Top Companies' AI Moves

Today's Stories

1. 1

   Honeywell CTO Mehul Patel: we'll stop talking about AI

   At an IMTS media panel in Chicago, Honeywell Technologies CTO Mehul Patel predicted companies will eventually stop talking about AI because it becomes routine, and Fanuc America CEO Mike Cicco said AI's effect on physical robots is still at the starting line. Patel's prediction implies AI's value will be judged by whether factory systems run reliably on their own, not by how often AI is named in strategy decks.

   Fanuc's claimed protection layer, which Cicco said sits between what a robot is told and what it does, is the test of whether autonomous factory work earns trust. Watch how Fanuc's robot total grows past the 1 million reached in 2023.

2. 2

   Morgan Stanley gives Booking Overweight rating and a $230 price target

   Morgan Stanley analyst Matthew Cost began covering Booking Holdings with an Overweight rating and a $230 price target, calling AI "a new acquisition channel and product opportunity for OTAs rather than a threat." That counters the sector-wide worry that AI search tools and chatbots will cut travel platforms out of the booking process, so Morgan Stanley is arguing AI sends high-value traffic to them instead.

   The thesis hinges on whether AI tools really behave as a search layer that funnels bookings to incumbents, or bypass them. Morgan Stanley expects online travel bookings to grow about 7% annually from 2026 through 2030.

3. 3

   Lockheed's Jim Taiclet: tripling PAC-3, quadrupling THAAD

   CEO Jim Taiclet told a Morgan Stanley panel Lockheed will pair the F-35 and advanced missiles with cheaper autonomous and counter-drone systems, using AI-driven "mission technology roadmaps," and expects to triple PAC-3 and quadruple THAAD output while investing $8 billion to $9 billion through 2030. The shift recasts Lockheed as a "mission integrator" rather than solely a maker of individual weapons, and the multiyear agreements behind the production targets point to sustained demand rather than one-off orders.

   Taiclet named supply-chain capacity as the biggest scaling risk, so the tripling and quadrupling targets hinge on whether suppliers keep pace. Watch the JATM/AIM-260, which he said has not yet entered full-rate production.

4. 4

   John Deere adds JD AI assistant to its operations center

   On Sept. 1, Deere introduced JD, an AI assistant in its operations center that lets farmers ask about their own data — fuel use, yields, machine performance, harvest timing. The tool deepens farmers' reliance on Deere for understanding their own operations, not just their equipment, which could reinforce its existing market position.

   Deere says farmers should stay in control of their data and understand how it is used — the test is whether those controls hold up as the company's software role grows.

5. 5

   Lockheed Martin wraps Riyadh AI internship

   Lockheed Martin completed a Riyadh summer internship for Saudi university students in AI, robotics and advanced manufacturing, with projects on unmanned-aircraft factory automation and extracting rotorcraft log-card data. The programme mixed practical projects with mentoring by experts and aimed to build local technical skills; some participants joined the company's supply chain team.

   Whether such programmes translate into durable local industrial capability is unproven, and it hinges on how many interns stay in the sector. Watch Lockheed's continued engagement in the country.

6. 6

   ServiceNow launches AI Control Tower, Context Engine, Shift Zero for AI governance

   ServiceNow introduced AI Control Tower, Context Engine, and Shift Zero, tools for managing AI agent access, identity governance, and security compliance as enterprises expand AI-driven automation across operations. These tools link ServiceNow's AI narrative to concrete spending on governance and compliance rather than just productivity chatbots, giving large clients a way to monitor agent access and apply security policies across workflows.

   The near-term swing factor is how quickly customers adopt AI Control Tower without compressing margins as AI infrastructure costs rise. Watch the pace of adoption and whether governance tooling becomes crowded and weakens pricing power.