Mohammad Noshad: How AI Agents Are Making Hospitals Safer | Ep 1264

Summary

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Podcast Summary:
The Digital Executive - Episode 1264
Guest: Mohammad Noshad, CEO & Co-founder of Shield AI
Title: How AI Agents Are Making Hospitals Safer
Date: June 8, 2026
Host: Brian (Coruzant Technologies)

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Overview

In this episode, Brian interviews Mohammad Noshad, a seasoned academic and entrepreneur, co-founder and CEO of Shield AI. The discussion centers on how physical, “active” AI agents are being used in hospitals to not just analyze or advise, but to perform real-world tasks like autonomous disinfection and optimizing operating room workflows—making hospitals safer for patients and staff. The episode also delves into the transition and impact of AI from passive information delivery to operational execution in healthcare environments, aiming for seamless integration and measurable improvements in safety and efficiency.

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Key Discussion Points & Insights

Mohammad Noshad’s Background & Motivation

• Academic to Entrepreneurial Journey (03:00–04:50)
  • Mohammad describes his early fascination with machine learning during his 2013 PhD studies, collaborations at Harvard, and eventual move from academia into entrepreneurship.
  • Two prior companies: First built on Department of Energy SBIR program; second used lasers for satellite connectivity, now core to SpaceX and Amazon Kuiper.
  • The key personal motivator: the loss of a friend to a surgical site infection in 2022, catalyzing a pivot to healthcare AI with his brother Morteza.

“After the exit of the second company, this was 2022, me and Morteza had a friend who passed away because of his surgical site infection. So that was a moment for us to learn about kind of like this problem in health care… there is a great opportunity to build the next company in the healthcare space.”
— Mohammed Noshad [04:35]

Passive vs. Active AI in Healthcare

• The Paradigm Shift (05:00–07:05)
  • Traditional healthcare AI (passive: observes, predicts, recommends) adds data or dashboards for clinicians to interpret.
  • Noshad stresses this approach increases burdens on clinical staff, complicating already complex workflows.
  • Shield AI’s approach: “active AI” — agents that directly act, e.g., autonomous cleaning, flagging missing supplies, or prepping rooms.

“The transition we're seeing... is that moving from an AI that provides just information to an AI that's actually getting the work done. And that was our vision for SHIELD—we wanted to build an AI that is more action-based. It's an active AI that gets the work done within the hospitals.”
— Mohammed Noshad [06:05]

How Shield AI’s System Works

• Real-World Impact & Study Results (07:15–09:10)
  • Shield AI combines proven UV-C disinfection technology with autonomous AI, eliminating the manual limitations of existing UV cleaning methods.
  • A recent Stanford study, published in the American Journal of Infection Control, showed over 93% reduction in contamination in pilot hospital rooms—significantly improving patient safety against healthcare-associated infections (~72,000 US hospital deaths annually).

“So what we showed in that study is that for the first time, we combine it with the AI. And that AI… not only just learns and kind of projects where the contamination is, but actually is taking the action and disinfecting those surfaces autonomously.”
— Mohammed Noshad [08:45]

The Future of Hospital Operations

• Beyond Disinfection: Staff-Agent Collaboration (10:30–13:38)
  • Adoption of autonomous UV disinfection has been rapid due to non-disruptive integration and immediate ROI for hospitals.
  • Shield is expanding toward “active AI” managing broader operational tasks:
    • Pre-case operating room checks (flagging missing supplies, communicating directly with staff via room speakers).
    • Reducing surgical interruptions, errors, and infection risk—yielding measurable time and cost savings.
  • AI devices are likened to the “brain” of the hospital environment, developing deep knowledge of workflows and assets. Future vision includes a “coordination layer” for both human and robotic actors, harmonizing tasks for streamlined, safer, and more pleasant clinical environments.

“These devices, we look at them as the brains of these rooms… now they have become more competent in terms of understanding the environment. They now know all the tools in each case, what is kind of like the workflow… Shield is basically providing that connective tissue and coordination layer.”
— Mohammed Noshad [12:15]

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Notable Quotes & Memorable Moments

• On transitioning from academia:
  “So when I did my PhD… At the time it wasn't called AI, it was mostly machine learning… After a few years [at Harvard] in 2016 I met a program director at [the] Department of Energy… that's how I left academia and decided to start [my] first company…”
  — Mohammed Noshad [03:10]

• On the distinct value of active AI:
  “You're just making it more difficult for them [clinicians] to adopt those technologies… how we can make this adoption seamless by getting the work done, not just providing another piece of information or a dashboard data…”
  — Mohammed Noshad [06:35]

• On the future of autonomous agents in healthcare:
  “That's just one example. And when we look at a broader view, one of my personal exciting kind of aspect of this is… bring more muscles into the OR. And that could be robotics. From humanoids to other form of robotics.”
  — Mohammed Noshad [11:30]

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Timeline & Important Timestamps

• [02:54] — Mohammad’s background, motivation, and shift from academia to entrepreneurship
• [05:53] — Defining passive vs. active AI in healthcare and its importance
• [08:21] — How Shield AI’s autonomous UV system operates and key study results
• [10:33] — Expanding active AI’s role into operating room prep, asset tracking, and the future of clinical-agent collaboration
• [12:15] — The concept of AI as the “brain” of the hospital environment and vision for robotics integration

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Tone & Style

• The conversation is warm, inspirational, and grounded in practical healthcare impacts.
• Mohammad remains technically insightful but focuses on tangible real-world benefits and user-centric adoption.
• The host, Brian, is appreciative and adds personal perspective from his own healthcare technology background.

