Our digitally hyper-connected smart world continues to transform around us at an ever-accelerating pace. From the birth of the integrated circuit in the ‘70s to smartphones, the Artificial Intelligence (AI) revolution is just the latest evolutionary phase of technology that is encompassing almost every aspect of our lives.

While aviation has historically been a cautious adopter, they are well on the way to incorporating AI technologies in many diverse applications, including aerospace manufacturing. AI helps consolidate the disparate information across the aerospace industry’s highly connected manufacturing information technology and operational technology systems, providing a common operating picture for the management of all manufacturing activities. Today’s aerospace factories are a complex menagerie of legacy and modern systems, each with associated processes and data sources, reflecting when they were implemented; AI stitches this patchwork together. The 10^th annual State of Smart Manufacturing report states that 56% of companies are piloting smart manufacturing—20% at scale, and 20% planning to invest—highlighting the adoption rate across manufacturers¹.

AI provides a unique ability to assess large amounts of data and identify patterns and anomalous behavior of the systems and processes. Once identified, it can then recommend corrective actions to help improve both quality and productivity. AI is commonly used in the aerospace industry for predictive maintenance of aircraft and other aerospace platforms, enabling the detection and response to systems before they fail, thereby providing operators with the ability to maintain uninterrupted service. Similarly, IBM ranks predictive maintenance as one of the most impactful industrial AI use cases, reducing unexpected downtimes and maintenance costs².

Embry-Riddle Aeronautical University’s Center for Aerospace Resilient Systems (CARS), along with MIT Lincoln Laboratory and Astronautics Corporation of America, have been a part of the FAA Cybersecurity Data Science (CSDS) research program, which is focused leveraging AI for the detection of cyber threats to aviation systems, including manufacturing, aircraft logs, ground support systems and the supply chain. Since 2021, Dan Diessner and, more recently, Dr. Sean Crouse, have led the FAA’s CSDS research program engagements with the Aerospace Industries Association and the aviation OEM community. These efforts to apply AI against cyberattacks on the U.S. aerospace manufacturing base have already produced tangible results. The CSDS team has released an Aviation Architecture Framework (AAF) that maps shop‑floor, supply‑chain and flight‑operations data into a common ontology, giving analysts a single pane of glass across IT and OT assets³. More recently, Embry-Riddle CARS has also partnered with the University of Washington and aviation original equipment manufacturers in a National Institute of Standards and Technology (NIST) AI for Resilient Manufacturing proposal to establish a Manufacturing USA Institute dedicated to the application of AI for manufacturing in the U.S. aerospace industry.

While aerospace manufacturing has some unique aspects, leveraging and applying the success of other manufacturing industries will accelerate implementation. The National Association of Manufacturers highlights that AI is now integral to U.S. manufacturing, enhancing efficiency, product innovation, safety and predictive maintenance while keeping workers in the decision loop⁴. As AI becomes synonymous with smart manufacturing (the defining capability of Industry 4.0), aerospace producers now stand at a pivotal juncture. Those who pair rigorous data governance with targeted, worker-centric AI deployments will not only drive first‑pass yield higher and unplanned downtime lower; they will also fortify the cyber-physical backbone that keeps the global fleet in the air. 

The roadmap is clear: start with clean, connected data; pilot high‑value use cases such as vision‑based inspection or predictive maintenance; scale through cross‑functional teams that blend operations, security and data science; and measure success in both throughput and resilience.

As we look toward the September 5, 2025 EVOLVE Learning from Leaders forum, where we will explore how AI impacts your business and your life, the imperative for aerospace manufacturing is unmistakable—enhance decades of manufacturing craftsmanship with the latest technologies, and let AI propel aerospace into its next era of safety, speed and sustainable growth.

References:

• Rockwell Automation (2025). Research Report 10th Annual State of Smart Manufacturing Benchmark your digital strategy, explore global best practices, and uncover 2025 investment trends. https://www.rockwellautomation.com/en-us/capabilities/digital-transformation/state-of-smart-manufacturing.html?
• Finio, M., & Downie, A., (2024, November 15). How is AI being used in manufacturing? By Finio & Downie. IBM. https://www.ibm.com/think/topics/ai-in-manufacturing
• ERAU Center for Aerospace Resilient Systems. (2025). Cyber Security Data Science (CSDS). https://erau.edu/research/industry-collaboration/center-for-aerospace-resilient-systems/csds
• National Association of Manufacturers. (2024, May). Working Smarter: How Manufacturers Are Using Artificial Intelligence. https://nam.org/wp-content/uploads/2024/05/NAM-AI-Whitepaper-2024-1.pdf