“If you don’t have machine learning and AI helping you sift through all of that, you’re not going to be able to make good decisions in the timeline that we have,” said Bogdan, who previously led the two of the Air Force's most high-profile aircraft acquisition programs, the KC-46 air refueling tanker and the F-35 fighter jet.

He likens the challenge to a car traveling down a highway. Dozens of objects will pass in front of it over a 10-minute period. Which one will it collide with? It is nearly impossible for a person to determine but a computer can make the calculations from a series of inputs — and identify the best way to maneuver out of danger.

But the Pentagon only has very basic capabilities like that when it comes to space, Bogdan says.

“U.S. Space Command and the Air Force are eager to tap into industry and the innovation that industry brings to get those capabilities sooner rather than later,” he said. “All the senior leaders I talk to recognize that in order for us to catch up, this can not take decades.”

Bogdan also spoke about the Pentagon's efforts to work more with smaller, nontraditional contractors to improve its AI capabilities in space and why the military's new focus on space as a warfighting domain is so game-changing.

This transcript has been edited for length and clarity.

Why is artificial intelligence so important in space?

Space now has transformed in the eyes of the Department of Defense and the government [into] a warfighting domain, mostly because adversaries for decades have seen it that way and we just didn’t. Now we’re playing catch up a little bit. … How do we help the Department of Defense … regain space superiority? One of the principle ways we believe we can do that is being able to take data and turn data into information and turn information into action. That’s fundamentally the way warfighting happens.

One of the tools and capabilities we feel will become increasingly important for that is AI and machine learning, partly because there is so much data that has to be sifted through to create actionable decisions but also because of the [short] timelines commanders will be put under to fight in space. If you don’t have machine learning and AI helping you sift through all of that, you’re not going to be able to make good decisions in the timeline that we have.

There are three main areas where we see AI and machine learning being important and applicable to space warfighting. The first is space domain awareness, or trying to understand what’s going on in space. … That means understanding when things are maneuvering, are they maneuvering on purpose? Is it an adversary?

The second area we think AI and machine learning can help is what we call threat characterization and threat assessment. … Let’s say there is an adversary … [who launches] an anti-satellite missile. Today, the ability for the U.S. to detect that missile launch is near perfect. … What we can’t do today — and where machine learning and AI can help us — is understanding what assets are at risk in space because of that launch of that antisat missile. It may take only 10 minutes to get where it needs to go. … Within that 10 minutes, you have to figure out what to do. The first step is figuring out what of your assets is at risk. … That requires lots of computational power [and the] ability to sift through tons of data in a very quick fashion.

The third piece where AI and machine learning can help is figuring out what the best thing to do is. … The timelines [in space] are so incredibly short. We’re talking minutes. … What you want to do is pick the best of that set of options [to respond] to make sure assets are safe and the mission is degraded as little as possible.

How can operators identify a threat in space without AI?

You can see either the anti-satellite missile or the adversary satellite maneuvering towards your asset. But everything in space is constantly moving. … [You have to quickly figure out] what energy does it have so you know what orbit it’s going into, and what are the assets I have in that particular orbit that may or may not be at risk? It’s a very difficult problem. ... When a car is heading towards a tree, the tree isn’t moving. In space, the car is now heading in a direction and in front of it are 20 or 30 things that will pass in front of it over the next five to 10 minutes. You have to figure out which of these is likely to be affected.

With machine learning and AI, as that satellite is maneuvering or the anti-satellite missile is being launched, algorithms and computing power can quickly go through all of the different possibilities and probabilities and provide you [information] in near real time on what things are at risk.

Are Pentagon leaders focusing enough on AI in space?

Many of the space leaders I have talked to in both the Air Force and U.S. Space Command clearly recognize that they need additional tools and capabilities in space domain awareness to help them truly sort out what's going on up there. … That’s why Booz Allen initially is building algorithms and AI and machine learning models to take care of the space domain awareness problem. That’s the first step in fighting combat. You have to know what the environment is like. … Unless we build the capabilities to defend our assets and until we build the command and control to maneuver and do both offensive and defensive operations in space, those algorithms and machine learning techniques have to take a back seat.

The stand up of U.S. Space Command and the stand up of the U.S. Space Force are policy decisions that clearly show that the government understands that space is now a contested and complex warfighting domain. That’s a good thing for this country. That’s the first step.

Is the Pentagon using AI now with any of its space assets?

I’m aware of some fairly simple models being used today on very limited sets of data … to understand portions of space. But the holy grail is understanding what all [space assets are] doing at once. We don’t have that capability yet.

How long until DoD has this capability?

For Booz Allen, within a couple of years we will have some sophisticated AI models and capabilities that we’d like to have DoD using for domain awareness. It’s definitely not decades. It’s probably less than five years. … I know that U.S. Space Command and the Air Force are eager to tap into industry and the innovation that industry brings to get those capabilities sooner rather than later. All the senior leaders I talk to recognize that in order for us to catch up, this can not take decades.

What is the government doing to pursue this capability?

[The Pentagon is] trying very hard to tap into small innovative companies that may not be traditional Department of Defense contractors. One of the things Booz Allen has done is we’ve worked with many different AI leaders and partners ... to bring their AI and machine learning models to a platform that Booz Allen has built called Modzy so the government can have easier access to their AI. It’s a way for Booz Allen to bridge the gap between commercial innovation in AI and machine learning and what we understand about the mission of the Department and Defense and government. … Companies can bring their world class AI models and algorithms to the platform, and the government can access them through the Booz Allen platform.

The government also just stood up a Space Information Sharing and Analysis Center. We have one with the auto industry, the aviation industry, the pharmaceutical industry. … The purpose is to bring together commercial space companies, whether they work with the Department of Defense or not, and share information about threats, cyber threats, and protecting space infrastructure because we all recognize that this is going to be a big team effort. It’s not just DoD contractors, it’s also commercial industry players and civil folks. It’s getting them all together to understand what the threats are. Booz Allen is a founding member of the ISAC. It’s another clear indication that the government and industry are wrapping their arms around this whole thing called space warfighting.