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For listeners seeking actionable knowledge or context on how AI is actively transforming healthcare environments, this episode offers groundbreaking, real-world examples of AI augmenting—not replacing—human clinical staff, with measurable improvements in safety, efficiency, and workflow.

Transcript

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[Brian (Host)]

Welcome to Coruscant Technologies, home of the Digital Executive Podcast. Do you work in emerging tech? Working on something innovative? Maybe an entrepreneur? Apply to be a guest at www.corazon.com brand welcome to the Digital Executive. Today's guest is Mohammed Nushad. Mohammad Nushad is the CEO and co founder of Shield AI where he is pioneering the use of physical AI agents to bring real time operational intelligence and automation into hospital environments. He also serves as a Strategic advisor at Field AI. With a background in electrical engineering and a PhD in AI, he led cutting edge research at Harvard University in AI and machine learning. His work has been cited over 2400 times and has received several best paper awards. His experience spans robotics and space connectivity and he is now focused on building technology that helps save lives globally. Well, good afternoon Mo. Welcome to the show.

[Mohammed Nushad (Guest)]

Awesome. Thank you Brian.

[Brian (Host)]

Absolutely my friend. I appreciate it. Really do. I know you're in the San Francisco Bay area. I'm in Kansas City. Just a couple hours apart as far as time zones, but I know it's challenging to work through calendars. So I just appreciate you being here and I'm totally excited to jump right in. So Mo, your path here is fascinating. Electrical engineering, a PhD in AI, leading cutting edge research at Harvard. We're expanding robotics and space connectivity and now co founding SHIELD AI with your with your brother Morteza. Take us back to the beginning. What drew you to this AI and machine learning in the first place? And what were the inflection points that took you from academic research with over 2,400 citations to building A company focused on saving lives in hospitals.

[Mohammed Nushad (Guest)]

Yeah, thanks Brian. Thanks for having me. So when I did my PhD, this was back in 2013. At the time it wasn't called AI, it was mostly machine learning people were referring to. And it was one of the fascinating areas for me personally, looking at how these systems can basically predict different outcomes and work to learn different behaviors of these systems. So that was motivation for me and my co founder and brother Morteza, when he basically did his PhD at University of Michigan, Ann Arbor. And after my PhD, I moved to Harvard. I was working on a lot of exciting projects over there with an amazing team. And after a few years there in 2016 I met a program director at Department of Energy and they had a program called sbir. And you know, I thought it would be interesting to build a system based on that. So that was the story of kind of like my first company. That's how I left academia and decided to start first company which was interesting, kind of like technology we were building. And after that it was second company which was even more exciting. Using lasers in space to connect satellites in LEO orbit, which basically same technology that's being used with SpaceX, Amazon, Kuiper to establish the backbone of connectivity across all of those satellites in space. And then after the exit of the second company, this was 2022, me and Morteza had a friend who passed away because of his surgical side infection. So that was a moment for us to learn about kind of like this problem in health care. And we thought with our training in AI, there is a great opportunity to build the next company in the healthcare space.

[Brian (Host)]

Thank you. Appreciate the backstory and story starts out great, did some awesome things in academia, higher education, and then you jumped into entrepreneurship and founded a couple companies. But the touching part of the story is obviously you lost a friend, you and your brother from a basically side effect of a surgery. And it was certainly made you think about how do we take healthcare more seriously. And I love this part. I worked in healthcare most of my life on the technology side, so I can totally appreciate that. But I appreciate you sharing the story and jumping in to try to solve a big problem in the healthcare space. And Mo, you've drawn a sharp distinction between passive AI and active AI. Most healthcare AI today observes, summarizes or predicts, shields agents and actually execute disinfecting rooms, tracking or turnover flagging missing supplies. What, why is that distinction so important? And what changes for a hospital when AI moves from advisor to operator?

[Mohammed Nushad (Guest)]

Right. So in health care, I would say health care has probably one of the most complex workflows. And you know, when you provide just information or data for the health care workers and you ask to them to change behavior or change the workflow, you're just making it more difficult for them to adopt those technologies. So the transition we're seeing not just in healthcare but overall with agentic AI is that moving from an AI that provide just information to an AI that's actually getting a work done. And that was our vision for SHIELD we wanted to build an AI that is more action based. It's an active AI that gets the work done within the hospitals. And we basically every piece of the technology we built at SHIELD AI was with that kind of like philosophy in mind on how we can make this adoption seamless by getting the work done, not just providing another piece of information or a dashboard data and asking the health care professionals which have, you know, they have tons of things on their plate already, but how we can get a few of those items off their shoulders and let them focus on more important items and stuff.

