Why the aviation aftermarket needs a reality check on the limits of automation and the enduring value of human judgment.
If you listen to the current market narrative around aviation software, you might think we are on the verge of entirely autonomous operations. Across the industry, from legacy providers like Veryon and OASES to newer entrants like AvSight, the messaging suggests that AI is ready to take the wheel—assisting with everything from deep analysis and complex recommendations to autonomous action inside daily workflows.
At Aviate, we believe in the transformative power of AI. But as we build the next generation of Aviation ERP, we also believe it is time for a necessary reality check.
Aviation is not an industry where we can “move fast and break things.” The stakes are simply too high. When it comes to Aircraft Services, MRO, FBO, and materiel distribution, we need a much more balanced conversation about where AI should help, where it should stop, and why human judgment must remain central.
Let’s separate the myths from the reality of AI in aviation operations.
Myth #1: AI will eventually make the final operational decisions.
Reality: AI should do the heavy lifting; humans must make the final call.
There is a misconception that the ultimate goal of AI in an ERP is to replace the decision-maker. The vision sold is one where the system autonomously orders parts, signs off on maintenance routing, and reroutes aircraft without human intervention.
In reality, autonomous decision-making introduces unacceptable risk. If an AI hallucinates a part compatibility or misinterprets an Airworthiness Directive, the consequences aren’t just a slight delay—they are grounded aircraft and compromised safety.
At Aviate, our philosophy is that AI should perform the exhaustive background work. It should instantly cross-reference the IPC, check global inventory, evaluate vendor reliability, and pre-stage a purchase order. But it must stop there. The AI presents a fully synthesized, evidence-backed option, leaving the final, critical sign-off to the human professional.
Myth #2: More AI “assistance” means a better workflow.
Reality: The best AI is invisible, not conversational.
Competitors are pushing the narrative that having an AI “assistant” constantly analyzing your work and offering recommendations is the pinnacle of software innovation.
The reality is that a busy shift supervisor at an MRO doesn’t want another voice in the room offering unsolicited advice. They want friction removed from their process. AI shouldn’t be a chatbot you consult; it should be the invisible engine automating the mundane.
Where AI Excels:
- Data Synthesis: Instantly pulling pricing history, market scarcity, and current inventory to suggest an optimal sale price for a rotatable part.
- Pattern Recognition: Flagging a recurring defect across a specific fleet type before it becomes a widespread bottleneck.
- Administrative Automation: Parsing complex RFQs and automatically mapping them to inventory SKUs.
By letting AI handle the high-volume, low-risk administrative burden, we clear the runway for humans to focus on high-value, complex problem-solving.
Myth #3: Trust in AI comes from how “smart” the model is.
Reality: Trust in AI comes from absolute traceability.
The market talks a lot about the intelligence of their underlying models. But in aviation, we don’t care how “smart” an algorithm is if we can’t verify its work. Human judgment relies entirely on context.
If an AI suggests replacing a component with an alternate part number, a human inspector cannot simply take the system’s word for it. They need to know why. Where does AI get risky? When it operates as a black box.
We are building Aviate so that every AI-driven recommendation comes with verifiable receipts. If our system suggests an action, it links directly to the specific Maintenance Manual page, the historical work order, or the Service Bulletin that justifies it. We believe that for human judgment to remain central, the human must have immediate access to the ground truth.
The Aviate Balance
The future of aviation ERP is not about building an AI that replaces the human. It is about building an operating model that makes the human undeniably faster, vastly more informed, and completely confident in their decisions.
By understanding where automation thrives (speed, synthesis, and background processing) and where it introduces risk (final approvals, safety compliance, and edge-case resolution), we can build software that respects the gravity of aviation operations.
We don’t need AI to fly the plane. We need it to clear the runway so our experts can do what they do best.
