Honeywell CTO on Physical AI, Honeywell Forge & the Dell AI Factory

Industrial organizations have spent decades optimizing automation. The shift happening now is fundamentally different.

Honeywell CTO Suresh Venkatarayalu has studied AI since his early computer science days, working on neural networks over 30 years ago. He points to a major shift underway in industrial environments: traditional systems were built to operate deterministically, following fixed rules and predictable outcomes. Foundational AI introduces systems that can interpret context, adapt to changing conditions, and improve over time.

That progression from automation toward autonomy sits at the center of what Honeywell is building with Honeywell Forge on the Dell AI Factory.

At Dell Technologies World 2026 in Las Vegas, Patrick Moorhead and Daniel Newman sit down with Suresh Venkatarayalu, CTO of Honeywell, and Sam Grocott, SVP of Product Marketing and AI Product Management at Dell, to examine how physical AI is transforming industrial operations and what it takes to move from early AI discovery into enterprise-scale deployment across mission-critical environments.

Key Takeaways:

🔹 Honeywell’s AI journey spans more than 30 years, but this is the real inflection point. Teams are moving from systems that simply execute instructions to systems that can see, think, act, and learn inside industrial environments built on deterministic controls.

🔹 Honeywell Forge is entering a new phase after a decade focused on connectivity, visibility, and workflow applications. They’re now training AI models on 30 years of operational knowledge, including technical documentation and service data tied to 50–60 million assets, to support real-time decision-making and autonomous operations.

🔹 The conversation around enterprise AI has shifted from experimentation to scale. Sam Grocott noted that last year’s focus was simply getting started. Now the challenge is operationalizing AI across entire workflows and business processes, not layering isolated tools onto existing systems.

🔹 Hybrid AI is evolving faster than hybrid cloud ever did. Enterprises are actively balancing workloads across cloud, on-prem, edge, data center, and device environments simultaneously, making orchestration and infrastructure strategy far more complex than early AI narratives suggested.

🔹 Honeywell chose the Dell and NVIDIA ecosystem because physical AI requires everything from compact edge compute to high-performance infrastructure, alongside simulation through Omniverse and model deployment through NVIDIA NeMo. The ability to connect those layers securely and at scale was critical.

🔹 This is an operational opportunity. Extending asset lifecycles and improving control system performance with AI could unlock effectively unlimited throughput gains across tens of millions of industrial assets.

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SURESH VENKATARAYALU:

If we can extend the life cycle of an asset and allow it to operate extensively and then if we can manage the processes the control system processes around these operations better I think the throughput is unlimited in a big way.

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PATRICK MOORHEAD: 

The Six Five is on the road here at Dell Technologies World 2026 here in Las Vegas. The big theme here is about making agentic A.I. real at anywhere including on prem. That was my biggest takeaway, at least Daniel.

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DANIEL NEWMAN: 

Yeah there was a lot. I mean it was a it was a great keynote and I think there was a lot about bringing AI to life. And I think there was a lot about bringing the real world and AI together meaning industrial businesses pharmaceutical health sciences. You know a lot of us technologists we spend a lot of time playing with the toys and in our little labs. But seeing it brought to the real world and seeing it being done at a scale that enterprises can operate and realize benefits. I think that was the big theme that Michael and the team had at this year's Dell Technologies World.

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PATRICK MOORHEAD: 

Yeah, for sure. Great customer walk-ons. Eli Lilly was great to see. We saw Samsung in a video, but we saw Honeywell, which you and I know very well. Our firms have researched what they're doing on the industrial side. Yeah. Forever. And let's talk about how a ice transforming those industrial operations in real life and person on the stage Suresh from Honeywell. Great to see you. It's great that we go all the way from you walking off stage and maybe getting some water and a break to be great to see you. And also Sam, great to see you as well. Great to be here. Always great to be here.

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DANIEL NEWMAN: 

Yeah it was great. And it was such an opportune moment for Michael to start to you know I think at the end it was a part that really stuck with me was when him and Jensen basically came to that conclusion that we're really just getting started. Yeah. You know it's been three years. We've been talking and it's like I you know Sam you and I shared a meal at one point. We were talking about how far things have come and I've been two years since that. Yeah. And is

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SAM GROCOTT: 

It has come so much farther. It's laughable. What we were talking about was really cool then. Years ago compared to what we can do now.

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DANIEL NEWMAN: 

It is absolutely wild. So Suresh I want to start out with you. I mean you know you talked a lot about the company's evolution traditional industrial controls company. That's kind of what people know. They all have a thermostat from Honeywell and you guys do so much more than that across automation. What is sort of in the driver of that you know innovation across the company. And how are you guys sort of helping your customers you know deliver and realize operational intelligence across all these different industrial and commercial environments.