[Brian (Host)]

Thank you. And I appreciate that obviously you, in your mind you wanted to set out and make the technology easier to adopt. Yet taking off some of that workflow you or workload, you did talk about the healthcare and I truly know this, they have one of the most complex workflows of course. And so changing a workflow just because or to add a piece of technology in that process can really frustrate the clinicians or make it more inconvenient and potentially more unsafe. So I really appreciate you highlighting that and taking the extra effort to make sure that you can integrate something that would actually help the clinician in the process. So thank you, Mo. The Stanford study published in the American Journal of Infection Control showed your autonomous UV C system reduced contamination by more than 93% against a backdrop of roughly 72,000 US hospital deaths annually tied to healthcare associated infections. Walk us through how the system works, the sensors, the AI decisions, what's happening in a hospital room that a human cleaner can't match.

[Mohammed Nushad (Guest)]

Right. So I would say infection control and automating disinfection is one of the important aspects of our AI and how combining it with a well established technology, which is UV can make it an order of magnitude more effective. So UV is, is a proven technology. It's being used in hospitals, but in today's workflow it's, it's manual and when it's manual there's limitations in terms of the frequency and usability of that. So what we showed in that study is that for the first time we combine it with the AI. And that AI, again, not only just learns and kind of projects where the contamination is, but actually is taking the action and disinfecting those surfaces autonomously. And that study showed that we're able to get over 93% reduction in contamination in those environments, which can translate to a significantly safer environment for the patients. And ideally the outcome will be lower number of infectious, procedural and surgical environments.

[Brian (Host)]

That's amazing. Really appreciate here's honestly how the true power of AI, right, Autonomous disinfectant basically, or disinfector, but infection control and automating disinfection, I think really goes hand in hand here. We do know that a lot of UV is great. Problem is it's done manually today, but with your platform, you're able to again combine those two and reduce those infections and diseases, germs, et cetera, in those rooms. So I appreciate that. MO looking four, maybe six years out as physical AI agents move from disinfection or and I guess operating room optimization into broader hospital operations, as an active AI becomes standard across critical environments, how do you see the relationship between clinician staff and autonomous agents evolving? And what role does shield play in shaping a future where hospitals are not just smarter, but measurably safer for every patient who walks through that door?

[Mohammed Nushad (Guest)]

Right. So we started with UV disinfection and we're already seeing a great speed of adoption within hospitals because now they don't need to change anything, they don't need to change behavior. And our sales cycle is significantly fast. It's weeks. We're able to get these devices in and it's working in the background. It's not interrupting or changing any workflow. But now with that, we are expanding to even broader areas on where we can use that active AI to take a role. And whether it's an operating room. Identifying what is missing in an. In a basically an operating room before the case start, before the surgery starts. And we have these devices that basically have speakers and they can communicate to the staff right in the room so that we notify them if there is, let's say, five missing items, supplies, tools, we prevent basically interruptions during the surgery. Now that can significantly save time, reduce basically unintended delays for that case. But at the same time, it provides a safer procedure for the patients because each of those interruptions potentially can increase complication and infection risk. That's just one example. And when we look at a broader view, one of my personal exciting kind of aspect of this is These devices, we look at them as the brains of these rooms, whether it's an operating room or now we're expanding to ICUs Med surge emergency rooms. And how we can leverage basically this brain. Because now they have been learning, right? So we're passing that kind of like early stages where we put these devices in. They have seen enough cases, enough procedures, and now they have become more competent in terms of understanding the environment. They now know all the tools in each case, what is kind of like the workflow, like, right? So learning the work flow, learning different items that are being used. And then so this is the brain, how we can bring more muscles into the or. And that could be robotics. From humanoids to other form of robotics. Shield is basically providing that connective tissue and coordination layer, right? But now because of the knowledge we have, we know at each time what's needed in each room or what the room setup should look like and how we can leverage that, let's say human and robot to move from an area and bring an item into the room or help with that room set up before kind of like the first case during the day. So that's a feature I personally very excited about and how this can transition health care into a much more effective and efficient environment. Reducing the cost, reduce, reducing the waste and providing a much safer environment for the patients and something an environment that's pleasant and more convenient for the staff to work within.

[Brian (Host)]

That's awesome. Really is. And I know that you started out with UV disinfection, but then you kind of moved into that really accurate, the inventory and asset management piece of it, which I thought was interesting because things happen, especially with humans, we forget to put something in a room for a procedure or a case and interruptions are just the worst. That obviously, as you said, brings potential room for error or introduce additional infections into that environment. But at the end of the day, you're reducing overall that cost and that waste and making things way more efficient. So I really appreciate it. As you know, I just love healthcare. That's been really where I spent most of my career. So I'm very, very hopeful and I want to hear more about it in the future. And Mo, it was such a pleasure having you on today and I look forward to speaking with you real soon.

[Mohammed Nushad (Guest)]

Awesome. Thank you for the opportunity, Brian. It was great speaking with you.

[Brian (Host)]

Bye for now.