Large Language Models

Today's Stories

1. 1

   Michaels launches Ask Mike AI shopping assistant

   Michaels announced Ask Mike, an AI shopping assistant built with Google Cloud's Gemini Enterprise for Customer Experience. The tool was developed in six weeks and is now live on the retailer's website, offering personalized product recommendations and creative guidance based on shoppers' descriptions. The assistant moves beyond keyword filtering to help shoppers find products through natural conversation—for example, describing a child's birthday party or seeking fabric for DIY projects. In just a few weeks, Ask Mike has fueled nearly 75,000 conversations, positioning Michaels to capture market share as it expands party and craft offerings following the closures of Party City and Joann.

   Michaels plans to release more features, including AI-generated product overviews and contextual prompts added to product pages. Other retailers like Ulta Beauty and Macy's have also built Gemini-powered AI assistants, while Lowe's partnered with OpenAI for its Mylow AI adviser.

2. 2

   Uber Cuts 10% of Customer Support Team, Blames AI

   Uber is laying off roughly 10% of its Community Operations team (global customer support) and requiring remote staff to work from an office three days a week. VP Megha Yethadka said in a memo that the restructuring is needed to "layer AI on" and scale customer solutions, framing AI as both the opportunity and the catalyst for the change. Uber joins Salesforce, Block, Klarna, and others attributing customer service cuts directly to AI agents handling more workload. But Gartner predicts half of these companies will end up rehiring for similar roles by 2027, arguing AI still cannot fully replace human judgment in service work. Commonwealth Bank of Australia and Klarna have already reversed their AI-driven cuts after service quality suffered.

   The roles eliminated at Uber tilted toward escalations, training infrastructure, and process design—not front-line scripted work. Employees affected had an average of over 7 years tenure. Whether Uber's restructuring actually works may depend on how well AI handles the "fragmented processes" the company says it must fix first.

3. 3

   Only 6% of hotels appear in AI search results as travel industry grapples with legacy systems

   The Skift Data + AI Summit 2026 convened executives from Hilton, Marriott, Booking.com, Priceline, and Air Canada to discuss AI adoption in travel. Key findings include that only 6% of hotels surface in AI search results, and 95% of GenAI projects report zero ROI. Leaders identified infrastructure modernization, agentic AI deployment, data ownership, and personalization as critical challenges. The travel industry is discovering that AI adoption requires more than technology—it demands workforce capability, organizational accountability, and legacy system overhaul. Marriott's Colin Coleman noted that 'the technology is not the hard part anymore' and that identifying problems worth solving is the true challenge. For hotels and travel platforms, being invisible to AI search is a direct revenue risk, since AI is becoming the primary entry point for travelers.

   The report documents how budget, aspirational, and luxury travelers use AI differently and where they enter the funnel. Speakers from Sierra and Amadeus emphasized that agentic AI (AI systems that can act autonomously) is already in production at leading companies, meaning delay is becoming a competitive disadvantage. Priceline's CTO highlighted preference data as the next personalization layer, requiring customers to see and edit their own data as a trust requirement.

4. 4

   Uber lays off 10% of customer service staff, cites AI efficiency gains

   Uber is laying off about 10% of its community operations team and requiring remote customer service employees to relocate to an office city and work there three days a week. The company cited AI as the reason for the restructuring in a statement on Thursday. Uber's VP of global community operations stated that AI presents "a massive opportunity for us to accelerate output, improve quality, and scale customer solutions at pace," but the company needs "an effective organization to layer AI on" rather than fragmentary processes. This marks Uber joining other major companies—Block, IBM, and Snap—in cutting jobs explicitly tied to AI investment.

   CEO Dara Khosrowshahi has said Uber is slowing down hiring as it invests more in AI. The layoffs affect less than 1% of Uber's 34,000-person global workforce. Last month, Uber also laid off a quarter of its human resources and recruitment staff, though that cut was unrelated to AI.

5. 5

   S&P Global adds AI-powered document tool to Capital IQ Pro via Farsight partnership

   S&P Global Market Intelligence announced a new AI-driven capability within its Capital IQ Pro platform, delivered through a strategic partnership and minority investment in Farsight. The tool will be available later this year as an add-on and automatically generates client-ready materials—pitch decks, confidential information memoranda (CIMs), and valuation materials—using a firm's own templates, prior work, and standards. The capability lets bankers and investors accelerate document preparation while maintaining firm-specific quality standards, combining S&P Global's trusted financial data with AI-powered workflow automation. This reflects S&P Global's shift toward pairing its data depth with integrated AI tools, positioning it to help clients move from insight to action more efficiently.

   The tool becomes available later this year as an add-on to Capital IQ Pro. The minority investment signals S&P Global's commitment to embedding best-in-class AI into its Market Intelligence division's operating model, which is designed to pair data and domain expertise with more integrated AI-powered tools and workflows.

6. 6

   Palantir Shifts AI Strategy to Operational Infrastructure

   Palantir Technologies is positioning itself as an operational layer for enterprise AI deployment, rather than as an AI software vendor alone. The company's Ontology platform connects data, business processes, and decision-making into a unified model, while its AIP Bootcamp program accelerates customers from proof of concept to production. In Q1 2026, Palantir delivered 85% revenue growth, including 133% growth in U.S. commercial revenues, with a 60% adjusted operating margin and 53% GAAP net margin. By embedding AI into existing business workflows and customer technology ecosystems, Palantir creates a moat that makes switching platforms increasingly difficult. This operational-layer approach addresses a real customer need: most enterprises care more about production-ready AI than experimental projects. The combination of deep integration and expanding usage creates durable recurring revenue growth and long-term customer value.

   As customers deploy more workflows and connect additional data sources through Ontology, the depth of integration determines whether Palantir can sustain its competitive advantage. The financial performance—especially the 133% U.S. commercial revenue growth and 60% adjusted operating margin—signals whether this strategy is translating into sustainable business momentum.