Episode Transcript
[00:00:00] Speaker A: Foreign.
[00:00:08] Speaker B: Hello everyone and welcome to our podcast on AI driven performance Improvement. I'm Anil Kumar, your host.
I lead the private equity AI practice at Alvarez Marcel and oversee A and M assist our AI driven performance improvement platform.
I'm very excited today to talk about AI and its impact on critical industries.
Today we are focusing on aerospace, defense and space sectors that are on one hand leading a lot of the innovation, but also on the other hand facing unique challenges.
AI is really transforming and disrupting the industry in many different ways.
Joining me today is Lou Paluso, our leading expert on aerospace and defense and my fellow MD at A&M's Private Equity Performance improvement practice. Lou, welcome to the podcast.
[00:01:01] Speaker A: Pleasure to be here. Anil. Thank you for the invitation to participate in the series.
[00:01:06] Speaker B: It's very clear, right, that AI is still developing. We are in the early stages, so our aim is to generally gain insights and perspective because there's no really definitive answers. A lot of it is we have companies, industries, executives figuring where they need to be and everyone is on their journey. So it would be great to, you know, start with understanding the current landscape.
And Luke, from your perspective then, what are the most significant operational and cost related challenges facing the aerospace, defense and space industries today?
[00:01:42] Speaker A: So we've got a couple of forces that are converging across our vertical industry segment and sub segments.
There is the challenge of trying to improve the operational performance and efficiency of aircraft, weapon systems, space systems that are so critical to our economy, whether it's straight transportation, national defense, sovereignty, communications, all sorts of fundamental issues.
But inevitably there's always this balance between trying to optimize the performance and mission objectives of these systems while managing cost and doing that within the context of the changing environment around customer requirements and demand creates enormous challenges as well as opportunities specifically.
Look at it from an analytical standpoint. 80% of the cost of these systems is determined in design.
So anything that can be done on the front end of product development, engineering and innovation to leverage technology can have a dramatic effect not only on the performance of the system, but on its life cycle, costs and economics.
[00:02:59] Speaker B: That makes a lot of sense. And can you talk about some of the challenges?
Because what I hear and when they talk to executives in this industry, it seems like the industry is going through a really big disruption and transformation and a lot of challenges. And how do these challenges manifest themselves in terms of inefficiencies or bottlenecks?
[00:03:19] Speaker A: So there's always this push if I look at the aviation specifically to try to reduce the cost and the weight of aircraft through the advancement of new materials and new designs. There's always a push to try to make aircraft more efficient and more capable and obviously to continue to improve and drive SAFET improvements over time.
And then the last piece is now, with the rise in environmental consciousness, there's a move to try to get off of conventional carbon based fuels into alternate power platforms that are better for the environment from a sustainability standpoint. So these all represent tremendous challenges to the people that are trying to design and build aircraft, whether they're for commercial or military use.
And then of course, with the advent of technology, we're blessed with more and more information available and at the industry's disposal if we can leverage all the learning, both historically, but also how to adapt and incorporate new learnings as the industry continues to evolve and develop and mature.
[00:04:31] Speaker B: And what about the space industry? Space is one of the areas where we. It's, it's a lot in the news and from both innovation perspective, but also challenge perspective, it's not easy for everyone to compete and deploy the investments required in this industry. What are the challenges that this industry is facing?
[00:04:50] Speaker A: So it's, you know, probably, I would argue, one of the most exciting periods in space ever. If you look at the number of launches, the number of new entrants, coupled with legacy providers of space assets and infrastructure, changes in communication, changes in the way people are consuming media, I mean it's, it's tremendous, right? The proliferation of the cell phone and the prospect of doing more direct to device kind of communication with people and enablement of entertainment and other data consumption and management.
