The latest multibillion-dollar AI deals are a reflection of the massive computing power needed to build AI products and services—and 2025 has shown just how steep the costs can get. We expect price increases to trickle down to brands, resulting in more expensive access to AI tools and services. Brands should stay agile—diversify vendor bets where budgets allow, test across ecosystems, and align with the stacks most relevant to audiences and workflows. Failing to anticipate and respond to this hardware–cloud–AI consolidation could leave brands locked into costly, limited ecosystems with little room to maneuver.
Microsoft is extending AI further into its productivity tools with Agent Mode in Excel and Word, plus a new Office Agent in Copilot chat, per The Verge. The tools automate Microsoft 365 spreadsheets, documents, and PowerPoint through prompts, mirroring a trend already visible in Google’s Gemini rollout across Drive, Docs, Sheets, and Slides. For marketers, the payoff for adopting AI in 365 and Drive could be higher productivity and stronger performance, possibly at a fraction of the cost of separate AI subscriptions. The downside is lock-in and the risk of over-reliance on single platforms.
AI use outside of content creation still ranks low among small and medium-sized businesses (SMBs) despite interest, showing a gap between curiosity and capability. While two-thirds of SMBs use AI for marketing and content creation, only 35% are applying it to customer service, per Revenued’s AI Usage Among Small Businesses report. If SMBs want AI to move beyond content creation, they’ll need to invest not just in tools but in training, governance, and measurable pilots. To close the gap between interest and implementation, brands should use upskilling as a differentiator, start with low-risk pilots, and build trust in outputs.
Airline group Lufthansa plans to cut 4,000 roles by 2030 to boost profitability as it leans into AI adoption. The Germany-based company said most layoffs will be limited to administrative roles as it evaluates what work won’t be necessary in the future. Identifying areas where AI is making work redundant and redeploying or retraining employees to higher-value tasks—rather than hacking away at worker numbers—can preserve institutional knowledge and build trust in the technology’s use across an organization.
Nearly all (97%) of Goldman Sachs’ Gen Z interns use AI in their personal lives, up from 86% in 2023, per the company’s annual intern survey. For a majority of generative AI (genAI) use cases, Gen Zers prefer that real people stay involved, but there are exceptions. More than a third (38%) of respondents said they were good with shopping AI results with no human oversight. For brands, this might mean leaning into Gen Z to train on genAI skills, understand where to get the most value out of AI, and what AI pilots can be cut or built on to improve efficiency.
More than half (53%) of US consumers turn to AI for conducting shopping research, per an August Adobe survey.
Consumers are increasingly receptive toward digital ads and generative AI in marketing, per Kantar’s Media Reactions 2025 report. While consumers increasingly see digital ads as the norm, advertisers must work harder than ever to cut through the clutter and deliver relevant, memorable experiences that drive action.
OpenAI is preparing to turn ChatGPT into an advertising platform, posting a new role for an engineer to build systems for ad integration, campaign management, and attribution. The move could position ChatGPT as a new challenger to Google, Meta, and Amazon’s ad businesses. Already a major driver of referral traffic to retailers like Walmart, Etsy, and Target, ChatGPT has clear potential to evolve into a commerce and ad engine. But execution will be critical: Poorly integrated ads risk undermining user trust, even as AI-driven ad formats are projected to grow at triple-digit annual rates in the coming years.
Generative AI (genAI) has been pitched as a path to efficiency. Instead, 95% of enterprise pilots have failed to show measurable impact, per MIT Media Lab. AI adoption among larger firms peaked at 13% to 14% in early 2024 and dropped to about 9% by mid-2025—a nearly 30% YoY drop. AI adoption fluctuations serve as a warning. CMOs face a choice—either invest in structured AI training and workflow integration or risk eroding brand credibility and trust. Training employees to know when not to use AI will be as important as teaching them how to use it.
A growing share of consumers are integrating AI into their shopping journeys, with ChatGPT driving nearly 21% of Walmart’s referral traffic in August and playing a major role for Etsy, Target, and eBay. GenAI is now the second-biggest source of product recommendations, with trust in AI shopping tools soaring from 46% to 86% in just months. Retailers are experimenting with frictionless AI-driven checkout, while Salesforce predicts AI tools will drive 21% of global holiday orders this year. Amazon, however, is blocking AI crawlers to protect its ecosystem, a risky strategy that may drive shoppers to rivals.
The news: Cloudflare is rolling out a new feature that gives content publishers greater control over how Google scrapes and presents their content and helps them keep content out of AI summaries without opting out of Google search results all together—a choice Google hasn’t allowed. For publishers, Cloudflare’s feature could provide further control over how content is indexed and brands are compensated. Experimenting with the tools will help companies understand how AI summaries are affecting their traffic and searchability.
Alibaba released two cutting-edge additions to its Qwen 3 large language model (LLM) that are ripe for enterprise application.Qwen3-Omni gives enterprises a rare mix of flexibility, cost savings, and global reach that many proprietary models can’t match. Qwen3-Max could push Alibaba into the frontier of agentic AI, combining massive scale with code-generation tools that could rival other developer-first models. For CMOs, Qwen3-Omni’s multilingual and multimodal skills could power richer customer interactions and unlock real-time insights from video, audio, and text data.
OpenAI and Google are racing to lock in users in two of Asia’s most populous markets with budget-friendly AI subscriptions, per TechCrunch. OpenAI’s $4.50-per-month ChatGPT Go has expanded from India to Indonesia, while Google countered with a similarly priced AI Plus plan ($4.56). Marketers should prepare for audiences in India, Indonesia, and beyond who will be AI-native from the start. Analyzing AI adoption and usage trends opens opportunities for when campaigns run along AI search results. That means testing localized creative strategies and viewing Asia as the engine driving the next phase of generative AI growth, not a secondary market.
AI is no longer a nice-to-have in retail, it’s becoming essential. It helps make shopping smoother, sparks product discovery, and guides motivated customers to make purchases. But trust still matters most. The retail playbook needs to adapt, using AI to enhance the shopping journey rather than replace it.
A new Teads Connected TV paper shows AI has firmly entered the mainstream of video advertising. Sixty percent of marketers now use generative AI to create scripts, voiceovers, and visuals, while others rely on AI tools for audience insights, performance analysis, and real-time optimization. The findings highlight a clear opportunity—marketers that combine AI’s scale and predictive testing with human oversight can build campaigns that are both efficient and distinctive.
Now that most financial institutions (FIs) have deployed or piloted genAI, some recurring lessons have emerged. Implementing these lessons learned can help FIs prevent massive losses from failed pilots. Governance helps set expectations, parameters, and metrics before the bulk of the money is spent—helping prevent project failure and disappointment. 79% would prioritize governance if starting AI implementation over. Seventy-one percent of respondents would have engaged stakeholders earlier, involving them in planning meetings. This would help FIs ensure alignment and reduce delays that could arise from misunderstandings and disagreements partway through.\
Nvidia will invest up to $100 billion in OpenAI in $10 billion stages and supply the processors for 10 gigawatts of new AI data centers—an energy load equal to New York City’s peak demand or enough to power 7 million to 9 million US homes, per CNBC. Big Tech is locking arms to secure control of the AI future. These alliances blur the lines between investor, supplier, and customer, concentrating power among a few giants. If the project delivers, Nvidia’s dominance grows. If not, the “Stargate effect” looms—ambitious AI ventures that overpromise and underdeliver.