 for ad attentiveness,” and said X users are 45% more likely to buy products they’ve seen advertised on X compared to non-X users, according to GWI figures from Q2 of 2024 through Q1 of 2025. 

The company also claimed that, per X internal data from August 2 to Dec 7, 2025, the platform observed a 140% lift in click-through rates, a 43% increase in conversion rates, and a 37% increase in sales. 

Ad performance—and ad-linked sales in particular—has been a fixation of Musk’s as the company looks to recover ad revenues. In February of 2023, Musk wrote in a post: “Almost nobody buys anything on Twitter, but almost everyone on Instagram does.”

As recently as this month, Musk posted an interactive survey on X asking users if they’d ever made a purchase based on an ad they’d seen on the platform. Of some 1.6 million responses, 88% they had not.

Have you ever bought anything based on an ad on this platform?

— Elon Musk (@elonmusk) March 9, 2026

X did not provide an on-the-record comment by press time. 

In a heated discussion with leading AI scholars Tuesday evening, Eric Schmidt, the American businessman who held the top post at Google from 2001 to 2011, argued that AI systems can develop unexpected behaviors that limit the extent to which companies like Google can implement preemptive safety and governance mechanisms into their products.

A central “problem” with regulating frontier AI models, is that, sometimes, “a new feature emerges in these systems that is not tested, testable,” Schmidt said onstage at the annual Isaac Asimov Memorial Debate, moderated by physicist Neil deGrasse Tyson in Manhattan. 

“We can stop [the emergence of new features or behaviors], and therefore stop all progress, by law, by banning larger models,” he said, “but as long as you have this new emergent power, you have deep reasoning, deep capabilities, and they will make mistakes. You have to be tolerant.”

Schmidt—who also served as chairman of Google’s parent Alphabet from 2015 and 2017 and advised Alphabet for three years after that—supported the 2014 acquisition of DeepMind, the unit that now houses Google’s most cutting-edge AI research. 

Schmidt said that AI developers, like Google and others “should be held accountable” if they’re found in violation of the law, but emphasized that AI developers frequently have to ship AI products and retroactively correct bad behaviors they didn’t predict as the models evolve. 

“I went through this when I was at Google, in earlier versions of [Google’s AI] technology, where the system would actually do something that was wrong, and we fixed it. And we fixed it as fast as we could, because we had to, because it was the right thing to do,” he said. 

Google did not respond with an on-the-record statement by press time. 

Schmidt was challenged by Latanya Sweeney, a professor of government and technology at Harvard and the former chief technology officer at the Federal Trade Commission, who cast doubt on the suggestion that AI leaders would happily comply with regulations. She said that leading tech companies have proven time and again to ignore key regulations or attempt to bend the law to their commercial interests. 

Sweeney is not off base. Just last year, U.S. federal judges found Google guilty of operating not one but two illegal monopolies—one in adtech and one in online search. The decisions came six years after Meta, then Facebook, was forced to cough up $5 billion to the FTC and modify its business practices after it was found to have mishandled reams of user data in the now infamous Cambridge Analytica scandal.

“Technology just ignores [laws] and rewrites them. That’s true in social media. It’s true in AI as well,” Sweeney said to Schmidt. “We already have laws [that] address issues of bias, consumer protection, and so forth. None of those are enforced online.”

Sweeney suggested that mitigating the risks associated with AI, including algorithmic harms and biases encoded into AI systems from their training data, requires more foundational changes rather than ex-post-facto fixes. 

“There are questions about existential harms in the future, but there are a lot of harms happening right now. And it doesn’t have to be that way….It depends on who this AI is servicing, and in particular, the design of the technology—the decisions made in that design is really determining what our values will be,” she said.

Schmidt pushed back on the implication that all harms could be preempted with better design and training, arguing that leading AI programs are not simple machinery but complex, non-linear systems that often develop unforeseen capabilities. But he agreed with Sweeney’s assertion that Silicon Valley leaders have at times “rushed” products to market, adding, “They’ve found all sorts of problems, and then they’re busy correcting them. I think that’s the cycle, and it’s very hard.”

Luckily, he said, AI developers have evaluation cards and safety testing teams in place to mitigate as much risk as possible in advance. 

