Artificial intelligence (AI) and quantum computing have already collided in the security landscape and changed how governments, industry, and critical infrastructure operate. At the GBEF EDGE Security Summit, a panel of senior leaders from government, industry, and Congress described this collision as a “seismic convergence.” When combined with powerful sensors and networks, this tech holds tremendous promise and peril in terms of missions and vulnerabilities. It also raises some hard choices about how fast to move.
New Tech But Not Really New
Two generational technologies, AI and quantum, have arrived at scale at the same time and have already intertwined. AI has moved from algorithmic research into chat assistants, copilots and operational tools that people use every day. Quantum, while less visible, has arrived in devices, sensing, and specialized systems that most users do not recognize as quantum at all.
Dr. William “Bill” Streilein, Chief Technology Officer at Noblis, reminded us that AI is not new. “We know AI is here. We use it every day. The algorithms we’re using have been around for 30 years,” he said, “Basically what’s changed is the scale.” That scale drives capabilities such as multimodal models, real time analytics, and mission support tools that can monitor complex environments far beyond human bandwidth.
Quantum’s principles were discovered a century ago. Yet it is only now emerging in practical systems that matter for security, logistics and sensing. “It’s actually already in your phone,” Streilein noted, pointing to quantum based sensing used for measuring acceleration and improving location accuracy. The technology is present, but it has not yet delivered the “almost sci-fi capabilities that are promised,” like ultimate encryption or being in two places at once.
That gap between perception and reality is one of the reasons public debate lags the technology. Most people associate quantum with mysterious lab hardware and futuristic science fiction. But quantum capabilities today are concentrated in three core areas: computation, sensing and communication. While they are not yet widespread for everyday tasks, they are already being used experimentally and operationally where classical systems struggle, especially in complex sensing and optimization problems.
Quantum Is Different From AI
The two technologies are not the same. Katie Arrington, Chief Information Officer, IonQ, stressed that the industry often blurs AI and quantum into a single buzzword, which obscures how different they are. “Most people think AI is cool and awesome. No. Quantum is so much different than AI. But they’re great collaborators. They can do amazing things.”
AI can monitor noisy quantum systems and make real time corrections, while quantum computers can accelerate the heavy computational workloads that AI needs to train and operate at scale. “Quantum can actually now take on the computation that AI needs in record time to enable models to train faster and also come to conclusions much faster,” Streilein explained in describing his “number one convergence” use case.
In short, AI and quantum are complementary, not interchangeable. AI will increasingly orchestrate and interpret quantum outputs, while quantum boosts the depth and speed of AI powered insights.
Use Cases That Could Change Daily Life
Arrington offered an example that translated the convergence of AI and quantum into everyday impact. She said imagine a quantum computer that could ingest traffic light data from every municipality in the country, “down to that hometown that has two people in it,” and in a millisecond compute how to retime traffic signals so nobody sits at a light for more than thirty seconds.
“That saves on fuel, that saves on energy, it saves on manpower. That’s what quantum computing is supposed to be doing. Big life changing things,” she said. The same approach applies to air traffic control, congested logistics,and border operations where every delay carries cost and risk.
Quantum driven optimization could also help look at “every car, every plane, every person coming into our country and figuring out which ones are bad or good,” Arrington noted. Those same capabilities can extend to unmanned traffic management, maritime autonomy, and critical infrastructure protection, where AI and quantum together can triage massive sensor streams and focus human attention on genuine anomalies.
That’s exactly what US Customs and Border Protection has decided to do at the convergence of AI, quantum, and networking, which is already operational.
CBP’s 3-Legged Stool Of Convergence
Sunil Madhugiri, CBP’s Chief Technology Officer, described the agency’s framework as a three legged stool: AI, quantum computing, and networking, all resting on a seat held together by cyber and data.
“Ever since 9/11 happened, the predictive analysis component, we’ve been doing this for a long time,” Madhugiri said. CBP has been building analytic capabilities since the mid 2000s and has now integrated generative AI into how the agency does business. The convergence comes when AI, quantum, and network infrastructure operate together, with cyber security and data management cutting across everything.
The stakes for CBP are high because the tolerance for error is effectively zero. “We cannot get things even one wrong. Because if you think about one bad decision or if something happens, like you let somebody in, or let a bad car come in, there are massive implications for that.” One misclassified object, one missed anomaly and the consequences can cascade.
To make convergence real, CBP started with one of the most urgent problems: post quantum cryptography (PQC). “Believe it or not, CBP wrote a paper three years ago on PQC,” Madhugiri said. His team took a live application, mapped its classical cryptography and then pulled it apart to evaluate post quantum encryption schemes in practice.
