Audience customization is the top GenAI use case for marketers who produce multiple versions of video ads (42%), per a March Interactive Advertising Bureau (IAB) survey.
The news: Google Ads is ending manual language targeting, taking over a significant element of campaign management. In lieu of manual targeting, Google’s AI will detect user language automatically using signals such as language settings and historic search activity. Our take: Brands should consider auditing current campaigns to identify where automated language detection might create gaps and establish safeguards, such as breaking out campaigns by region or market and including clear, native-language text in headlines and descriptions to signal intended language to both users and Google’s systems.
The news: Meta is moving forward with its ad automation ambitions by introducing new options to consolidate ad targeting, per a company announcement. Meta’s Ads Manager page noted that “some detailed targeting options have been combined,” and that ads using now-unavailable options no longer deliver starting in January. Our take: Automated AI campaigns are the path forward as long as giants like Meta continue pushing for automation and away from manual—necessitating advertisers take key steps to adapt. Campaign goals must be reframed for an AI-first environment.
Generative AI is rapidly moving from novelty to necessity in advertising, collapsing production costs and timelines while expanding creative possibilities. National TV ads that once required six figures and weeks of work can now be made in days for a fraction of the budget, opening broadcast-quality campaigns to smaller advertisers. With nearly 90% of large video advertisers already adopting AI, use cases like personalization, ideation, and versioning are proliferating. Yet consumer skepticism remains strong—especially among older audiences—underscoring that human craft and cultural nuance still matter. The challenge ahead: merging automation’s efficiency with trust and authentic creativity at scale.
The news: ByteDance’s TikTok paid people to lend their likenesses to digital avatars, often paying less than $1,000 per actor, per The New York Times. The avatars, which are free for TikTok advertisers to use, were meant for TikTok alone but have appeared on ByteDance’s video-editing tool CapCut and on platforms like Facebook and YouTube. Our take: AI-based productions are democratizing advertising, allowing even the smallest firms to produce high-quality ads with minimal effort and budgets. Forty-five percent of smaller advertisers will use generative AI (genAI) in their videos by 2026, per IAB’s 2025 Digital Video Ad Spend Report. However, brands must weigh the benefits against the risks, considering 31% of US adults say AI use in ads would make them less likely to buy, per CivicScience.
Retailers have built lucrative revenue streams from retail media networks (RMNs), leveraging on-site ad inventory and first-party transaction data. As the potential grows for consumers to shop through AI agents instead of retailer sites or apps, those data streams and ad surfaces are at risk.
The news: OpenAI CEO Sam Altman is warning of a growing AI investment bubble. “Are we in a phase where investors are overexcited about AI? My opinion is yes,” Altman said during a dinner with a group of reporters, per The Verge. Still, he emphasized that AI remains “the most important thing to happen in a very long time.” Our take: Altman’s warning about an AI bubble applies to marketers too. The temptation to chase every shiny new AI tool is real, but teams should develop an AI experimentation roadmap with clear outcomes to avoid wasting resources. Pushing vendors for case studies can help maximize budgets.
The news: As entry-level roles for younger hires shrink, ad schools are retooling their programs to promote AI fluency and skills. Miami Ad School, Virginia Commonwealth University’s Brandcenter, and London’s School of Communication Arts are adding AI education curriculum focused on concepting, campaign execution, and portfolio development, per Adweek. Our take: CMOs who understand how AI is reshaping both entry-level roles and leadership expectations will be in a better position to build resilient, AI-ready teams. However, companies shouldn’t focus only on hiring junior employees with existing AI literacy—keeping resources open to train both new and current workers as AI evolves will encourage a diversity of skills and experience on staff.
ChatGPT saw 52.2 million US unique visitors in June, up 180.6% from last July, per Comscore.
Hogarth CEO Richard Glasson says AI hasn’t diminished creativity—it’s made craftsmanship more essential. By pairing genAI with human expertise, Hogarth is reengineering production to meet nonstop content demands without sacrificing cultural nuance or brand voice. In an era when 54% of marketers fear AI will erode creativity, the agency’s hybrid model positions craft as the premium differentiator.
The advertising industry’s age and experience mix is shifting fast. In the US, entry-level roles are shrinking as automation replaces routine tasks, while in Australia, “juniorisation” favors younger, digitally fluent hires over seasoned veterans. Agencies face a balancing act—bringing in Gen Z talent to master AI-driven tools and authentically shape campaigns, while retaining senior expertise crucial for strategy, oversight, and client trust. Without a robust entry-level pipeline today, the industry risks a future shortage of homegrown leaders just as marketing grows more complex.
