Artificial intelligence is transforming industries at record speed, with the global AI market already valued at $390.91 billion. However, in aircraft maintenance, where safety is non-negotiable, adoption remains deliberately cautious. Despite rapid technological progress, aviation experts estimate that full-scale AI implementation in aviation MRO will take at least a decade. Today, AI is applied selectively to support tasks such as surface-damage inspection, predictive maintenance, and inventory optimization, always under strict safety oversight.
In recent years, AI-related products and companies have emerged as key economic drivers, attracting significant attention from investors and the public. AI’s market size was valued at $390.91 billion in 2025 and is projected to reach $3.497 trillion by 2033.
However, industries employ different strategies to implement this technology. For example, adoption of new AI tools among aviation maintenance, repair, and overhaul (MRO) professionals has been relatively conservative.
The FAA published its first-ever AI roadmap in 2024 — it advocates a cautious, phased approach, starting with lower-risk applications before touching anything safety-critical. Full AI integration in aircraft maintenance is still years away, and those doing this work say that’s exactly how it should be. The reason is the strict boundaries. Yet, this does not mean that AI technologies have no place in today’s aircraft MRO (maintenance, repair, and overhaul).
According to Žilvinas Lapinskas, CEO of FL Technics Group, an independent aircraft MRO service provider, AI still has a way to go before it can be considered a trustworthy partner.
“When we discuss implementing new tools, it ultimately comes down to three key factors: efficiency, safety, and reduced turnaround times. At this stage, we do not yet have sufficient evidence that AI solutions meet all of these criteria. Aviation maintenance standards and procedures are extremely strict for safety and reliability, so we must proceed cautiously and be fully confident before introducing new technologies,” says Mr. Lapinskas. “However, this does not mean that AI cannot help optimize a wide range of daily tasks and processes. In areas such as engineering support, data analysis, and maintenance planning, advanced technologies can help process large volumes of technical information faster while remaining fully compliant with strict regulatory requirements.”
What can AI do and what cannot?
The aircraft MRO field is primarily driven by safety culture, meaning every decision is made through this lens. There are numerous reasons for this emphasis. Even a relatively small error can have far-reaching consequences, including mechanical failures or malfunctions that compromise passenger safety. FL Technics is still evaluating whether AI tools can ensure flawless work.
Mr. Lapinskas is certain that the broader push toward full digitalization will be the foundation of modern MRO. AI tools are improving at optimizing inventory management and workflow planning. In other words, AI is gradually being embedded in daily operations, accelerating task planning, coordination, and execution.
“Our innovation strategy has always focused on practical, measurable technologies that deliver cost-effectiveness and generate value for customers. This pragmatic approach enables us to improve operational efficiency while maintaining high safety and quality standards. As we explore the potential of AI and other emerging technologies, we will apply the same mindset: carefully evaluating how these solutions can support our operations and bring additional value in the future,” says Juozas Lapeika, Deputy CEO for Base Maintenance at FL Technics.
The company is already taking a careful approach to applying AI to selected operations. For example, its Base Maintenance Department uses AI-powered surface damage inspection to assess aircraft exterior conditions more quickly and consistently. Another key area is predictive maintenance. AI tools are used by the CAMO (Continuing Airworthiness Management Organisation) Department to automate compliance checks, document searches, and data analysis.
Similar technologies can also help transform large volumes of operational data into actionable insights. AI copilots are improving at helping engineers manage complexity and accelerate workflows.