It's very, very exciting. And as a result of that, it's attracting a tremendous amount of capital into that segment. And the source of a lot of innovation both in product design and manufacturing, through the use of things like additive manufacturing versus more conventional manufacturing method, advanced use of materials, and the ability to process phenomenal amounts of data for very different use cases and missions, depending on who the customer, either the data or some of these assets are. I'll give you an example. We're seeing more and more of a need for higher levels of autonomy, whether that's edge computing or the ability to operate maneuver spacecraft specifically once they're on orbit. You know, it's getting a little congested up there between the number of assets that are now on orbit from various countries that are putting more and more assets in space.
And unfortunately we also have challenges, debris and other objects in space which can represent an existential threat to any spacecraft that's operating in the various orbital planes and Domains.
So having the ability to do remote processing, collision avoidance and deal with the realities of the operating environment in space are really fundamentally important. And areas where advanced technologies, including AI will help drive levels of autonomy, levels of intelligence, levels of safety and performance that just haven't existed in the history of putting objects in space.
[00:07:01] Speaker B: I know AI is still early days, but massive potential. But even before we get to the AI, I think the technologies beyond throwing massive resources at these problems, there's already a lot of leaps in technology in these industries, Right? Think about simulations, investments in material size. Is there a framework when they think about how should these companies prioritize investments, how should executive thinks about where to invest and when we're not really to invest in. Is there a framework that recommend executives in these industries to look at?
[00:07:35] Speaker A: Yeah, there's a couple of ways of looking at it. One is to really try to figure out how to adapt these existing and emerging technologies to really fundamentally have a disruption in the cost structure or the production effectiveness of the business.
And there's tremendous opportunities there, whether it's automation, to use of advanced materials, to driving innovation really across the whole of the operating model of these businesses and companies that just didn't exist before.
Second is that it's an industry that's collected data from sensors and performance for a long, long time, decades in fact.
And so there's a great opportunity to better mine all of the history and learnings from prior generations of classes of equipment that have been produced and learnings in sustainment and managing maintenance protocols on a global basis that still are assets that I think are under leveraged and untapped, that can improve the performance of existing equipment and assets that are operating, but also raise the prospect of incorporating those learnings in the next generation of design to have pretty profound impact either in terms of the breadth of capability, the operating safety, or the economics of these systems.
[00:09:00] Speaker B: Exactly. That makes a lot of sense. Let's move to the more exciting part, which is AI. When you think about AI, we think about how AI can accelerate a lot of these processes, how it can analyze a lot more data than it used to, and how things a lot more innovation compared to the conventional methods. When you think about AI and the way we are looking at other industries, and a lot of this probably applies to aerospace, defense in space as well. AI is enabling us as humans to spend more time on innovation, creativity, complex deep dives and complex analysis by taking away a lot of the data gathering, problem sniffing, looking at issues where it used to take a lot of time. How do you think we are still in early stages, but what are the potential exciting applications emerging from use of AI these days?
[00:09:55] Speaker A: Sure. So the good news is we've got more data and more information and more access to that information than we ever had.
The bad news is, how do you deal with all the information that we have and make some utility of it? So there are a couple of emerging applications that I think are easy for people to potentially get their heads around. If you think about air traffic management as an example in civil aviation, well, right. The ability to safely increase the utilization of airports, to improve the safety margins in the air flight scenarios, you know, are all huge. But there's a limit to how much information a human air traffic controller can process and how much information a pilot can process. And there's a lot coming at them in terms of workload.
So to the degree AI can be leveraged to improve the performance and safety of things like air traffic control has a huge impact on really all of our lives in terms of both safety and operations of civil aviation. You take that and you multiply it probably by an exponential factor in the military environment where either manned or unmanned aircraft operating on its own or in a network with other assets, the ability to manage data and information you need and the time that make very, very important decisions is getting shorter and shorter and shorter. And so really, the effectivity of those systems will be fundamentally determined by the success of using AI to help process, manage and respond to inputs and data as it becomes available to make really very, very critical, very, very critical decisions. And then mentioned in the space domain, there's this opportunity to improve performance of collision avoidance, safety of operations, network optimization in terms of the collection and transmission of data of all forms on a global basis. And these are problems that really can only be scaled and solved through the use of AI.
