Air Force New Fighter Jet: Secret Plane Will Have AI Copilot

The U.S. Air Force has a new favorite way to announce big things: hint at them, confirm they exist, refuse to elaborate,
and thenwhen everyone’s eyes are glued to the skycasually add, “Oh, and it’ll have an AI copilot.” If that sounds like
sci-fi, that’s because sci-fi has been doing product marketing for fighter jets for decades. The difference now is that
the Air Force is testing, funding, and fielding the building blocks of AI-assisted flight in public view… while keeping
the most sensitive details under wraps.

This article breaks down what the “secret plane” likely refers to, what an AI copilot actually means (spoiler:
not a robot that steals your snacks mid-sortie), and why the next era of air combat is less about a single miracle jet
and more about a team: a crewed fighter working with AI-enabled systems and uncrewed “wingmen.” We’ll keep it grounded,
practical, and readablebecause if your browser can autocomplete your address, your fighter jet can probably help manage
a few thousand sensor inputs without breaking a sweat.

The “Secret Plane” Isn’t One PlaneIt’s a Whole Approach

When headlines talk about the Air Force’s “secret new fighter jet,” they’re usually pointing at the umbrella effort
known as Next Generation Air Dominance (NGAD). NGAD has long been described as a family of systems,
not just a single aircraft. That’s an important mindset shift. For decades, we’ve treated fighters like superhero
origin stories: “Here’s the jet. Here’s the stealth. Here’s the nameplate.” NGAD is more like a cinematic universe:
multiple platforms, shared tech, rapid upgrades, and a big emphasis on networking, survivability, and teaming.

The Air Force’s current air dominance fighter, the F-22 Raptor, entered service in 2005 and remains a
benchmark for stealth and air-to-air performance. But threats evolvedespecially long-range air defenses, electronic
warfare, and the sheer geography of possible future conflicts. Range, persistence, and the ability to operate in
heavily contested airspace increasingly matter as much as raw maneuvering.

One of the most eye-catching parts of this story is how quickly the Air Force pushed early NGAD work. The service has
publicly acknowledged flying a demonstrator years before most people had heard the acronym. That’s where the “secret plane”
vibe comes from: a real aircraft existed, flew, and proved conceptswithout the traditional slow-roll of public detail.

Meet the F-47: The Public Face of a Still-Secret Program

In 2025, the Air Force publicly moved NGAD into a major new phase by awarding an Engineering and Manufacturing Development
(EMD) contract to Boeing for the crewed NGAD platform designated the F-47. A designation doesn’t mean we suddenly
get a full spec sheet, a walkaround video, and a “Top 10 Features” slideshow. It means the program is real, funded, and
moving forwardand that the Air Force is ready to attach a name to what was previously mostly classified.

Public reporting and official statements emphasize that the F-47 is intended to replace the F-22 as the centerpiece of
air superiority, while operating alongside uncrewed systems. What stays classified are the details that matter most in
a real fight: exact signatures, sensor performance, mission systems, electronic warfare approaches, and how it’s expected
to survive when everything in the sky is trying to detect, jam, track, and ruin your day.

What an AI Copilot Really Is (and What It Isn’t)

“AI copilot” is catchy, but it can mean a range of thingsfrom a smart assistant that manages sensors to an autonomy
system capable of flying aggressive maneuvers while a human supervises. In practice, the Air Force’s public messaging
points toward human-machine teaming: the human still has command authority, while the AI helps handle complexity,
speed, and information overload.

Think “Workload Manager,” Not “Replacement Pilot”

Modern fighters already rely on computers for stability, navigation, sensor fusion, and weapons integration. The leap
to AI copilots is about adding software that can:

• Prioritize sensor inputs so the pilot sees what matters right now (not everything, everywhere, all at once).
• Suggest routes and tactics based on mission goals, threat updates, and fuel/time constraints.
• Automate routine tasks (checklists, configuration changes, sensor modes) at the speed of relevance.
• Coordinate with uncrewed teammatesassigning roles, deconflicting airspace, and adapting as conditions change.

Why This Matters: Humans Are GreatUntil They’re Swamped

The pilot of a next-gen fighter isn’t just flying. They’re managing sensors, communications, electronic warfare,
datalinks, mission updates, and (potentially) a small formation of uncrewed aircraft. That’s like being a driver, air
traffic controller, and cybersecurity analystwhile pulling Gs. An AI copilot isn’t there to take the stick for fun.
It’s there so the human can focus on judgment, intent, and rules of engagement while the machine handles the “busy work”
at machine speed.

