Aerospace Software: AI Must Produce Evidence, Not Just Output
For flight-critical software, the test for AI development tools is whether their output survives as certifiable evidence, not how fast it was produced.
AI assurancebriefings.
The Next Certification Frontier Is Navigation, Not Autonomy
As AI-driven sensor fusion becomes the answer to GNSS jamming and spoofing, aviation certification lacks a framework for proving adversarial robustness.
The Compliance Question Surrogate Models Can't Answer
AI surrogate models are replacing validated engineering and lab tools faster than ISO 42001, the EU AI Act, and FDA regimes can absorb them.
Aviation Is Deploying AI Faster Than It Can Certify It
MRO, cockpit, and airspace AI are advancing across aviation while the FAA still lacks a settled safety assurance method, raising airworthiness and liability exposure.
The Assurance Gap Behind Every AI Autonomy Pitch
Aerospace certification data from Farnborough exposes a wider governance problem: many AI autonomy and risk-detection claims have no equivalent conformity regime at all.
The Compression Blind Spot in Aerospace AI Assurance
Edge AI models shrunk by 99% for aerospace and defense inference lack a certification pathway to treat compression as a qualifiable design change.
Explainable AI for Defense Systems Is Still R&D, Not a Certified Capability
Fresh SBIR funding for real-time model health monitoring shows explainable AI assurance in defense aerospace remains pre-competitive research, not a purchasable safeguard.
AI Autonomy's Blind Spot Is the Signal It Trusts
Aerospace AI assurance cases assume clean navigation data, but PNT signals are now contested terrain that most safety cases never model.
