The article argues against a common misconception: AI does not fly UAVs and never should. Low-level flight control relies on deterministic systems like state estimation and control loops running at hundreds of Hertz with hard real-time constraints. Probabilistic AI models, with variable latency and silent failure modes, are fundamentally unsuited for keeping a drone stable and safe.

Instead, AI belongs at the high-level cognition layer. Its proper use cases include target detection, terrain understanding, path planning, and mission-level decision-making. The author outlines a healthy architecture where the flight controller handles survival, autonomy stacks manage logic, and AI modules provide perception and assistance. This hierarchy is critical for reliability.

The future of robust UAVs is hybrid, not purely AI-driven. Systems will blend classical control for stability with AI for world understanding, trusting physics over data. This clarifies AI's role as an advisor that suggests actions but never directly touches the controls, a crucial distinction for aviation safety.