Proof It’s Not Just Marketing: AI Has Already Flown With the Air Force

If “AI copilot” sounds like a concept pitch, it helps to know the Air Force and DARPA have already put AI into real aircraft
in meaningful ways. These efforts aren’t the final answer for the F-47, but they show the direction: build trust, prove safety,
and expand autonomy step-by-step.

Example 1: The U-2 and an AI “Aircrew Member”

In late 2020, the Air Force reported a milestone: an AI algorithm flew aboard a U-2 Dragon Lady and acted as a working
aircrew member during a sortie. The systemknown publicly as ARTUµwas trained to execute specific in-flight tasks
that would normally be handled by the pilot. It’s a perfect early template for “AI copilot” as a workload partner: not a rogue
decision-maker, but a trusted system taking on defined responsibilities.

Example 2: DARPA ACE and Real-World AI Air Combat Tests

DARPA’s Air Combat Evolution (ACE) program has pushed beyond “helpful assistant” into the realm of autonomy in highly dynamic
situations. In 2024, DARPA announced in-air tests of AI algorithms autonomously flying an F-16 against a human-piloted F-16 in within-visual-range
combat scenarios. The headline takeaway wasn’t “robots are taking over.” It was: the U.S. is working to make autonomy reliable,
testable, and trustworthy in the most demanding environment possible.

Example 3: The X-62A VISTA and the Secretary of the Air Force’s Ride-Along

Also in 2024, the Secretary of the Air Force flew in the X-62A VISTA, an experimental aircraft used to test AI and autonomy capabilities.
The stated goal was to experience the technology firsthand and highlight how machine learning and specialized software can support
autonomous aerial combat testing. Public details are understandably limited, but the message was clear: senior leaders are confident enough
in these systems to get in the cockpit with them (with the appropriate safety frameworks in place).

The Bigger Play: Crewed Fighters + AI Drone Wingmen

The most important context for an AI copilot is that the Air Force wants future airpower to scale. Crewed stealth fighters are incredibly capableand
incredibly expensive. Meanwhile, a single pilot can only be in one place at one time. Enter the concept of uncrewed teammates: aircraft that fly with,
support, and extend the effectiveness of crewed platforms.

That’s the heart of the Collaborative Combat Aircraft (CCA) effortoften described as “loyal wingmen.” The idea is not to replace the crewed fighter,
but to multiply its impact with semi-autonomous uncrewed aircraft that can carry sensors, provide decoys, extend reach, and take on mission roles
that are too risky or too numerous for a limited fleet of exquisite crewed jets.

Why AI Copilots Pair Naturally With CCAs

Imagine a pilot managing even two uncrewed wingmen manually while also handling a contested environment. It’s doable in a demo, but it’s not scalable.
AI copilots become the glue: helping the human give higher-level intent (“screen this sector,” “hold this altitude block,” “prioritize that emitter”)
while autonomy handles execution details at speed. The mission becomes less about micromanaging and more about commanding a small, networked team.

The Tech Under the Hood: Digital Engineering and “Upgradeability”

One of the most underrated parts of the NGAD story is the Air Force’s emphasis on digital engineering, modular open systems,
and faster software iteration. This matters because AI copilots are software-heavy. Software needs updating. And updating software on a highly secure,
combat-critical platform is not the same as updating your phone (because your phone update rarely has to survive electronic attack at Mach numbers).

Public descriptions of the program highlight the idea of building aircraft that can be upgraded more rapidlyboth hardware and softwareso the force
doesn’t get stuck waiting a decade to add capabilities that are already standard in the commercial world. In plain terms: the Air Force wants a fighter
that can evolve, not fossilize.

Strategic Why: Range, Survivability, and Beating the “Tanker Problem”

The Air Force’s thinking about future air dominance is shaped by geography and contested environments. Long distances matter. So does the vulnerability
of support assets like aerial refueling tankers. Public analysis has noted that older concepts of operations face new risk when adversary air defenses and
electronic warfare systems become more sophisticated and long-ranged.

This is where the “family of systems” approach becomes practical. Instead of relying on one platform to do everything, NGAD aims to mix survivable crewed
aircraft, uncrewed teammates, and networked capabilities that can adapt to threats. An AI copilot fits because it helps manage complexity and make better
use of the assets you actually have in the air.

The Hard Part: Trust, Safety, and Cyber Reality

AI in a fighter jet isn’t just a technical challengeit’s a trust challenge. The Air Force and DARPA repeatedly emphasize building confidence in autonomy:
testing in controlled ways, using safety pilots and strict boundaries, and proving systems can behave predictably even when the environment is chaotic.