The news: New data from Digital Content Next revealed that Google AI Overviews lead to as much as a 25% decrease in publisher referral traffic, reinforcing brands’ and publishers’ ongoing concerns over the tech’s adverse impact on content effectiveness. Our take: AI Overviews will continue usurping referral traffic from publishers, meaning that the brands who last will be those who adapt to the change rather than fight it. Brands must optimize for AI visibility, not just search rankings.
On today’s podcast episode, we discuss how the world’s largest online retailer is weathering tariffs so far, the biggest takeaway from Prime Day, and why Amazon’s AI future could be wearables. Join our conversation with Senior Director of Podcasts and host, Marcus Johnson, Senior Director of Briefings Jeremy Goldman, and Analyst, Rachel Wolff. Listen everywhere you find podcasts and watch on YouTube and Spotify.
The news: Apple could soon renew its smart home and robotics plans with a slew of products. The hardware giant is planning an AI-enabled tabletop robot, per Bloomberg, a smart home camera, and a smart speaker with a display. This could all be accompanied by a major Siri upgrade built on large language models (LLMs). Our take: This could be Apple’s biggest ecosystem play since the iPhone. If successful, it could drive growth in a post-iPhone era, reestablish Apple in the AI game, and usher in a new era of home-based intelligence.
The news: Apple is bringing back blood oxygen monitoring for Apple Watch as part of its health and wellness features. Apple discontinued the feature in the US in 2023 after a patent dispute and court ruling forced the halt. The takeaway: Apple still leads smartwatch brands with a 22% market share, but its dominance has slipped. Health and wellness features incorporating AI assistance are key for future growth. Tech companies should market wearables as health tools for consumers, especially to older demographics who have greater health needs but lower smartwatch adoption rates.
The news: Microdramas may be the next big thing on mobile, at least that’s what a new Hollywood startup is hoping. MicroCo plans to use AI to help create 1- to 3-minute vertical-video shows meant for the mobile screens. Microdrama seasons would be 30- to 100-episode arcs—think telenovelas in short bursts. Our take: Microdramas are a growing venture and are ideal for the quick-hits crowd occupying social media. MicroCo could come out ahead if it can create and monetize buzzworthy content. While brands have the opportunity to advertise within short videos, they might fare better creating their own microdramas to appease consumers who are tired of ads.
AI search startup Perplexity shocked the industry with an unsolicited $34.5 billion all-cash bid for Google’s Chrome browser—despite Chrome not being for sale. The offer comes as a US court weighs whether Google must divest Chrome after an antitrust ruling, and positions Perplexity as a ready operator if a spin-off is ordered. Even if the deal never closes, the move amplifies Perplexity’s profile, pressures Google, and underscores the growing importance of distribution channels alongside model quality in AI competition.
The news: Despite consumers’ rising use of AI agents for search, shopping, and discovery, brands are falling behind on generative engine optimization (GEO) strategies. 47% of brands have no deliberate GEO strategy or have no idea if they appear at all in AI agent responses, per a new report from Cordial. Another 47% have only just begun optimizing content for AI discovery. Our take: To boost visibility, brands should optimize for conversational context and create structured, machine-readable content that AI can index, like clear website FAQs, TL;DR summaries, and detailed product specs. Expanding presence across social platforms that feed AI training models, such as Reddit, Quora, and YouTube, can also improve chances of surfacing in AI-generated responses.
The news: Advertisers are broadening how they use AI tools for marketing campaigns beyond data analysis, per a report from DoubleVerify. Nearly half (46%) of advertisers plan to use AI for creating media strategies in 2025, up slightly from 2024. An equal percentage of marketers are using AI for bidding optimization and mid-flight plan optimization. Our take: Widespread AI adoption in marketing is inevitable as AI tools proliferate across industries. Success hinges on how, not if, marketers implement the technology. Consumers are more likely to trust brands that are transparent about how they use AI in their ad materials.
The news: Google announced an expanded use of AI to combat invalid ad traffic in a bid to help advertisers preserve budgets and maintain trust, per a recent blog post. Though Google has previously used AI to prevent invalid traffic (IVT), the company has updated its “industry-leading defenses powered by large language models,” with the goal of better analyzing ad placements, suspicious user interactions, and app and web content. Our take: By taking concrete steps to reduce IVT and address transparency concerns, Google may begin to rebuild trust with advertisers.