Fix Business Processes First, Then Add AI, Experts Advise

Industry experts advising aerospace and aviation operators are urging a foundational discipline before AI adoption: fix the underlying business processes first. The guidance, surfaced at discussions in Wichita among aerospace professionals and reported by Aviation Week's Molly McMillin, reflects growing concern that companies are layering AI tools onto dysfunctional workflows and expecting transformative results. The domains where AI is generating the most conversation in aerospace—supply chain management, workforce pipeline development, MRO backlogs, and operational efficiency—are precisely the areas where poorly structured data, inconsistent processes, and siloed information have plagued the industry for decades.

The caution is especially relevant to flight departments and aviation operators considering AI-assisted tools for maintenance tracking, parts procurement, scheduling optimization, and crew management. An AI system can only surface patterns and predictions as reliable as the data it ingests. For Part 91K and Part 135 operators managing aircraft on complex interchange or lease agreements, or for MRO providers handling heavy checks on business jets with incomplete historical records, feeding disorganized or inconsistent inputs into an AI model does not yield better decisions—it accelerates bad ones at scale. The practical implication for operators is that the prerequisite work is analog and organizational: standardizing data entry, enforcing documentation discipline, and clearly mapping workflows before any AI layer is introduced.

The broader aerospace supply chain context adds urgency to this conversation. Since the post-pandemic recovery, the business aviation sector has confronted sustained backlogs in airframe and engine MRO, persistent AOG parts delays, and technician shortages that show no near-term signs of resolution. AI-driven demand forecasting and inventory optimization tools have been marketed aggressively as solutions to these problems, and some large OEMs and MRO networks have reported genuine efficiency gains. However, those gains have generally come at organizations that had already invested in ERP standardization, parts data hygiene, and digitized maintenance records—the structural prerequisites that smaller operators and FBOs often lack.

For flight operations professionals, the expert consensus represents a useful counterweight to vendor pressure and industry hype cycles. Aviation has historically been an early and serious adopter of automation in safety-critical contexts, yet the administrative and logistics layers surrounding flight operations have often remained paper-heavy or patchwork-digital. The sequencing advice—process discipline before AI deployment—echoes lessons from earlier technology transitions in aviation, including the adoption of electronic flight bags and electronic maintenance logbooks, both of which required cultural and procedural overhaul before they delivered promised efficiency. Pilots and aviation managers evaluating AI procurement decisions in 2026 would be well-served by auditing their own data quality and workflow consistency before committing to platforms that assume clean, structured inputs.