Top Companies' AI Moves

Today's Stories

1. 1

   AI answer engines are directing patients toward AbbVie and Galderma's aesthetic medicine products, concentrating market visibility among the two companies.

   AI answer engines are sending patients to AbbVie and Galderma, which together control 80% of aesthetic medicine's AI citations. This means when people search for aesthetic medicine information through AI-powered tools, the results overwhelmingly point them toward these two companies' products and services. Aesthetic medicine is increasingly discovered and researched through AI answer engines rather than traditional search. Because two companies dominate the AI citations in this space, they gain outsized visibility and influence over patient decision-making in a growing market segment.

   The concentration of 80% of citations among just two players suggests that AI answer engine results may be shaping patient choices in aesthetic medicine more heavily than in many other medical fields. This could amplify competitive advantage for AbbVie and Galderma while making it harder for smaller competitors to reach potential patients.

2. 2

   ProEnergy Supply launches IVAN, an AI procurement system designed to make independent wholesale distributors visible to AI buying agents in a $15 trillion（約2400兆円） B2B market where most lack the digital infrastructure of giants like Amazon and Home Depot.

   ProEnergy Supply launched IVAN, a patent-pending AI procurement network that makes distributor data—including negotiated pricing, credit terms, inventory, and manufacturer relationships—machine-readable and visible to AI agents. More than $1 billion（約1600億円） in distributor revenue is already under LOI or binding agreement with the company, and charter membership is open ahead of a Q4 2026 production launch. Gartner predicts that by 2028, 90% of B2B buying will be intermediated by AI agents, moving more than $15 trillion（約2400兆円） through AI agent exchanges. Independent distributors using manual processes for pricing and rebates are invisible to these agents and risk being bypassed entirely, while large competitors have already invested billions in closed agentic systems. IVAN lets independent distributors compete by surfacing their unique relationships and commercial advantages directly to AI buyers.

   IVAN deploys under each distributor's own brand, with PES taking only a small transaction fee—distributors pay only when they earn an order. The company has filed 49 patent claims in early 2026 and secured an exclusive partnership with Google-backed OpenSolar, which serves more than 28,000 U.S. solar professionals. Charter membership is now open for distributors in electrical, solar, plumbing, HVAC, and related verticals.

3. 3

   Texas Instruments stock shows strong recent momentum in AI and manufacturing expansion, but valuations diverge sharply—analysts say it could be 24% undervalued while others flag overvaluation risks.

   Texas Instruments has posted a 90 day share price return of 70.72% and a 1 year total shareholder return of 69.62%, driven by analyst attention to its AI power chips and battery monitoring products for electric vehicles. The company is in the midst of a multiyear capacity-expansion cycle centered on U.S.-based 300mm analog manufacturing. The stock presents two conflicting investment narratives. One analyst view frames fair value at $435.69 against a last close of $332.28—implying 24% upside—based on expectations that capacity buildout will improve margins and competitive position as utilization normalizes. A competing valuation model, however, suggests the stock trades above estimated future cash flow value of $213.69, appearing overvalued instead. The outcome hinges on whether the company's manufacturing assets ramp as expected and whether end demand in industrial and automotive markets holds.

   The key downside risk is that utilization ramps more slowly than expected or if end demand in key industrial and automotive markets softens. Investors should evaluate both the upside case (richer margins, improved cash flow recovery) and these warning signs before deciding.

4. 4

   California consumers sued major gas station operators for allegedly using AI pricing software to inflate fuel prices by up to 22 cents per gallon.

   A lawsuit filed Monday in Sacramento federal court claims that Walmart, Marathon Petroleum, BP, and 7-Eleven — which operate more than 1,700 filling stations across California — are using an AI tool from Kalibrate Fuel Systems Ltd. to automatically adjust pump prices. The complaint alleges station owners inflated gasoline by as much as 22 cents a gallon and diesel by 33 cents on top of already high prices. This is one of the first cases brought under AB 325, a California law passed last year that prohibits the use of shared pricing algorithms. California already has the highest gas prices in the US, and the state's fuel watchdog issued subpoenas to some station owners over high prices last month. Every additional penny costs California drivers about $134 million（約210億円） a year, according to the complaint.

   The suit seeks damages for California drivers who overpaid for gas under the state's antitrust law. Walmart said it is reviewing the complaint; BP declined to comment, and spokespeople for Marathon, 7-Eleven, and Kalibrate did not respond to requests for comment.

5. 5

   Marc Pritchard outlined Procter & Gamble's AI strategy and a new modular agency model at Cannes Lions.

   Marc Pritchard, P&G's Chief Brand Officer, detailed the company's approach to artificial intelligence and described a modular agency model during remarks at Cannes Lions, a major advertising and creativity conference. P&G is one of the world's largest advertisers, so how the company structures its AI use and agency relationships signals a broader shift in how major brands are organizing creative and media work in the era of AI tools.

   The modular agency approach—organizing partners in specialized, flexible units rather than traditional monolithic structures—may reshape how large advertisers manage creative production and AI-driven content.

6. 6

   DeepSeek's new reasoning model becomes #2 among open-weights options, challenging Anthropic and OpenAI's market leadership.

   DeepSeek released a new reasoning model that ranks #2 among open-weights reasoning models. The model supports 1M tokens of context (a measure of how much information it can process at once), up from 128K tokens in its prior version. Open-weights models are freely available for developers and companies to download and customize, unlike proprietary systems from Anthropic and OpenAI. DeepSeek's rise to #2 shows that lower-cost alternatives are closing the gap with leading AI labs, which may reshape pricing and adoption patterns in the AI market.

   The model's performance on reasoning tasks — a growing capability that enterprises are beginning to rely on for complex problem-solving. DeepSeek's ability to scale context window size (from 128K to 1M tokens) suggests the bar for what open-weights models can accomplish is rising quickly.