Top Companies' AI Moves

Today's Stories

1. 1

   Uber burned entire 2026 AI budget in 4 months after rolling out Claude Code

   Uber deployed Anthropic's Claude Code to its engineering organization in December 2025, and adoption accelerated rapidly—84% of engineers used it by March, climbing to 95% using AI tools monthly by spring, with roughly 70% of committed code originating from those tools. One executive's two-hour coding session cost $1,200; average monthly costs per engineer ranged from $150 to $250, while heavy users ran up bills of $500 to $2,000. Uber consumed its entire 2026 AI budget in just four months, illustrating how quickly costs spiral when companies roll out consumption-based AI tools broadly without constraints. The company's financial models did not anticipate the speed of adoption, and internal leaderboards ranking engineers by Claude Code usage encouraged higher consumption even though the teams promoting adoption were not responsible for the budget.

   Uber President and Chief Operating Officer Andrew Macdonald stated it was becoming harder to justify rising token costs without evidence that they were producing more useful features for customers. The core tension remains unresolved: whether the billions of dollars corporate America is pouring into AI are delivering measurable returns.

2. 2

   The Met launches AI tools to explore art collections with Google

   The Metropolitan Museum of Art and Google Arts & Culture unveiled two generative AI initiatives marking 15 years of collaboration. One stems from a six-month Technologist in Residence program where creative technologist Julia Daser used Google Gemini and Vertex AI to build and test prototypes in exhibition spaces with museum curators. The other is Art Aura, an interactive AI experience powered by Google Gemini that lets users drag artworks, styles, or descriptive phrases into a digital zone to discover thematic connections across The Met's collection. The tools are designed to deepen how people discover and engage with art both online and in person. Art Aura specifically creates a personalized portrait of a user's artistic taste by revealing hidden connections across centuries of work in The Met's collection, extending the museum's 15-year effort to make art accessible without distance constraints.

   The new Google Arts & Culture landing page for The Met is now live, offering access to over 200,000 digitized objects and 50 stories from the museum's collection.

3. 3

   McDonald's buys Dynamic Yield for machine learning–driven menu recommendations

   McDonald's acquired Dynamic Yield, a machine learning company that specializes in personalized recommendations, for around $300 million（約480億円）. The technology will enable drive-thru stations to adjust menu displays based on weather, time of day, and trending items, and to suggest products to customers based on their order history. McDonald's will use customer data to recommend items customers didn't know they wanted—similar to Amazon's cross-sell model—with the goal of increasing sales. The chain has already tested these recommendation techniques in limited form in 2018 and found results strong enough to extend the system chain-wide.

   McDonald's is integrating this into its broader modernization push, which includes mobile ordering and self-ordering kiosks being rolled out to thousands of restaurants over the next couple of years, according to CEO Steve Easterbrook.

4. 4

   AI infrastructure costs mounting as companies face compute demand surge

   Companies are confronting rapidly escalating costs for AI infrastructure and compute resources as their AI workloads expand, raising questions about whether AI projects are economically sustainable. The shift from experimental AI spending to sustained production deployment means businesses can no longer absorb AI costs as overhead—they must now justify AI investments like any other capital expenditure, which could reshape which companies and use cases remain viable.

   Organizations are beginning to evaluate whether the promised productivity gains and efficiency improvements from AI deployments justify the substantial ongoing compute and infrastructure expenses required to operate them at scale.

5. 5

   Pension fund struggles to measure hidden AI exposure across portfolio

   A pension fund attempting to quantify its artificial intelligence (AI) exposure discovered the task far more difficult than expected, revealing how deeply embedded AI has become across companies in ways that are not always transparent or easily identifiable. For institutional investors managing trillions in assets, understanding exposure to emerging technologies is critical for risk management and strategic allocation—yet the opacity around AI integration means many funds may be underestimating or overlooking their actual technology exposure.

   The pension fund's experience suggests a broader challenge for the investment industry: without standardized frameworks or disclosure requirements for AI exposure, investors lack clear tools to assess how dependent their portfolios are on AI-related capabilities and risks.

6. 6

   Vertex Inc. trading near 52-week low as Q1 2026 shows free cash flow turnaround

   Vertex, Inc. (NASDAQ: VERX), a provider of indirect tax compliance software, is trading at $12.48 as of July 14, 2026, near its 52-week low of $10.21. Q1 2026 results, reported on May 7, 2026, showed total revenues of $196.6 million（約310億円） (11.1% year-over-year growth), cloud revenues of $96.8 million（約150億円） (20.7% growth), and a critical positive inflection in free cash flow to $7.659 million（約12億円） from negative $12.250 million（約20億円） in Q1 2025. The company's Value Creation Plan, announced in April 2026, targets $60 million（約96億円） to $70 million（約110億円） in annualized cash savings beginning in 2027. Vertex operates in a compliance software market projected to grow from $40.82 billion（約6.5兆円） in 2026 to $74.12 billion（約12兆円） by 2031 at a 12.67% compound annual growth rate, driven by escalating regulatory complexity and digital transformation. Despite trailing-12-month losses (TTM EPS of −0.04), the free cash flow turnaround and strong cloud revenue growth signal a path toward profitability. The company's market capitalization of $2.02 billion（約3200億円） and price-to-sales ratio of 2.63 appear to discount both the strength of its recurring revenue model and its positioning in an essential, expanding compliance market.

   Vertex's Q2 2026 earnings report is scheduled for August 5, 2026, which management expects will demonstrate execution on its profitability targets. The company's FY2026 revenue guidance stands at $823.5 million（約1300億円）–$831.5 million（約1300億円）, with adjusted EBITDA of $202.0 million（約320億円）–$208.0 million（約330億円）. Cloud revenue is guided at approximately 25% growth for FY2026. Additionally, in April 2026, Vertex announced new AI capabilities embedded in Vertex Cloud to enhance tax and compliance workflows, and the company's solutions are now available on the Oracle Marketplace.