On September 27, US transportation secretary Sean Duffy posted a video on X calling the new air traffic management tool “GAME CHANGER.” He claimed it would save time, cut delays, and improve the flying experience. The system, named SMART, was designed to use artificial intelligence. Almost three weeks later, the post took on a different tone. The Federal Aviation Administration issued a national groundstop on Friday the 13th, throwing airline schedules into chaos. Officials quickly stated there was no evidence of a cyberattack and no sign that SMART caused the communications failure. When asked if he could rule out AI failure that night, Homeland Security secretary Markwayne Mullin replied, “There’s nothing certain right now.”
Autonomous flight milestones
New systems like SMART represent only the beginning of changes in aviation. Consider the Cessna Caravan that departed Buchanan Field Airport in Concord, California, on a calm September morning. The single-engine turboprop flew south to Phoenix, then east to Fort Worth, stopped at Shaw Air Force Base in South Carolina, and finally landed at Dare County Regional Airport off the coast of North Carolina. The trip covered 3,200 miles while navigating busy airspace and avoiding storms.
The journey was remarkable because no human touched the controls. Joby Aviation, the company behind the project, stated a safety pilot remained aboard the aircraft but never needed to intervene. The flight marked a major milestone. The industry has traditionally been conservative because human lives are at stake. Technology is often better when it is time-tested than when it is new and unpredictable. Yet AI is entering aviation with unprecedented speed. The immediate effects are hard to see, but the coming changes promise to alter air travel economics and how people and goods move through the sky. A key question remains: can we trust this technology to be reliable and safe?
Industry perspectives
Opinions vary. A recently retired FAA employee stated, “We’re introducing all this new technology to improve the system, and it’s going to be a disaster.” They added, “This is literally a Pandora’s box that we are going to regret.”
History of automation
Aviation’s adoption of AI dates to the early 2000s. Advances in batteries and microelectronics made drones more capable and inexpensive. Officials concluded that robots and humans would eventually share the airways, requiring new infrastructure. At that time, virtually all aircraft were piloted by humans, leaving no way for drones to avoid human-flown planes or each other.
In 2007, the federal government launched Next Generation Air Transportation System, known as NextGen. This project mandated broad changes to air travel over coming decades. A key provision required aircraft in the United States to be equipped with ADS-B by 2020. This system constantly sends radio signals indicating an aircraft’s location and destination.
With a roadmap for robot-friendly skies in place, major players like Amazon and Walmart began planning drone delivery services. In 2014, Google unveiled Project Wing. By 2018, the service was ferrying food, coffee, and medication to 164 homes near Canberra, Australia. The next year, the pilot program expanded to Christiansburg, Virginia. Costs were high and service slow, but the programs were not meant to be viable businesses. Instead, they provided Google with operational experience for future use.
Simultaneously, startups developed electric vertical takeoff and landing aircraft, or eVTOLs, also known as electric air taxis. These are essentially oversized drones designed to carry a few people short distances. By 2022, 600 different models were under development. Manufacturers promised cheap, short aerial hops would become common. Joby was among the leaders. In 2020, the company unveiled the design of its S4 model, which it said could carry a pilot and four passengers 100 miles or more at speeds up to 200 mph. The S4’s maiden flight occurred last year.
A commercial launch seemed imminent but deadlines kept getting pushed back. Engineering a flying autonomous robot was only part of the problem. Designing an airspace for operation, training humans to supervise them, and developing an economic framework were also necessary. “It’s a very important, safe, careful dance,” says Bowles.
Regulatory hurdles
Silicon Valley’s speed often conflicts with air travel norms. “Aviation regulation has been conservative and prioritizes reliability, because the consequences of failure are severe,” says Mary Schiavo, an aviation lawyer and former inspector general in the Department of Transportation. “Certification standards and airworthiness require proof and demonstrated safety, and that usually means incremental rather than radical change.” The FAA was not in a rush to let unproven robots operate in national airspace.
AI faced resistance in Europe as well. In 2017, aircraft manufacturers Airbus and Dassault asked EASA, the European Union’s version of the FAA, to consider allowing airliners to operate with a single pilot. Traditionally, airliners require multiple pilots to divide workload and ensure a replacement is available if one becomes incapacitated. In Airbus’ vision, automated systems would shoulder the copilot’s workload and take over entirely if needed.
