Honeywell signs deal with Google Gen AI for industrial companies

Google Gemini, the flagship generative AI from alphabetis tapped by Honeywell to search the industrial giant's massive data base for insights that can lead to lower maintenance costs, higher productivity and opportunities to upskill employees.

“The path to autonomy requires plants to work harder, people to work smarter and processes to function more efficiently,” Honeywell CEO Vimal Kapur said in a statement announcing the collaboration, which will provide insights into genetic AI to industrial customers starting in 2025.

Kapur recently told CNBC that the biggest problems AI can solve in an industrial context begin with a generational labor shortage, as falling birth rates in the industrialized world mean there are fewer workers available for jobs that were popular 25 years ago . “Everyone has this problem in the industry,” he said at a recent CNBC “Evolve AI Opportunity” event. Kapur told CNBC that AI will enable an employee with five years of experience to perform at the same level as an employee with 15 years of experience using AI co-pilots.

AI-powered agents offered by Google help automate tasks for engineers and help technicians resolve maintenance issues. Kapur had told CNBC at the recent event that Honeywell will soon integrate connectivity into aircraft engines to enable predictive maintenance and reduce the time needed for work in workshops.

Honeywell says that while Gen AI is already being used in the industrial sector, this partnership will take the opportunity to a higher level than current “Gen AI point solutions” and “go beyond simple chat and predictions” by bringing Google AI to the Honeywell Forge IoT connected platform.

Honeywell Forge, an Internet of Things platform that includes information from industrial designs, manuals and real-world performance of Honeywell products, will leverage Google Cloud's Vertex AI and Google's large language models to create AI trained on this data -Develop agents.

“We are moving from automation to autonomy,” Suresh Venkatarayalu, Honeywell CTO and president of Honeywell Connected Enterprise, said in a Google blog post about the deal. “Our goal is to equip companies with AI agents that support workers in real time – on the factory floor and in the field.”

Workers can ask the AI ​​questions like: “How did this unit work last night?” or “Why is my system making this noise?” according to the companies.

Google AI will offer engineers images, videos, text and sensor readings.

“Industrial companies play a critical role in our daily lives, be it the aircraft we fly, the medical devices we use or the sensors that control the air conditioning in our offices,” said Carrie Tharp, vice president of strategic industries at Google Cloud. in the blog post. “With an entire generation of workers retiring and – in many cases – no one behind them, industrial companies are under enormous pressure.”

Honeywell said it is also exploring the use of Gemini Nano, an on-device version of AI, for operations in data centers, hospitals, refineries and warehouses, among others, particularly in rural areas where internet connectivity can be an issue. Gemini Nano can deploy AI directly on scanners, sensors and controllers for autonomous operations.

Encouraging industries across the economy to adopt genetic AI is critical for AI giants like Google to turn a capital-intensive technology into a profitable opportunity. According to Honeywell data, 82% of companies in the industrial sector that identify as leaders in AI are lagging behind in adoption, with only 17% having fully launched initial AI plans.

Companies across the economy are also hoping that their internal data will become as valuable as the large language models like Gemini that are driving the genetic AI boom. Clément Delangue, co-founder and CEO of Hugging Face, one of the world's most highly valued Gen AI startups backed by Amazon, Nvidia and Google, said at the CNBC Evolve AI Opportunity event: “Data and datasets are…” next Limit for AI.” He noted that over 200,000 public datasets have been shared on Hugging Face’s platform, which uses an open source approach to developing AI models, and the growth rate of datasets added to the platform is faster than that Growth rate of new large language models.

“The world will evolve to where every single company, every single industry, even every single use case will have its own specific, tailored models,” Delangue said.

Siemens and Microsoft announced a Gen AI deal for the industrial sector late last year, which included an AI co-pilot for cross-industry use.

Kapur sees generational artificial intelligence as a growth opportunity for the workforce-challenged industrial sector that will open up new revenue opportunities, rather than primarily as a productivity tool, and he is optimistic that the adoption curve will steepen quickly. “Awareness is high, adoption is low, but there will be a tipping point,” he said at the recent CNBC AI event. “I really believe 2025-2026 will be a big year for AI adoption in industry.”