How A&D manufacturers can harness AI for innovation and resilience

We’ve all heard the hype about artificial intelligence (AI) and the last two years have seen a shift from AI experimentation to execution. The challenge has never been about whether AI could add value but about moving from pilot programs to company-wide implementations.

The aerospace and defense (A&D) sector's relationship with AI is complex. The U.S. Department of Defense increased its fiscal year 2024 budget to $842 billion, with a focus on integrating AI and automation into defense systems. The UK Ministry of Defence spent approximately £60.2 billion on defense in fiscal year 2024/25 with future planned increases including allocations towards new technologies. However, adoption patterns show a different picture. While AI spending is increasing, the industry faces distinct challenges compared to other sectors. The regulatory, security and mission-critical nature of A&D operations means that AI implementation needs more validation and testing than in other applications.

Where does AI deliver the most impact in the A&D industry?

• Predictive maintenance and asset management: AI can analyze large sensor data from aircraft systems and then detect anomalies and failures and trigger maintenance action before any issue occurs. This often results in reduced unplanned downtime and extended asset lifecycles.
• Manufacturing optimization and quality control: AI has revolutionized the manufacturing process by helping improve factory operation and supply chains, reduce delays, improve customer experiences, lower costs and increase productivity. In quality control, AI-powered visual inspection systems can spot defects that might get missed by human inspection, mainly during repetitive tasks.
• Supply chain intelligence: A&D supply chains are known for thousands of components, global supplier networks, long lead times and countless regulations. AI systems can analyze multiple variables at the same time, like supplier performance, demand patterns, geopolitical factors and production schedules to identify any potential disruptions.

How should A&D manufacturers approach AI implementation?

82% of A&D companies expect the highest value in product innovation and customer experience from AI implementations. This expectation is a mature understanding of where AI can deliver value rather than just operational efficiency. However, expectations must be balanced with implementation realities. Successful AI deployment in A&D manufacturing industry usually requires:

• Data infrastructure: A critical aspect in discussions of AI benefits is the requirement for proper data infrastructure. AI systems depend on quality data and in manufacturing environments, this means digitized operations and integrated systems.
• Clear problem definition: Starting with specific challenges rather than broad AI initiatives. Companies can achieve better results when they identify high-impact use cases and implement targeted solutions rather than attempting enterprise-wide AI transformation.
• Iterative approach: Beginning with pilot programs, measuring results, refining approaches and gradually expanding scope. This allows manufacturers to build internal expertise and show value before committing to full deployment.
• Change management: Ensuring that employees understand how AI tools enhance rather than replace their capabilities. User adoption remains one of the barriers to AI value realization.
• Vendor partnership: Working with providers who understand A&D requirements. Generic AI solutions often fail to address the specific regulatory, security and operational requirements that characterize this industry.

IFS.ai: Industrial AI built for A&D

IFS research reveals the barriers organizations face when implementing AI. In A&D manufacturing specifically, 42% cite legacy technology as hampering the road to AI value, 39% say data complexity is a challenge to AI value and 45% indicate that skills building needs to be a higher priority. These challenges underscore why purpose-built Industrial AI matters.

IFS.ai is AI specifically designed to help companies from different industries build business resilience, mitigate risks, support their sustainability strategy and meet their goals. For A&D, this translates into practical capabilities that can solve the industry's most pressing challenges. For instance, AI-powered maintenance scheduling and supply chain optimization maximize asset availability and minimize material delays to ensure the right parts are available when and where needed. Failure prediction prevents unscheduled maintenance, while failure identification, troubleshooting and repair suggestions promote maximum technician efficiency.

Overcome barriers with Baker Tilly

Baker Tilly provides the manufacturing industry with a complement of resources, capabilities and an approach to IFS Cloud implementations that is market-leading and will be transformational to your business. We work alongside our clients to ensure that their IFS Cloud implementation, integration and training is successful so they have full confidence and can take complete ownership and operation of the application suite.

Take the next step in AI implementation!