A new study shows that while commerce media enthusiasm is high, actual readiness is far lower. Nearly half of respondents believe they are operationalized, yet only 13% qualify as advanced across leadership, technology, and measurement. Most fall into nascent or emerging categories, limited by siloed workflows, manual creative processes, and fragmented data systems that prevent closed-loop attribution. Advertisers seeking accountable, performance-driven programs may be surprised by how few networks can truly support scaled, automated operations. The findings highlight a widening gap between ambition and capability—and the need for unified data, automation, and clearer measurement.
The New York Times is posting advertising momentum as its proprietary AI stack reshapes how marketers reach premium audiences. Q3 ad revenues climbed 11.8%, with digital ads rising more than 20% and generative AI tool BrandMatch now powering more than 150 campaigns. NYT’s first-party data engine interprets emotional cues, reading patterns, and topic affinities to deliver precise contextual placements—fueling strong campaign lift for partners such as Crown Publishing and Belmond. With 11.76 million digital subscribers and a diversified product suite, NYT’s fully owned ecosystem gives it targeting capabilities most publishers cannot replicate.
Personalization remains one of the most reliable attention drivers, but recent data shows consumers are still uneasy about how brands achieve it. People across age groups feel more negative than positive toward personalized ads—even though they pay more attention to content that feels relevant. The result is a widening gap between consumer expectations and marketer behavior. To unlock personalization’s upside, brands must apply AI to improve relevance and transparency, not just scale output.
OpenAI is rolling out a group chat option for ChatGPT to all logged-in Free, Go, Plus, and Pro users globally. The company said in a blog post that the feature is intended to help users collaborate with one another in the same conversation—such as working with friends, family, or coworkers on plans, decisions, and brainstorming. To capitalize on this new engagement tool, marketing leaders should start experimenting with group-based AI workflows and prepare for new discovery channels.
US connected TV (CTV) viewers fall back on YouTube when they can’t find anything else to watch, per Hub Entertainment Research. Ninety percent of 16- to 34-year-olds turn to YouTube at least sometimes when other streaming services don’t meet their viewing needs. Nearly three-quarters viewers age 35 and older make that switch at least sometimes. Poorly performing search and recommendation tools may be partially to blame. Streamers should target demographics and viewer interests and behaviors via platform analytics and interactive or live polls to capture attention, earn trust, and boost stickiness.
Three major AI releases—Microsoft’s Agent 365, Google’s Gemini 3 Pro, and xAI’s Grok 4.1—could point the way to how businesses will deploy and govern AI. Following OpenA’s GPT 5.1, each new product update approaches intelligence from a different angle: Microsoft is offering operational control, Gemini is touting multimodal reasoning and search, and xAI is demonstrating emotional fluency. The brands that map these tools to specific workflows—governance with Microsoft, discovery and search with Google, and engagement with xAI—could see faster execution, sharper insights, more resilient customer experiences, and tangible ROI.
Nearly 70% of large organizations are using genAI tools in marketing, but only 7% of global marketing leaders strongly agree that genAI use has improved the effectiveness of their campaigns, per a new study from Capgemini. The challenge may lie in budget control: More than half of AI initiatives are funded by IT. For AI to become the engine of growth that leaders envision, marketing needs to assume ownership, budget, and strategic influence to bridge the gap between its potential and its realized value.
Luma AI has secured a $900 million funding round led by Humain, pushing its valuation above $4 billion and marking one of the largest investments to date in AI-generated video. As agencies, studios, and brands increasingly adopt AI for editing, narration, testing, and full video generation, Luma’s raise signals a shift: AI video is becoming the creative backbone for modern advertising, powering faster iteration, scalable personalization, and multi-format production across every screen.
Adobe is acquiring software platform Semrush for $1.9 billion. The deal, which is expected to close in the first half of next year, will help Adobe expand beyond creative tools into a full-service marketing and analytics suite that can compete with Google and Meta. Whether or not marketers use Adobe today, the deal presents an opportunity to check tech stacks and evaluate search, design, and analytics tools. The acquisition could also help marketers trim martech spending by streamlining the tools they need to create content and stay on top of brand visibility and performance.
Google offered remedies to settle an antitrust case in the European Union following a nearly €3 billion ($3.5 billion) fine arguing that Google abuses its dominance in digital advertising. The EU’s tough stance signals that the global regulatory environment is intensifying.
Google is expanding its use of agentic AI across its advertising suite, announcing that Ads Advisor and Analytics Advisor—two new, Gemini-powered assistants—will roll out to all English-language Google Ads and Google Analytics accounts in early December. Per Google, the tools aim to make campaign management and data interpretation faster, simpler, and more conversational. AI copilots are becoming table stakes. With Google and Amazon both embedding agentic AI into their ecosystems, conversational interfaces will soon be the default way advertisers plan and manage campaigns.
AI is reshaping the ad agency landscape and eliminating the need for entry-level hires, according to a Sunup report that found that 91% of US senior agency leaders expect AI to reduce headcounts and 57% have slowed or paused entry-level hiring.
A year after enterprise software firms began rolling out AI agents, most tools now look and act alike—creating confusion for companies trying to choose the right solution. And because many rely on the same OpenAI or Anthropic models, their offerings are almost indistinguishable, per The Information. Brands should prioritize AI agents that connect across ecosystems, protect data, and scale smarter instead of locking into one vendor’s walled garden. Doing so builds resilience, flexibility, and trust in an increasingly crowded AI market.
35% of US employees who use unapproved AI tools at work have shared employee data, the most commonly shared category of potentially sensitive information, according to an August survey from Cint and Cybernews.
Last week, Tesla and Rivian approved two of the most aggressive CEO compensation plans in history—Elon Musk’s potential $1 trillion payout and RJ Scaringe’s $4.6 billion plan. Both hinge on hitting decade-long performance and valuation targets tied to EV production, AI innovation, and market capitalization growth. Why it matters for brands and marketers: This compensation era spotlights the rise of the personality-driven company. Musk and Scaringe are seen not just as CEOs, but as brand assets whose visibility and vision influence valuation. For advertisers, the message is that leadership narratives can serve as marketing multipliers that help drive brand identity and, for better or worse, brand reputation.
Spending on martech tools will continue to grow over the next five years, but data silos, inefficient ROI measurement and training gaps could hold back the tools’ potential. 78% of B2C organizations increased their martech budgets over the last five years, and that pace isn’t slowing: 79% plan to raise them again by 2029, per McKinsey’s Rewiring Martech report, and 34% will boost it by at least 11%. Despite these aggressive investments, only 35% of organizations say their martech operations have reached a “transformational” level of maturity. CMOs should ensure teams are supplied with the technical skills to aid martech’s advancement and treat the tools as a part of operations across the board—not just an IT task. They should also connect martech success metrics directly to clear outcomes—like customer retention—to prove its value across the organization.