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SURESH VENKATARAYALU: 

You know Dan joined Honeywell 31 years ago. And my my major was computer science and neural net. Look, the industry took neural.

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DANIEL NEWMAN: 

Yeah. So you were studying A.I. before. Exactly.

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SURESH VENKATARAYALU: 

31 years for us to really talk about a transformational impact that it's bringing into the industrial world right now. The reason that I joined Honeywell at that point in time it was a control system company by heart and made aerospace commercial building industrial environment. What we have done in the last 140 years is incredible. We actually deliver a controls platform for them to run their operations, either a large commercial building in a data center world or industrial plant at optimal level. Our customers expect, say, 99.6 nights, six sigma performances. Now, if you ask the question, have we leveraged AI all our years? Yes, it was a deterministic model. machine learning systems. We have used it for a very long period in time. What's interesting in the last two to three years is you have this foundational models that have come in which is a probabilistic model idea of incorporating that into a deterministic world to say all right we build systems that can see and act. But can you actually build a system that can see think act and learn. I think that's the pivot point. So the question for us is our customers are happy with what we delivered. But with a combination of thinking and reasoning and learning systems if we can bring it back into the industrial world the value will be incredible. So at this juncture as we work with our customers everyone are looking for a new additional value where they can extend the value of their assets operational side. So our operational intelligence that we had is probably in my opinion is going to X and 3 X than what we have done in the past. So it's an exciting exciting period. That's one of the reason our partnership with Dell and NVIDIA and trying to really build an A.I. stack and helping them up. It's a great beginning. Our customers deserves it and we believe that we can bring that category faster which we call a physical A.I. transformation.

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PATRICK MOORHEAD: 

Yeah. So Sam yeah. Gosh believe it or not we were all talking about the previous AI wave about eight years ago. But Dell is very much ingrained in this OT world. And you know I remember things like you know servers that were applied on the back of a forklift or in an elevator shaft pretty much anywhere that you needed to compute. There was a Dell configuration that was available and here we are now. And I just you know I think the previous generation we just didn't have enough compute to do enough of the A.I. Some of it we did and some of it was really good. But it just seems like we can do so much more now. You have are doing a lot of business in OT. And I'm curious what is it about the Dell AI factory that you've optimized for this. You're obviously doing well. What is really hitting.

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SAM GROCOTT: 

Yes so look we talked about the 5000 customer milestone which we just achieved Honeywell being one of our great new customers that are really seeing the advantages of how do we make it easier for enterprises to deploy this. I would say if you look back to just a few years ago when I really started to come on it was the Wild West. Everybody was getting started. People were doing POC's. We've now kind of hit an inflection point where we're going out of that like early discovery phase. And into scale and I think that's the key word for us is how do we take those early learnings as a partner to our customers and say OK this is how you take those great ideas and scale it across an organization that's when the AI factory comes in because. Organizations are looking for that easier. But I'm not saying easy button because that doesn't exist. It's never going to find it. It's not possible but we can absolutely take the best practices and playbooks that we're building with companies like Honeywell and others to say this is how you scale an organization with a. I think the really interesting dynamic that you're starting to see play out is. The answer was always AI in the cloud. SAS, SAS, SAS cloud. And now you're seeing this shift to more of a hybrid AI movement. It's going much faster than the cloud to hybrid cloud movement we saw over the last decade. Now we're firmly in this spot where organizations are trying to figure out, where do I run the AI? Some of it's going to be best run in the cloud. Some of it's going to be run in a hybrid. Some of it's going to be run in the data center. Some of it's going to be run at the edge, at the device level. So the sophistication that's now required to do A.I. at scale is where I think Dell can really come in and help organizations scale and make it repeatable, secure deliver the performance and give you that governance that you're you're hoping for.

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PATRICK MOORHEAD: 

Just having an operationally aligned regardless of where it sits.

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SAM GROCOTT: Yeah.

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PATRICK MOORHEAD: 

It has a tremendous amount of value. I see for sure.

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DANIEL NEWMAN: 

Yeah it's sort of a it's sort of a metaphoric harness. Yeah. And then it becomes a real harness. So. So Suresh you were mentioning from the stage you know you talked and you talked a little bit about in your last answer about Forge. I remember you know learning about Forge and I think that was one of the big inflections of Honeywell was when you announced this you know kind of this intelligence platform at the edge industrial IOT intelligence. I Share for everybody out there a little bit about what forge is in particular and then sort of how is this being used to deliver real time intelligence operational outcomes you know across customer environments today.

