Executives Say AI Could Reshape Used Serviceable Material Trading, but Data Quality and Human Judgment Remain Key
Why It MattersAs new capital flows into the parts aftermarket, proprietary data and human judgment on part condition and traceability, rather than AI models alone, are being positioned as the lasting competitive edge.
Surging demand for used serviceable material (USM) from airlines and maintenance companies has drawn private equity, institutional and lessor capital into the parts market. New entrants should be wary, because the modeled and realizable values of aircraft teardowns can vary widely, depending on factors such as inventory turn times, repair costs and customer networks.
The parts aftermarket generates large volumes of data, including historical trading, repair events, market movements and customer behavior, which gives artificial intelligence considerable potential to support investment decisions, inventory placement and parts pricing. Scott Symington, chief commercial officer at AJW Group, said automated inventory tracking and forecasting can reduce errors and delays, and that the company's inventory management system, Apollo, uses probabilistic modeling to balance service levels with capital investment. He expects predictive capability to become increasingly important in helping businesses identify demand and position material before it is needed.
Darren Naughton, engines vice president at USM supplier APOC Aviation, agreed but said human judgment remains vital for assessing a part's condition and traceability. He said the differentiator over the next few years will be the quality of in-house data rather than the model built on top of it, and that AI can significantly improve turnaround times on certain tasks across the business, not just in trading.
Abdol Moabery, chief executive of GA Telesis, said he has seen numerous "paper tigers" in the AI space whose claims do not match their products, adding that a chatbot attached to an Enterprise Resource Planning system is not an AI strategy. He said the competitive advantage will go to companies with proprietary data, the infrastructure and people to use it, and evidence that AI is changing decisions and financial outcomes. GA Telesis began investing seriously in AI in 2022.