[00:12:09] Speaker B: Where do you think companies are in general? Obviously, the answer is it depends. Different companies are in different stages of evaluating, implementing, driving these changes. But in general, where do you think the industry is right now in terms of adopting AI?
[00:12:25] Speaker A: I would say it's still very much in the experimentation phase where there's a lot of companies doing a lot of small scale pilots and exploring applications.
I think going forward, I would recommend much higher level of investment and commitment to solve major either efficiency issues, design issues, product development, or addressing sort of structural costs that probably require much more intense levels of management guidance and leadership and capital investment in order to fully take advantage of the opportunities that are presenting themselves today.
Right.
[00:13:07] Speaker B: One of the things you and I have spoken many Times about disruption, but how new entrants to this industry are carry because they don't have to the baggage that many of the incumbents may have of unlearning. A lot of the new entrants are coming up with very innovative way and have the potential to really disrupt parts of this industry.
And then you have the incumbents who have small pockets of innovation going on, but driving it at a large scale is difficult. How do you think about disruption and how do you think about larger big companies incumbents being able to manage that disruption?
[00:13:47] Speaker A: I think this is a challenge that's very true in our industry and it runs very similar to what other industries have learned in that oftentimes the disruptors in any industry are people that are coming in that are not the incumbents and legacy players.
Most of the traditional defense contractors have a certain level of technical capability, but they also have tremendous culture and mass which makes it very difficult for them to be agile and move very quickly.
There's a new generation of entrants in almost every area of the aerospace and defense sector which are coming in sort of with a digital native culture. Much more agile, you could argue, much less short term financial incentive to try to build and test and innovate and frankly take more risks and are creating a lot of disruption and potentially existential threats going forward as the either military customer, government customer or commercial customer continues to raise the expectation and demands of capabilities that they want in systems that they're buying that really represent the most contemporary use of technologies for lower cost and improved performance.
[00:15:22] Speaker B: So looking ahead, what would be your advice to companies in aerospace, defense and space sectors who want to prepare and capitalize on the impact of AI? What should they be doing today? Now to instead I would say invest.
[00:15:39] Speaker A: Heavily in the people that understand these technologies.
Invest significantly in the technological platforms that will enable the use and leverage of AI and other advanced technologies, but do it thoughtfully in a way that's going to actually make a difference in the business, whether it's in the productivity and efficiency of core systems or in the products themselves.
Because the pace of change is getting ever faster and you're going to be able to need to respond from people that are facile in the use of these systems and technologies.
And oftentimes it's very difficult to change the sort of critical mass that's been so connected to legacy ways of operating legacy systems, legacy cultures.
[00:16:35] Speaker B: That's a very powerful message. It's really being about to your point, being agile, looking outside, for outside the traditional competitive landscape and embracing disruption. Any final thoughts for our listeners as they consider this AI evolution?
[00:16:51] Speaker A: I would say unlike prior generations of technology where people could take more of a wait and see attitude and invest moderately and change slowly over time, we're in a fundamentally different pace of change, a fundamentally different pace of adoption.
And to be honest with you, I think the risks are much higher because traditional customers are becoming much more open to alternate sources of supply. Whether that's in the space launch arena where SpaceX has become the dominant provider to the anderals and palantirs of the world that are entering the military in this defense market, and a change in the attitude of the government willing to buy from these previously unheard of providers and demonstrating that it can be very successful.
[00:17:46] Speaker B: Lou, this has been incredibly insightful. Thank you so much for sharing your expertise with us today.
For our listeners, we've been speaking with Luke Peluso about AI driven performance improvement opportunities in aerospace, defense and space. We've explored the pain points, potential of AI and some key advice for companies.
Join us next time as we continue to explore the cutting edge of AI technology and its impact on other industries. Thank you for listening.