They did not stop there. Working with a major quantum vendor, CBP has now created the first quantum circuit for anomaly detection. The team took a Python based workload, translated it into a real quantum circuit and used it for anomaly detection on network traffic. “We found things which we have not seen before,” Madhugiri explained, emphasizing that quantum does not simply do things faster, it enables entirely new ways of seeing patterns that classical systems miss.
That distinction matters. AI and classical computing excel at scale, but remain bounded by binary architectures. Quantum introduces multi dimensional representations through qubits that can be active in superposition. It enables richer pattern discovery in areas like traffic flows, logistics and border security.
Healthcare, Tunnels And Quantum Sensing
Beyond computation, the panel repeatedly returned to quantum sensing and networking as the most surprising and powerful convergence frontier. CBP is exploring quantum sensing for non intrusive inspections and hazardous materials detection, drawing on quantum’s ability to detect chemical signatures more precisely than classical systems.
These sensing capabilities have obvious parallels in healthcare. Arrington highlighted work in “figuring out new ways to do compounds by finding outlets,” and spoke about quantum helping identify patterns in medical data that point to diseases like Ebola, measles, or cancer in ways the human brain cannot. Quantum enabled anomaly detection, combined with AI, can surface subtle correlations, early warning signs, and pathways to new treatments.
The same physics applies underground. The potential for quantum sensing to detect subterranean tunnels has enormous implications for border security. Whether scanning ports, tunnels, or critical facilities, quantum sensing promises a level of visibility that has both transformational security value and serious geopolitical consequences.
No Second Place In Quantum
Given the implications of quantum, a geopolitical race has begun around it. “There’s no second place in quantum. You either are the winner or you’re not,” Arrington said. She warned that adversaries are already developing quantum sensing strategies and will not use these capabilities for benign purposes. “They’re not going to use it to figure out how to get ahead of cancer. That’s the fear factor,” she cautioned. Quantum could be used to tweak pharmaceutical compounds at scale, exploit vulnerabilities in global supply chains, or weaponize biological agents.
Arrington’s hope, however, is that “quantum will be used to help fortify peace and solve big, big problems that the human brain just doesn’t have the capability to see.” She imagines using quantum sensing and networking to show the world the full impact of war in real time, making it impossible to deny the human cost.
The PQC Clock Is Ticking
On the flipside, post quantum cryptography presents an urgent tech downside. “We are in a very dangerous place and a very amazing place at the same time,” Arrington said. Both she and Madhugiri stressed that data is already being harvested by adversaries who may not be able to decrypt it today, but will once practical quantum decryption arrives.
“At once everything is going to go boom,” Arrington warned, if organizations wait too long to shift to post quantum encryption. Madhugiri echoed the urgency. He argued that short term PQC implementation is “extremely critical” and that the threat is not decades away, but more like three years away. He urged industry to start working on this now.
The risk is not just that encrypted data will become readable. Streilein pointed out that once your data is compromised, adversaries can impersonate you, drain accounts, and manipulate systems in ways that extend far beyond privacy loss.
The panel also looked ahead to the people who will have to live and work in this converged environment. Streilein noted, “Quantum will be here. And so if you imagine 10, 15 years from now, we will all be using Quantum and we need to build the workforce so that people can do this.” He even floated the idea of “quantum live coding” as a future skill, a nod to how completely these tools may embed into everyday development workflows.
Doing All The Things At Once…Now
Asked what we should be doing first, Streilein answered with both realism and optimism. “We should be doing all the things all at once. Quantum lets you do that actually,” he said. His core message was that quantum gives us a capability to look at many possible solutions simultaneously and find optimal paths rather than choosing one option at a time.
Yet the panel did converge on post quantum cryptography as the near term priority. PQC is the starting point because it protects data that is already being harvested, stabilizes trust in financial and mission systems, and buys time for more ambitious quantum and AI convergence projects. They also emphasized that PQC is only one piece of a larger roadmap that includes AI cataloging of data, quantum sensing pilots, workforce training, and multi domain collaboration among government, industry and allied nations. The question is not whether AI, quantum, and emerging tech will reshape security. It is whether we move fast enough, and thoughtfully enough, to guide that convergence toward resilience, prosperity, and peace.
For autonomy and unmanned systems leaders, this presents an operational design constraint. AI, quantum, and advanced networking will shape how drones are tasked, how resilient command and control links become, and how quickly we can detect and respond to emerging threats across air, land, sea, and space. The organizations that start now on post quantum cryptography, quantum ready data architectures, and workforce development will be the ones that define the next decade of secure autonomy rather than reacting to it.