Pardoned Nikola founder Trevor Milton is trying to raise $1B for AI-powered planes

Trevor Milton and an unnamed investment group bought SyberJet Aircraft late last year and are attempting a turnaround aimed at creating an AI-focused light jet. The effort has involved bringing in "dozens" of former Nikola employees, soliciting potential Saudi investors, and spending a few hundred thousand dollars on lobbying; Milton — convicted of fraud in 2022 and pardoned roughly a year ago — admits the project may be "10 times harder than Nikola ever was."

Analysis

A greenfield attempt to vertically integrate AI-native avionics for light jets creates two structural threads: a high upfront capital and certification hurdle that favors deep-pocketed incumbents, and a potential disintermediation of traditional avionics suppliers if the newcomer succeeds. Certification alone is typically measured in multiple years and can require low- to mid-hundreds of millions of dollars in engineering and testing before any volume revenues, so market moves will be driven by funding cadence and regulatory milestones rather than product announcements.

Second-order winners are the large systems integrators and defense primes that can convert any early demonstrators into scalable military/ISR contracts—they have the installed relationships, security-cleared workforce, and scale to absorb long certification timelines. Conversely, small public eVTOL/airframe names and speculative OEMs face funding competition and investor attention risk; capital that might flow into them could be diverted toward autonomous avionics hype, compressing their raising windows.

Key near-term catalysts to watch are FAA/EASA engagement signals, any DoD RFI/OTA activity, and tranche-specific fundraising rounds; each funding milestone materially de-risks the project and can re-rate related public suppliers. Tail risks include failed certification tests, supplier attrition, or a pivot toward defense that lengthens commercialization beyond investor patience—each can reverse sentiment quickly within 3–18 months.

Key Decisions for Investors

• Pair trade (6–18 months): Long RTX (RTX) and HON (HON) at market — these capture retrofit/defense subsystems revenue if a new entrant stokes demand for AI avionics. Hedge by shorting small-cap airframe/eVTOL names JOBY (JOBY) and Lilium (LILM) to offset headline-driven flow. Target return: 12–25% vs downside ~10–15% if certification timelines slip; keep size modest (max 2–3% net exposure).
• Directional AI/autonomy bet (12–24 months): Buy NVDA (NVDA) call exposure (e.g., 12–24 month LEAPs) for asymmetric upside from increased avionics GPU/AI demand and training requirements. Risk: broader semis drawdown; reward: high single-digit to 2x upside if autonomy compute TAM grows materially.
• Event-driven speculative (3–12 months): Small long position in LMT (LMT) or NOC (NOC) for defense upside if DoD issues RFIs for light autonomous platforms — treat as binary 3–6% portfolio tranche with stop at 6–8% drawdown. Rationale: primes win follow-on subsystems and integration work even if startups prototype the concept.
• Liquidity/risk management: Avoid outright large long positions on any single new entrant; instead scale exposure to public suppliers via options and pair trades. Set hard time-based stops at 12 months if no material FAA/DoD milestone is achieved to limit capital lock-up given long certification timelines.