Three Real Concerns (No Drama, Just Reality)

• Reliability under stress: It’s one thing to run autonomy in a clean test environment. It’s another to do it when communications are jammed,
  sensors are degraded, and the aircraft is maneuvering hard.
• Human control: The public policy direction emphasizes human oversight when it comes to weapons employment and lethal decisionsbecause accountability
  doesn’t autopilot itself.
• Cybersecurity: An AI copilot is software, and software can be targeted. Protecting mission systems and ensuring integrity is non-negotiable.

What to Watch Next

If you’re tracking the “secret plane with an AI copilot” story, here are the practical signposts to watch for (without expecting classified details to suddenly
appear on your timeline):

• Budget signals: Funding lines for the NGAD platform and CCA efforts reveal priorities and pace.
• Test milestones: Continued autonomy demonstrations (especially in realistic mission conditions) show maturity.
• Industry moves: Partnerships around autonomy software, mission systems, and secure networking matter as much as airframe headlines.
• Doctrine and training: How pilots are trained to work with AI copilots will tell you what the Air Force expects them to do in combat.

Conclusion: The Future Fighter Cockpit Is a Team Sport

The most interesting part of the Air Force’s next fighter era isn’t just a sleek rendering or a mysterious designation. It’s the shift in mindset:
air dominance as a systemwith a crewed platform at the center, backed by uncrewed teammates, and supported by AI that helps a human pilot
keep pace with machine-speed warfare.

The “AI copilot” phrase is sticky because it’s easy to picture: a digital partner that helps fly, fight, and decide faster. But the real story is more grounded:
reducing pilot overload, enabling manned-unmanned teaming, and building autonomy that can be trustedbecause in the air, “mostly works” is not a comforting review.

Experiences: What It Might Feel Like to Fly With an AI Copilot (A Pilot’s-Eye View)

Let’s talk “experience,” because that’s where this topic gets real. Not in a Hollywood wayno glowing robot eyes, no dramatic “I’m afraid I can’t do that, Dave”
momentbut in the practical, sweaty-palms, checklist-and-judgment world of flying advanced aircraft.

Picture the start of a mission day. You brief the plan, study threats, and run through contingencies. In a traditional fighter workflow, you’re already juggling
a dozen mental plates before you even taxi. With an AI copilot, the first “experience” is quiet: it’s not that the AI talks moreit’s that you do less
administration. The system can pre-load mission data, verify configuration mismatches, flag timing conflicts, and nudge you when the plan and the aircraft
setup disagree. It’s like having a very calm crew chief who lives inside the avionics (and never asks you to “circle back”).

Now you’re airborne and the environment starts changing. Maybe a datalink picture updates. Maybe a threat emitter lights up in a place it “shouldn’t” be.
In older paradigms, you’d dig through menus, cross-check displays, call for information, and try not to fall behind the timeline. The AI copilot experience is
more like: the system highlights what changed, suggests two or three response options, and explains why in plain pilot logic (“If you stay on this route,
your exposure time increases; alternate route adds 18 seconds but reduces risk”). You’re still the decision-maker. The AI is the fast analyst who never gets tired.

The most intense “experience” is when the workload spikesmultiple contacts, degraded comms, and your uncrewed teammates need direction. In a manned-unmanned
team, you don’t want to micromanage drones like you’re playing a strategy game with a broken mouse. You want to command by intent. An AI copilot helps translate
intent into action: “Wingman 1, widen the sensor net; Wingman 2, stay close and be my shield.” The autonomy handles spacing, timing, and collision avoidance
so you can keep your attention on the fight and the rules you must follow.

Then there’s the human side: trust. At first, you’d probably treat the AI like a new coworkeruseful, but you double-check everything. Over time, as it proves
consistent, you start to lean on it for what it’s best at: pattern recognition, speed, and relentless monitoring. That shift doesn’t feel like “giving up control.”
It feels like gaining margin. More time to think. More bandwidth to coordinate. More calm in moments where calm is a tactical advantage.

Finally, the debrief. If you’ve ever flown anything complicated, you know the post-flight is where learning happens. An AI copilot changes that experience too.
Instead of relying only on memory and limited logs, you can get richer timelines: what the system “saw,” why it recommended certain options, where it hesitated,
and how human decisions interacted with autonomy. That’s gold for trainingand it’s a major reason the Air Force and DARPA are so focused on building trust
through measurable testing rather than vibes.

So what’s the lived takeaway? Flying with an AI copilot would likely feel less like a robot takeover and more like a workload upgrade. The jet is still fast.
The stakes are still high. The decisions are still human. But the cockpit becomes less of a one-person circus and more of a well-run teamwhere the AI does
the heavy lifting on speed and data, and the pilot does what humans do best: judgment, accountability, and adapting when reality refuses to follow the script.