Honeywell CEO says AI will ‘redefine automation’ as labor shortages mount
June 11, 2026
“The power of AI is going to redefine automation,” Kapur said on “Mad Money” on Thursday.
His comments come as Honeywell prepares to spin off its aerospace business on June 29, leaving behind a pure-play automation company. Honeywell’s automation business provides sensors, controls and software that help customers manage critical operations across hospitals, airports, data centers, semiconductor facilities and liquefied natural gas plants. Cramer’s Charitable Trust, the portfolio used by the CNBC Investing Club, owns shares of Honeywell.
Last fall, Honeywell spun off Solstice Advanced Materials
“We are taking the opportunity to build a pure play automation company across multiple sectors, and opportunity is more compelling now, with AI coming in,” Kapur said.
Kapur said AI makes those systems more valuable because they already generate enormous amounts of operational data that can now become actionable optimization insights, improve decision-making and automate tasks that previously required human intervention.
The need for those tools is growing as businesses struggle to find enough skilled workers, according to Kapur. Honeywell’s customers are facing shortages of operators and technicians across sectors, he said, while aging populations and slowing workforce growth are likely to make the problem worse over time.
“Net workforce is not going to be increasing. It’s going to be decreasing over a period of time,” Kapur said.
As a result, companies are increasingly turning to AI and automation to do more with fewer people. However, Kapur said customers are viewing the technology as a way to drive growth rather than simply cut costs.
“Our customers are looking at it not as a productivity opportunity,” he said. “They are looking at it as a revenue-generation opportunity.”
Kapur believes Honeywell is uniquely positioned to capitalize on that trend because of its deep domain expertise and the vast amount of operational data already flowing through its systems.
“Physical AI for us is built on our domain knowledge,” he said. “It’s built upon the data which we possess in our system.”
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