Name: Honeywell CEO: Why “Physical AI” Won’t Replace All Industrial Jobs—and What It Will Change
Uploaded: 2026-01-21T21:34:00Z
Duration: 5 min 46 s
Description: Vimal Kapur, Honeywell CEO, speaks with WSJ Leadership Institute President Alan Murray on how AI is moving from digital tools to physical infrastructure. Kapur explains how Honeywell is using “physical AI” to help factories, refineries, and other businesses operate amid shortages in skilled employees—augmenting workers rather than fully replacing them.

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Vimal Kapur, Honeywell CEO, speaks with WSJ Leadership Institute President Alan Murray on how AI is moving from digital tools to physical infrastructure. Kapur explains how Honeywell is using “physical AI” to help factories, refineries, and other businesses operate amid shortages in skilled employees—augmenting workers rather than fully replacing them. Photo: Michael Claudio/WSJ

https://m.wsj.net/video/20260121/82a9ad68-bba9-4313-9bbe-d09a813ea49e/2/hls/manifest-hd-wifi.m3u8

Vimal Kapur, Honeywell CEO, speaks with WSJ Leadership Institute President Alan Murray on how AI is moving from digital tools to physical infrastructure. Kapur explains how Honeywell is using “physical AI” to help factories, refineries, and other businesses operate amid shortages in skilled employees—augmenting workers rather than fully replacing them.

Honeywell CEO: Why “Physical AI” Won’t Replace All Industrial Jobs—and What It Will Change

I;m here with Vimal Kapur, who is the CEO of Honeywell. Vimal, thank you so much for taking the time-

Thanks, Alan. Thanks for having me.

To be here. We're standing outside the Congress Center where President Trump is about to speak.

That's right.

So thanks for breaking away for a minute to talk to us. What's your mission here in Davos this week?

This is my fifth year.

It is.

Right, and you know, 80% of our time is with customers. This is a great place for us to meet our customers from Asia and Europe.

Yeah.

So that we are able to connect with them and avoid bit of a travel, but I think it's a rhythm which builds in, and that's bulk of it. I mean, I easily get 25 to 30 customers meeting.

Wow, it's remarkable to people.

That's right. It's a very productive way, and it's not introduction type, it's progression of the business. These are our existing customer. It's what's going on, what's next, their strategy, and our strategy. So it's very productive way for us to come in, and I will highly recommend. It takes a while to build that cadence.

Yep.

It doesn't happen on year one, but after you stay on it, it's just very productive.

That's the powerful thing about Davos, yeah. So Honeywell has been around for over 100 years, but you are in the midst of a profound transformation that starts with dividing it into three pieces.

Right.

Can you talk about what you're doing?

So, you know, Honeywell did so well in the last 20 years, and it's great run for our shareholders, great return of investment. Now at a time where it has to find its next 25, 50 years, and that is gonna happen through growth, which was the reason we said we should split into three companies, each dedicated to a specific team. Specialty chemicals, which is our Solstice Advanced Materials business and Honeywell Aerospace and Honeywell Automation. So we will complete the separation with aerospace by second half of this year, which is gonna create three public companies. And each public company had its own capability to grow in their respective space and benefit from the growth opportunities which it has.

Well I want to talk about the third company, automation, because I understand that's the one you're going with.

Absolutely.

And it's also the one that's dedicated to what all these pavilions up and down the promenade in Davos are dedicated to, and that's AI technology, how to take advantage of this tsunami technology that's washing over companies. How is Honeywell gonna do that?

So before I answer the question, I'm gonna step back and share you some external factors, which is gonna make AI very relevant for the sectors we serve, which is the industrial sector. And the primary issue our customers are facing is skills shortage, which is coming from the fact that population is shrinking in all mature markets, and for that matter, even in countries like China. So the question is, when population is shrinking and less workforce is available, how we can run our operations, a complex supply chain, energy sector, building the infrastructure? So you need less people to do more work, or less experienced people to do work or more experienced people. So that's kind of a context, and that's where physical AI world of Honeywell comes in. That all the systems we have supplied to our customer over the last 50 years and build this vast install base, we collect data from those systems and build a relevant set of analytics which benefit our customers. And we're so unique about it is, there are two things or three things unique about it. First is the data is not available in public domain. You can't train the data from-

There's no public LLM that has this data.

There's no data, so data is in a controlled system of Honeywell or many of our peer companies. Number two, the problem statement changes by end market. So problem if I have to solve for life sciences is different from a problem I've solved for a refinery or for a warehouse or for a hospital. They don't have the same issue, so data analytics have to be purposeful. It means you need to have a domain knowledge sufficient enough to solve the problem. And last but not the least, the solution has to be highly deterministic. It can't be that it's nearly right. It's not a probability-based system. You are, you know, running an actual operational system.

So, yeah.

So it just makes it fascinating for us that our customers have a real issue to deal with, shortage of skills.

Yeah.

We build capabilities which augment skill of the people. So the punchline here is physical AI augments existing workforce. It's not automating work.

Yeah.

It is not replacing jobs. And I think that's a dialogue we have to separate.

And you're doing it with domain expertise?

We are doing it with domain expertise on this data, which is cohorted in our systems.

So your belief is this company can win in the battle against all these tech companies up in the East Promenade?

We're already winning. Were already winning. And we partner with all the tech companies. We use the cloud for Microsoft and Amazon. We partner with Google for all their large language model capability. We use the infrastructure from Dell and NVIDIA. So these are all our partners. We use their capability and make it purposeful for our customers. That's our job.

Fascinating, yeah. Now it's not gonna be named Honeywell.

We will reveal the new name closer to when the spin is ready. So we'll have to choose a new name for Honeywell.

And the one other thing I want to ask you about is your investments and your expertise in Quantum. Is that gonna be part of Honeywell Automation?

No, it's already a standalone company.

Standalone, okay.

We own 52 or 53% of that company. And we are working to make it totally standalone. We don't think we are the rightful owner. As we are simplifying Honeywell, that's already a standalone company with Honeywell ownership. So at some point, Honeywell will, you know, value down its ownership from 52% to a much lower number, and that's work in progress. We are excited about the opportunity.

Well, it's a fascinating challenge you have.

Absolutely.

We wish you the best of luck. Thanks for taking some time here to share what you're doing with us.

Thank you very much. Thanks for this opportunity.

I hope you have a great Davos.

Absolutely. Thank you.

Thank you.

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