The transformation from paper-led operations to digitally driven, AI-enabled systems for aerospace and defense (A&D) manufacturing is here. Over the past two years, the conversation has evolved from cautious curiosity to a clear path forward. Today, smart, focused deployment of AI is a strategic imperative for A&D manufacturers.
AI Momentum in A&D: From Buzz to Business Case
At iBase-t’s Excelerate user conference in April, I highlighted a decisive shift—AI is no longer just a futuristic concept, it’s a business priority. And since ChatGPT’s November 2022 release, I’ve noticed that executive sentiment in A&D manufacturing has changed dramatically:
- Companies have moved from a “wait and see” mentality to asking, “How do we start implementing AI?” Although some executives still have questions about risk, we see many are now asking about implementation timelines and quick-win opportunities to solve operational challenges.
- AI initiatives have moved from R&D experiments to established operational budget line items.
- Boards and leadership teams now express clear concern about being eclipsed by competitors who are already leveraging AI, particularly in related industries such as automotive manufacturing.
- Concerns about AI displacing the workforce are now being replaced by the realization that AI will help address skills and labor shortages.
Adoption of AI in A&D manufacturing is no longer theoretical. It’s become mission-critical.
What Sparked the AI Explosion
AI’s rise didn’t happen overnight. It was enabled by the intersection and simultaneous growth of three pivotal technologies:
- Big Data: A&D manufacturing generates an immense amount of data, such as sensor readings, maintenance records, and quality inspection information. Digital transformation efforts have centralized this information into more accessible and structured “data lakes.” Cloud storage made it possible to retain and process this data economically.
- Graphics Processing Units (GPUs): Originally built for gaming, GPUs excel at parallel processing or handling thousands of simultaneous calculations, such as matrix calculations. Driven by platforms like NVIDIA’s CUDA, GPUs were then designed to be programmable for AI tasks. While their performance soared, costs began to drop significantly, making the technology more accessible and financially feasible.
- Cloud Computing: The cloud removed infrastructure barriers entirely, freeing up budgets and making enterprise AI available to mid-size A&D manufacturers, and not just the prime suppliers.
By late 2022, the computing power, data readiness, and cost accessibility from these three technologies converged, making AI a feasible reality for many more companies.
Aerospace & Defense: The Perfect Environment for AI
A&D manufacturing isn’t just ripe for AI, it’s overdue. Legacy systems, like antiquated ERPs and paper-based processes and documentation, are fertile ground for automation and digitization. Manual-entry ERPs are prime targets for automation, while paper-based quality processes can be enhanced with AI-enabled computer vision technology.
Regulatory complexity, with standards like AS9100, NADCAP, and ITAR, demands perfect documentation, traceability, and audit readiness. AI enables 100% compliance checks and even predictive issue detection before audits occur. Compliance documentation can also benefit from AI’s natural language processing applications.
As mentioned earlier, adjacent industries are already reaping the benefits of AI. The automotive industry is utilizing predictive maintenance, while most A&D manufacturers are still relying on scheduled maintenance. Tech companies are optimizing their supply chains with automation, but A&D is still using spreadsheets to keep track of it all. Forward-thinking A&D companies, like SpaceX and Blue Origin, use AI to iterate rapidly, while traditional companies are still using waterfall processes. At the same time, customers are increasingly expecting full visibility into their order or product status and availability, yet most A&D manufacturers cannot offer that level of customer service.
This confluence creates a competitive imperative: adopt AI now, or risk becoming irrelevant.
AI in A&D Manufacturing as a Competitive Advantage
AI investment in A&D manufacturing yields immediate, measurable returns, and iBase‑t is already implementing it with customers. For example, with Solumina ScanAI, manufacturers can digitize 1,000-page PDFs into Solumina workflows within hours. Previously, that same task would have required days or weeks of manual labor by highly paid manufacturing engineers who could have been using their time in a more valuable way. That’s a force multiplier for digitization and compliance. Beyond that, AI in A&D manufacturing can:
- Reduce rework through automated inspections and discrepancy detection.
- Result in faster decision-making due to its ability to sift through vast, complex data and deliver insights in real-time.
- Improve quality and compliance with computer vision and structured workflow automation.
- Free up skilled workers to focus on hands-on work while AI takes care of repetitive tasks.
In short, A&D manufacturers shouldn’t view AI as a nice-to-have or luxury. It’s a competitive advantage. The companies that act now will define the industry’s future. Those who wait will struggle to catch up.
The AI Wave Is Here
When implementing AI, companies can take a few critical steps to help set them on the right path. The goal is to start smart and start small, quickly prove the value of AI for your company, and then scale fast. Below are recommended actions for your first year of experimentation and implementation:
Immediate Actions (0-3 months):
- Audit your data readiness, identifying high-quality datasets for pilot projects.
- Form an AI task force with IT, operations, and quality representatives.
- Start with narrow, high-impact use cases (e.g., visual inspection, document processing).
- Partner with AI-experienced vendors who understand A&D requirements.
Medium-term Strategy (3-12 months):
- Implement pilot projects with clear success metrics.
- Build AI literacy through training programs.
- Establish data governance frameworks.
- Scale successful pilots to production.
Long-term Transformation (12+ months):
- Integrate AI into core business processes.
- Develop proprietary AI models for competitive advantage.
- Create feedback loops for continuous improvement.
- Build AI-first capabilities and culture.
At iBase‑t, our Solumina platform brings this transition to life with domain-specific AI tools designed for the complexity of A&D manufacturing. Are you ready to move with precision and purpose? Contact us to discover how iBase‑t can help you ride the AI wave, confidently and strategically.