But these measures are insufficient for protecting humanity, according to another panelist, Nate Soares. Soares is president of the Machine Intelligence Research Institute in Berkeley, California and co-author of If Anyone Builds It, Everyone Dies, a 2025 book on the existential risks posed by AI. 

In leading AI labs, the primary focus areas for safety and governance today are interpretability research, or “trying to figure out what’s going on inside the AIs’ heads,” and model evaluation cards, “which are trying to figure out how dangerous the AIs are,” as Soares explained.

He likened these efforts to a comically inadequate attempt to curtail nuclear disasters. “If someone was making a nuclear power plant in your hometown, and you went to them and you said, ‘Hey, I hear that this uranium stuff can have lots of energy benefits, but also can melt down when things go badly. What have you guys got that makes you think you’re going to get the benefits and not the pitfalls?’ If the engineers say—‘Oh yeah, we’ve got two crack teams working on this; the first team is trying to figure out what the heck is going on inside, and the second team is trying to measure whether it’s currently exploding’—that’s not a good sign.” 

Soares expressed urgent concern about the future of AI for the same reason Schmidt found the technology to be too difficult to govern: because frontier AI models tend to act in ways their makers didn’t explicitly design or even anticipate.

Schmidt argued that the benefits of AI will ultimately outweigh the risks, disagreeing with arguments made by Sweeney, Soares, and other academics onstage. 

“The companies that are doing this work are well aware of the dangers, and I know this because I work with them on this, and we spend an awful lot of time talking about them,” Schmidt said. “We can talk about some of them, but that is not to take away from the enormous benefit of these technologies.”

Schmidt, deGrasse, Sweeney, and Soares were joined onstage by Kate Crawford, a professor of AI at the University of Southern California, Chris Callison-Burch, a University of Pennsylvania computer science professor, and Cindy Rush, a statistician who teaches at Columbia University. 

X will temporarily bar creators from monetizing their content through its Creator Revenue Sharing program if they share AI-generated videos of an armed conflict without clearly disclosing that it was made with AI. The move comes three days after the U.S. and Israel launched strikes against Iran, sparking a chain of violent reactions.

X’s head of product Nikita Bier made the announcement in a post on X Tuesday morning, writing: “During times of war, it is critical that people have access to authentic information on the ground.” He added that AI platforms have lowered the bar to making “content that can mislead people.” 

Today we are revising our Creator Revenue Sharing policies to maintain authenticity of content on Timeline and prevent manipulation of the program.

During times of war, it is critical that people have access to authentic information on the ground. With today’s AI technologies,…

— Nikita Bier (@nikitabier) March 3, 2026

Creators who post AI-made videos of armed conflict without adequate disclosure, Bier said, will be suspended from Creator Revenue Sharing for 90 days. Additional violations will lead to permanent suspension from the program.

Replying to one user, Bier explained that creators would need to click on the menu and select ‘Add Content Disclosures’ where they will find a ‘Made with AI’ label option.

X will be able to check whether videos are AI-generated using available metadata imbued by AI systems in combination with Community Notes, X’s crowd-sourced fact-checking tool, Bier added. 

X debuted its revenue-sharing initiative in mid-2023. Through the program, X Premium-subscribed creators or verified organizations with at least 5 million organic impressions in the past three months who have at least 500 verified followers are eligible to cash out on their content. These users to earn based on engagement—a 2024 departure from previous rules that determined payouts based on ad impressions. 

The policy update comes two days after a Wired investigation found X drowning in misinformation about the conflict in Iran. Various months- or years-old videos were presented as new, some posts included outright disinformation about specific attacks, and  AI-generated imagery and videos spread like wildfire, shared even by the Iranian newspaper Tehran Times.

X has been recently plagued with its own endemic issues related to AI-generated content, too. In late December and early January, the site was overwhelmed with nonconsensual sexualized deepfakes of real users after users prompted Grok AI, embedded within X, to produce the images. Though the platform eventually tweaked its rules, the changes were far from comprehensive, as users can still use various Grok interfaces to produce such content. 

Meanwhile, the company has also been signaling its willingness to crack down on content that might deter advertisers from spending on X. Last week, X held a webinar for advertisers—the presentation for which was obtained by ADWEEK—promoting its brand safety capabilities. X’s ad revenues are about half of what they were before billionaire Tesla boss Elon Musk acquired the platform for $44 billion in late 2022, according to data from Emarketer.

X did not comment by press time.