That idea horrified pilots. The European Cockpit Association, a union of airline pilots, lodged a strong protest. The union explained to me via email that such a move “would remove an independent safety professional from the flight deck and give operators greater influence over the safety judgments that a pilot would otherwise make.” Last year, EASA shelved the plan.
Current expansion
Nevertheless, AI pressed onward. In 2023, the FAA began issuing waivers to allow delivery-drone flights beyond the visual range of operators. By the end of this year, it could make the rule change permanent. Major players are pushing ahead aggressively. This past August, Amazon announced plans to expand its drone delivery service to 500 locations across the country by the end of the year. Walmart is planning drone delivery from 270 store locations by the end of 2027.
The ultimate goal is larger. Industry insiders say that in a maximal vision, hundreds of thousands of drones will service most or all of the US population. “In five to 10 years, it’s going to be completely ubiquitous,” Anthony Vittone, chief operating officer of DroneUp, told me last year for Sherwood News. “People are going to be, like, ‘I don’t know how I lived without it.'”
Joby and other eVTOL companies have not progressed quite as fast but are moving ahead. In April, Joby flew the first-ever point-to-point eVTOL flight within New York City, from John F. Kennedy Airport to three heliports in Manhattan. The company has carried out similar flights in California and Texas under the auspices of the eVTOL Integration Pilot Program (eIPP). The Trump administration rolled out this federal initiative in March to demonstrate the capabilities of modern drones and eVTOLs.
Bowles says these demo flights are just the “front edge” of the Joby S4’s operational rollout. Next come demonstration flights with nonpaying passengers, then flights with paying passengers, and finally flights taking passengers from A to B. “All of that is permitted under eIPP, with increasing levels of oversight,” he says.
These flights will initially have human pilots, but paying one human to fly around a handful of passengers is expensive. For the model to make economic sense, the aircraft must fly themselves. If self-driving is a tough challenge for cars, it is all the more so for aircraft, where an unexpected control system failure is not just dangerous but likely deadly.
Behind the scenes
Given the scale of the challenge, AI’s entry into human passenger flight will not be as flashy as piloting eVTOLs. It will occupy a more modest, behind-the-scenes role. Data companies like Palantir and aviation industry stalwarts like Jeppesen and Thales are selling AI-enabled software that lets regulators, airlines, and flight dispatchers sift through masses of data to identify risks and plan aircraft and crew scheduling.
In September, the FAA announced it deployed software built by Air Space Intelligence, a Boston-based data company. The new AI-powered tool is called “Strategic Management of Airspace, Routes and Trajectories,” or SMART. It aims to reshape how airspace is managed. The program is not intended to replace controllers, the government says, but to make their jobs easier by using predictive AI to head off scheduling snags. “Combining SMART with our ongoing hardware upgrades gives us the tools to cut flight delays, optimize traffic, and keep airspace capacity across the country open—all while maintaining our gold standard of safety,” FAA administrator Bryan Bedford said in a press release.
The system is supposed to help controllers make decisions, not make those decisions for them. But if the program feeds nonsensical information into the system, will human operators catch the mistake? “This is the Trump/DOGE/Musk effect,” says the recently retired FAA employee, who asked to remain anonymous. “They’re pushing through all this new technology without any understanding of the complexity of the national airspace system.”
Some lawmakers are also concerned about SMART. On October 13, almost two dozen Democratic lawmakers reportedly sent a letter to the Government Accountability Office asking it to review the program. They cited fears that it might “hallucinate safety-critical information.”
Then there is the question of whether SMART could worsen the chronic shortage of air traffic controllers. The FAA hopes the technology lessens the shortage by requiring fewer workers. Other industries have yet to see AI-generated efficiencies actually materialize. Even if the software does not directly replace humans, the efficiency could be used to justify workforce reduction. In May, the FAA reduced its staffing target for active air traffic controllers from the 2024 goal of 14,633 down to 12,563, citing “modern staffing models and scheduling tools.”
Some are more optimistic than others. “I think the SMART program is an important improvement,” Schiavo says. “No one wants the current aviation environment with midairs, runway incursions, myriad near misses, delays, groundings, loss of separation, and long taxi or clearance wait times.”
Michael McCormick, a professor of air traffic management at Embry-Riddle Aeronautical University, also sees advantages to a predictive tool. “When you have the computing capability
