America Wants To Build Again. Can AI Help Engineers Keep Up?

AI and simulation tools can help engineers turn America’s manufacturing ambitions into reality.

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In April 2019, the DSV Limiting Factor, made by Triton Submarines, plunged to the greatest depth humans have ever gone: roughly 35,800 feet. It reached the seabed at Challenger Deep, the furthest known part of the ocean. Nearly seven miles down, deeper than Mount Everest is tall, that’s an impressive feat. Until you realize that more than 70% of the ocean floor still awaits high-resolution mapping, according to NOAA’s April 2026 figures.

Easier said than done. Engineers must first be able to design future vehicles capable of withstanding immense pressure that, at the deepest points, exceeds a thousand times the atmospheric pressure at sea level.

The ocean is just one frontier humanity longs to conquer. Space is another. To achieve either goal, we first require physical systems capable of withstanding extreme conditions. Engineers increasingly use simulation and digital twins to understand how systems may behave in dangerous or extreme physical environments before risking humans, vessels or machinery. “A digital twin is a digital replica of a physical object, person, system, or process, contextualized in a digital version of its environment,” explains McKinsey.com. “Digital twins can help many kinds of organizations simulate real situations and their outcomes, ultimately allowing them to make better decisions.”

In other words, developing simulations and digital twins can help us boldly go where humanity has never gone before. But what if simulation tools could also enable America to build again, as we did in the twentieth century, with a renewed focus on making advanced products here at home?

This is the promise that Masha Petrova described to me. “Simulation is sort of the hidden area, but it’s critical in order for us to manufacture again. Without that work, nothing happens, or we keep manufacturing things that are outdated, and innovation doesn’t occur.” Petrova is CEO of Nullspace, a deep tech company developing next-generation electromagnetic simulation software for mission-critical radio-frequency (RF) and quantum computing applications.

Returning to America’s building aspirations, a real problem lurks, one that could hold our national ambitions back: a dearth of human talent. “Every year, the US will need about 400,000 new engineers,” explained Boston Consulting Group in a 2023 analysis with SAE International. “Yet the next-generation skill sets that those engineers will require are sorely lacking, presenting the alarming possibility that nearly one in three engineering roles will remain unfilled each year through at least 2030.”

Even as firms struggle to find people with the right skills, the systems those engineers must design and manufacture are growing ever more complex. To appreciate how, consider antennas. Most people, when they think about these items at all, imagine rabbit ears on old television sets. Increasingly, however, antennas live inside our phones, cars, laptops, thermostats and security systems. “Now that we have satellites in space and drones in the theater of war, and advanced communications, design challenges increase,” says Petrova. “Creating systems that run on all these antennase requires specialized engineering knowledge developed over many years. It’s not possible to turn new graduates into experts overnight but we can design better engineering tools to empower leaner teams.”

Petrova describes an R&D process that includes simulating before building any physical prototypes. A familiar analogy can be found in a restaurant chain. Rather than commit to selling its new barbecue chicken sandwich at all 2,000 of its locations before knowing if patrons will order it, management might opt for a more conservative approach. They might roll it out at five places around the country to determine its appeal. By limiting their exposure to this test, they will not be out so much money and time if the offering flops.

When it comes to Nullspace’s own digital simulation software, it enables engineers to predict how an antenna and radar systems will work and interact with the surrounding environment before building and testing the physical product. Case in point: Petrova explained the company works with a major Japanese manufacturer. Previously, this client used another simulation tool that took six hours to model how a satellite antenna would perform. With Nullspace, the client cut that simulation down to just two minutes without losing accuracy of the results.

AI can further accelerate simulation workflows, helping engineers tackle increasingly complex designs without necessarily expanding their teams. “AI can make workflows much faster,” Petrova told me. “For example, an AI agent can help set up a simulation, change design parameters, perform variations and organize results for an engineer to review. While the simulation software handles physics calculations, the human engineer remains responsible for deciding whether the answers actually make sense.”

Making scarce talent go further in the AI Age is a subject I recently covered for Forbes in an article about agentic AI supporting teams short on personnel. Another company, Beehive Industries, which manufactures jet engines for drones and defense systems, is intent on rethinking the engineering team itself. Rather than relying on an antiquated ecosystem of disparate parts, factories, suppliers, and years of development, it is leaning into working smarter, not harder, starting with how it manufactures. Beehive says more than 90% of the components in every engine it sells are made using 3D printing, with design, machining, assembly and testing handled in-house. “More importantly, [3D printing] would reduce the time required to design, test, and deploy an engine, as well as minimize its production cost—an issue that the U.S. military is contending with, especially as it sometimes uses expensive missiles to take down cheap drones,” explains Tom’s Hardware.

The approach is paying off. “The Air Force has awarded a $29.7 million contract to engine startup Beehive Industries to complete work on a new disposable jet engine meant to power drones and munitions,” according to Air & Space Forces Magazine’s reporting in April 2026. Responding to the development, CEO Mohammad Ehteshami told me, “We need more engineers, but we also need to stop wasting the expertise we already have. An experienced engineer should be solving design problems, not spending their day working around outdated processes.”

Reflecting on both Petrova’s approach of simulating before building and Ehteshami’s push for better results from more streamlined processes, we can see how America can recapture its engineering prowess. Whether it’s developing next-generation vessels to map the floors of silent seas, ships to circle the cosmos, or just more jets to secure our nation, the solution is to combine human ingenuity with better tools. By giving teams a faster path from design to testing, supported by smarter supply chains, we can expand what people can accomplish. That’s how we turn today’s American engineering potential into tomorrow’s winning reality.