Oracle’s new AI portal, built on OpenAI’s technology, will let patients ask questions and get plain-language explanations about test results, diagnoses, and treatment options. Oracle understands patients are already using AI to interpret health records, so offering a safer, private way to do so is a smart move. Healthtech providers need to ensure AI tools for patients are highly accurate and offer clear guidance to users on how to use the tools, what the limits are, and when to seek human medical advice. Accuracy plus transparency is critical to building patient and provider trust.
The Google Pixel could grow to lead the smartphone market as sales surge, highlighting a strong consumer shift toward devices that balance competitive pricing, cutting-edge AI features, and ecosystem flexibility. The Pixel saw a whopping 105% YoY increase in sales in H1 2025, per Counterpoint Research, while overall global premium smartphone sales grew 8% YoY. Pixel’s growth points to an industry pivot where software-driven intelligence, rather than hardware specs alone, lead consumer choice. The smartphone race could move away from who offers the most storage or fastest processors and toward who delivers the most useful tools for daily life.
OpenAI struck a landmark $300 billion deal with Oracle to build AI data centers across the US, cementing Oracle as a critical partner in the race to scale artificial intelligence. The agreement, part of Project Stargate, covers more than half of the computing infrastructure OpenAI says it will need over the next five years, per The New York Times. AI’s future rests on who can actually deliver compute at scale. Marketers should diversify cloud and AI partners, experiment early, and prepare to shift strategies quickly as winners and losers emerge in this infrastructure race.
What CMOs say they expect to gain from AI: Efficiency and cost savings top the list of perks the industry hopes to gain from the disruptive tech.
AI platforms are no longer a side note in discovery—they’re driving measurable web traffic. Previsible’s 2025 AI Traffic Report shows that sessions driven by large language models (LLMs) surged 527% in just five months, per Search Engine Land. AI’s rise is reshaping how users find brands and information as web traffic declines, demanding an immediate strategic response from marketers. Those who adapt now—by tracking AI sessions, restructuring content for conversational interfaces, and optimizing across multiple models—will own the next wave of discovery. Those who don’t risk watching competitors capture visibility while their own content fades from discovery altogether.
Major web publishers, including Reddit, Yahoo, Medium, and Quora, are joining forces to push for a new content licensing system for AI publishers. The group is backing Really Simple Licensing (RSL), an open standard that lets publishers dictate how AI bots scrape their content and includes payment and royalty requirements. If publishers’ collective action can successfully enforce licensing terms for content scraping, regulators may follow with broader mandates. Visibility inside generative engines could change, pushing marketers to further prioritize generative engine optimization (GEO) strategies and comprehension of how AI responses source, cite, and surface branded content.
Microsoft is reducing its reliance on OpenAI by bringing in rival Anthropic to power key enterprise features, per The Information. With Microsoft 365’s entrenched position in productivity software, Anthropic’s integration could shift enterprise adoption trends away from OpenAI. If Anthropic gains traction, OpenAI risks losing one of its strongest distribution channels and with it, its influence on how AI is embedded in daily workflows. Marketers should watch to see not just who wins contracts, but who defines the next generation of workplace software.
Zendesk’s integration of OpenAI’s GPT-5 into its customer service stack has resulted in 30% faster response times, 95% reliability, and resolution of up to 90% of tickets in some cases, per VentureBeat. Fewer handoffs, quicker response time, and higher reliability are wins for both brands and customers. But there’s a catch—over-reliance on automation risks alienating users who still want a human touch when problems get tricky. For CMOs, lean into AI for speed and scale, but keep people in the loop to protect trust and brand experience.
At Tuesday’s “Awe Dropping” Apple event, the hardware giant unveiled next-gen AirPods, Apple Watch models, and iPhone 17 series. Apple is pacing its AI rollout, waiting until users are ready and the tech can show real value. By banking on product innovation and design, it secures its dominance in the smartphone space. However, as rivals push out increasingly capable AI features, Apple’s silence may come across less like strategy and more like struggle. It may be time for Apple to consider more outside generative AI (genAI) partnerships, lest it fall too far behind to catch up—even on its own terms.
40% of US adults say most or some of the health information on TikTok is trustworthy—the highest rating among major platforms, according to July data from KFF.
Eli Lilly launched a platform called TuneLab that gives biotech firms free access to AI drug discovery models that have been trained on years of Lilly's research data. In return, companies will contribute their own data so Lilly can improve the performance of its AI models. Lilly might be taking a bit of a risk by opening up its models to other companies, but the potential payoff of developing high-powered AI tools that can drive faster drug discovery, development, and time-to-market is one that’s too good to pass up.
A recent Pew Research Center study reveals a dramatic shift in online behavior: When users encounter AI-generated search overviews, they're almost half as likely to click through to websites and more likely to end their browsing sessions entirely. This fundamental change threatens the traditional internet business model where human traffic drives ad revenue.
Brands are testing the waters with AI-generated influencers as AI becomes a staple of advertising and everyday life. Telecommunications brand Vodafone is the latest to jump on the trend. Despite consumer hesitancy, AI is increasingly shaping the ad ecosystem, necessitating that advertisers take a balanced approach to leverage AI for its creative and operational potential without alienating consumers.
A federal judge rejected Anthropic’s agreement to pay at least $1.5 billion to settle a landmark lawsuit brought by a group of authors. Judge William Alsup expressed concerns that the ruling would be forced “down the throat of authors,” per Bloomberg Law. The case could set a legal precedent for future copyright battles between creators and AI firms. If approved, the settlement could set a legal precedent for future copyright battles between creators and AI firms. It could also push regulators to be more stringent in requirements for content licensing deals and cause AI companies to move more carefully when scraping data, considering the costs of legal proceedings.
On today’s podcast episode, we discuss how Americans view GenAI-made media, if the “AI concern gap” between AI experts and the general public will widen, and why some of GenAI’s negativity might not apply to ads. Join Senior Director of Podcasts and host, Marcus Johnson and Senior Analyst, Max Willens. Listen everywhere and watch on YouTube and Spotify.
IBM is positioning itself as a partner and integrator for enterprises at a time when various companies find themselves stuck in AI pilot limbo due to a lack of governance, per Marketech APAC. Its new global campaign, “Let’s create smarter business,” focuses on unifying its hybrid cloud, quantum computing, and business integration expertise to push enterprise AI from experiments to scale. CMOs should seize IBM’s ability to deliver safety and scale but protect agility. Build safeguards into contracts and keep internal or secondary partners ready to test new models as they emerge. That balance ensures AI adoption stays both credible and competitive.
OpenAI revised its projected cash burn through 2029 to $115 billion—about 230% higher than earlier estimates. This alteration demonstrates how capital-intensive model training and deployment have become and how far those costs are beyond what traditional startup economics can sustain. These financial forecasts illustrate a ballooning cash burn matched by surging investments and rising revenue expectations. OpenAI might need to explore tactics like affiliate links or in-chat advertising for monetization and added incentives and premium features to convert free users into paying ones.
AI is taking over tasks once handled by junior staff. Agencies and brands are embracing the efficiency and cost savings of AI—but at the risk of cutting the very pipeline that feeds future leadership, per MarTech. Marketers are realizing they can’t afford to treat AI as a zero-sum replacement for junior talent. The smart play is balance: Use AI for short-term efficiency while still investing in entry-level hires who can grow into long-term strategists and leaders. Pair automation with training, expand AI education, and let young staff lead adoption. That balance drives efficiency now while protecting tomorrow’s talent pipeline.