Pardoned Nikola Founder Milton Seeks $1B For AI Planes

Trevor Milton, the pardoned founder of Nikola, is courting investors to raise $1B for an ambitious push into AI-powered light jets after acquiring SyberJet Aircraft. According to a Wall Street Journal report, the effort centers on building a new avionics stack designed for AI-driven flight, positioning the small jet maker for potential commercial and defense opportunities.

Milton’s New Bet on Autonomy Centers on AI Avionics

Milton and an investment group purchased SyberJet late last year and have since sought to reboot the business by recruiting dozens of former Nikola employees, exploring funding from Saudi backers, and spending hundreds of thousands of dollars on lobbying. The plan, as described to the Journal, is to create a clean-sheet avionics architecture aimed at delivering a light jet that prioritizes AI-enhanced flight capabilities from day one.

He has acknowledged the scale of the challenge, characterizing aviation as substantially more difficult than the ground-vehicle venture that made him famous. The capital ask is equally bold: a ten-figure raise to underwrite software-heavy development, safety certification, and eventual production scale-up.

The SyberJet Puzzle: Retrofitting a Light Jet for AI

SyberJet is a niche light-jet manufacturer with a long-running program known for ambitious performance targets and persistent delays across multiple ownership eras. Turning that foundation into an AI-forward platform would require modernizing everything from flight controls and sensor suites to electrical and thermal systems that support high-compute avionics.

Industry engineers note that integrating AI into a safety-critical cockpit is not just a software problem. It touches weight, power, electromagnetic compatibility, redundancy management, maintenance tooling, and pilot training. For a small jet maker, that is a complex, multi-year orchestration of suppliers and regulators as much as it is a code sprint.

Certification and Safety Hurdles for AI-Centric Avionics

Any AI-centric avionics will face rigorous scrutiny from the FAA and international authorities. Safety-critical software typically must meet DO-178C objectives at the highest Design Assurance Level (DAL A), while hardware falls under DO-254. That means deterministic behavior, explainability, and verifiable failure modes—areas where cutting-edge machine learning still clashes with certification expectations.

Recent precedents show how cautiously autonomy is moving into cockpits. Garmin’s Autoland won FAA approval on select aircraft, handling emergency descents and landings when a pilot is incapacitated. Test programs from companies like Xwing and Reliable Robotics have demonstrated supervised autonomous flight and advanced autoflight capabilities, but full commercial certification remains incremental and tightly bounded.

Aerospace consultants say even conventional Part 23 certification for a new or heavily modified light jet can span multiple years with substantial nine-figure program budgets once testing, supply chain hardening, and conformity aircraft are included. Layering novel AI functions on top will likely add time, documentation burden, and specialized verification toolchains.

Market and Funding Reality Check for AI-First Light Jets

Investors have poured billions into next-generation aviation—from eVTOL air taxis to autonomous systems—through defense programs like the U.S. Air Force’s AFWERX initiatives and private-market raises by well-known startups. Analysts at firms such as McKinsey have tracked AAM capital flows in the tens of billions since 2020, but funding has grown more selective as timelines stretch and certification risk is repriced.

An AI-first light jet could find dual-use traction if it demonstrates measurable safety or cost advantages. Airlines and charter operators care about dispatch reliability, pilot workload reduction, and fuel efficiency. Defense customers prize autonomy for training, surveillance, and contested logistics. Without clear, certifiable performance improvements, however, the pitch becomes a hard sell in a cautious capital market.

Reputation Overhang and Governance Risks for Investors

Milton’s 2022 fraud conviction and subsequent presidential pardon are inseparable from the fundraising narrative. Governance, transparency, and program discipline will be central investor concerns, especially given the safety-critical nature of aviation. Expect diligence to focus on board independence, quality systems, supplier oversight, software safety cases, and the caliber of the avionics leadership bench.

Bringing in former colleagues may accelerate execution, but aerospace certification differs materially from automotive-style homologation. Investors will want evidence of experienced designated engineering representatives, robust human-factors testing plans, and early engagement with the FAA on certification basis and means of compliance.

What to Watch Next as Milton Pitches AI-Powered Jets

Key milestones to gauge credibility include:

• A defined certification strategy under Part 23
• Disclosure of Tier-1 avionics and flight-control partners (think Honeywell, Collins, or Garmin) or a convincing rationale for a homegrown stack
• A realistic prototype timeline tied to envelope expansion
• A safety case that moves beyond marketing to verification artifacts

On the financial side, signs of committed capital, not just soft circles, will matter. Any early research contracts from defense agencies, memoranda with charter operators, or pilot training partnerships would further validate demand. For now, Milton’s $1B raise for AI-powered planes is a high-risk, high-visibility bet that will live or die on execution and regulatory proof.