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SURESH VENKATARAYALU: 

Let me frame it up in two ways. I call it as there was a version one of our story a chapter one of forge for the first 10 years. It was yet another IOT stack. We were able to connect back to our customers operations able to pull the operational data. We were able to provide them insights based on connecting to their assets to the process and control system. And so the first generation brought in few things connectivity visibility and then providing a workflow based application for them to solve optimize their operation. But the AI world, the last year or so, obviously things are transforming every single week and every single day. The first generation was generative AI. We brought in generative AI, a foundational model, blended on top of Forge, and we said, look, let's take the last 20 to 30 years of our operational insights and domain knowledge, things like technical publication to the service tickets. We trained the model so that it started guiding and assisting the operators, plant operator or building operator, so that they were making decisions very, very quickly. But then in the last six to eight months, you started realizing the physical AI world has evolved much stronger. We felt Honeywell should be leading in this category because we deal with more than 50 to 60 million assets. Those assets are industrial assets, commercial building assets. If we know our fundamentals are simple, If we can extend the life cycle of an asset and allow it to operate extensively and then if you can manage the processes the control system processes around these operations better. I think the throughput is unlimited in a big way. So physically I was our focus. Then we actually said it requires you to really go back and contextualize your assets and processes and you need to have a technology. That's how we forged a partnership with Dell and NVIDIA and Google. We said we need the of the frontier models. And we need to start to train the model using ontology and knowledge graph. So I think we are moving into this next chapter where we are training AI with the knowledge of an industry and knowledge of a commercial building which is phenomenal in my opinion.

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PATRICK MOORHEAD: 

Yes so Suresh you know on stage today was you you outline your deployment strategy basically you know bringing the A.I. to the data which makes a lot of sense. Michael talked about that in our interview with him previously. But I want to get back to you. You have a lot of options out there. a lot of vendors you can go to. What is why did you partner with Dell for their AI factory. I'm not going to say as opposed to others but how did you make that step from scaling AI in this centralized infrastructure to deploying it out to the edge.

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SURESH VENKATARAYALU: 

I know this morning it was this morning it was quite interesting as you really watched. They actually talked about scale of infrastructure from from a miniaturized compute device for physically I vote which is which is if you really know Jensen launched last year. DGX Park to a high end server category. I think for us what's important is you've got to have a partner who brings this compute know secured and it's scalable across wide range that. And then that provides my customer a continuation and confidence enough to scale their industrial air operation. So that actually made it very very clear. On top of it the partnership between Dell and Nvidia makes it a lot more real because I fact we needed me to really bring in simulation omniverse platform the frontier models ability to really deploy at scale like an agent to get a platform with Nemo claw a combination of a compute. infrastructure. AI frontier model and simulation is so critical in a physical AI world. So it was it was a very natural natural transition for us to starting to work with them. Obviously in the past we kind of left it as an I.T. decisions to deploy your control system to ship it. But now they're going to be part and parcel of renovating our new platforms. That makes sense.

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DANIEL NEWMAN: 

Well Sam we only have a minute or two left but you know you know great to hear from Suresh. You know Dell has been a significant customer zero that goes back to the conversations we've been having. Just kind of love your take for everyone out there about sort of how do you whether it's Suresh's examples your examples. What is it about bringing experimentation to life in and doing this at scale. You know share a few bits of wisdom for everybody out there.

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SAM GROCOTT: 

Yeah yeah. So it's been a fun journey going from zero customers to five thousand. Now we've learned along the way. I think that's a really critical factor that we bring to the table. Those key learnings those blueprints those playbooks that we've been building and we're moving out of that phase of last year was just get started somewhere. We're through the get started phase. We're now and make it real and scale it. And that's requiring a full rewriting of workflows end-to-end across an enterprise. It's no longer a phone a friend or phone an expert when you need some help. No, create the expert. Flat out and create the most excellent capabilities across an organization. Agentify that and then let the humans come in and provide the human touch when required. That's a lot of work. That is a tremendous amount of rewriting. We're partnering with our customers today to really make sure that we provide them the experiences, those playbooks to do that the right way. Think end-to-end. so they can accelerate their journey on AI. So it's been a blast. And like we were saying earlier, it's like, what a fun place to be in right now. Every single week, there's something new. It's just so much fun. And getting to work with Suresh has been great.

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DANIEL NEWMAN: 

Well, Suresh, congrats on all your progress. And we look forward to continuing to track Honeywell. Sam, of course, we'll be with you through this journey. Thanks both for spending some time with us. Thank you. Thank you both. Thank you. And thank you, everybody, for being part of this 6.5. We are on the road here in Las Vegas for Dell Technologies World 2026. Stay with us for more programming.

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