AI-Powered Sustainment: Turning Complexity into Readiness

By Nick Smythe, Vice President, Sustainment Campaigns, Lockheed Martin

Lockheed Martin has been innovating for more than a century, and today artificial intelligence (AI) is a tool we're using to keep America, our allies, and partners safe. Now if this surprises you, join me in a quick rundown of how we continue to innovate and push the boundaries of technology in our industry.

Why AI

The world is smaller, more interconnected, and increasingly contested. In these environments sheer mass and energy no longer guarantee success; decision making speed does. AI gives us a decision advantage-the ability to process massive data streams, spot patterns, and recommend actions faster than humans alone could.

That's why Lockheed Martin is fueling sustainment innovation by fusing our systems engineering expertise with AI that delivers tangible, mission-critical outcomes for our customers.

Here are some real-world examples.

AI- Driven Demand Forecasting

Traditional approach: 20th century logistics relied on historic flight hour tables and static usage metrics. Those methods ignore real time consumption, leading to chronic under resourcing, limited stock effectiveness, and a reactive supply chain that can't keep up with modern combat tempos.

Our modern solution: Lockheed Martin now deploys machine learning models that ingest a richer set of variables:

• Consumption Data - Sensors embedded on airframes and subsystems report how often a component is engaged, the environmental stress it experiences, and degradation trends.
• Operational Profiles - Mission-specific factors (e.g., highG maneuvers, electromagnetic and atmospheric/environmental exposures) are fed into the model to weight consumption probability.
• Strategic Forecasts - AI integrates geopolitical risk indicators and projected sortie rates, producing a "decision advantage" horizon that tells logisticians where demands will spike in advance.

By moving from a static "flight hour" approach to a dynamic, AI driven forecast that leverages digital twins, the logistics pipeline becomes proactive. The model continuously retrains as new telemetry arrives, ensuring forecasts evolve with the operational environment-much like an iPhone that retains its shape but constantly adds new capabilities.

The dashboard is already live for the F-35 program, providing a 360-degree view of parts health, forecast confidence intervals, and actionable logistics orders. Extensions are underway for the F-22, F-16, and C-130 fleets, creating a common AI enabled picture across the Air Force's heterogenous platform set.

Autonomous Logistics and Technology Insertion

Looking ahead, logistics will increasingly run itself through AI driven robots and unmanned vehicles. By leveraging commercial AI advances, we can create a "logistics as a service" model that continuously injects cutting edge capabilities into sustainment.

• Autonomous Robotics and Resupply - Vision-based AI robots patrol supply warehouses, performing real-time cycle counts, detecting damage, and reallocating inventory without human intervention.
• Predictive Maintenance AI - Deep-learning models analyze engine vibration, temperature, and fuel-flow data to predict component failure up to 72 hours before it occurs, prompting preemptive part delivery.
• Digital Twin Simulations - AI driven digital twins of aircraft subsystems run in parallel with live platforms, enabling rapid "what if" testing of new repair processes, additive manufactured part designs, or upgraded software patches before field deployment.

These autonomous tools compress the acquisition cycle from years to months by eliminating manual bottlenecks and providing continuous performance feedback.

How Industry Should Think about Collaboration to Accelerate AI Based Capabilities

Make vs. Buy-partner when the fit is right.

We do not intend to develop every AI capability in isolation because we know the value of teamwork. When a company brings a compelling, complementary technology-be it advanced perception, autonomous navigation, or a specialized machine learning (ML) platform-we seek partnership. Our recent exploratory work with Rune Technologies on integrating Adaptive Logistics Intelligent Decision System (ALIDS) illustrates this approach. We identify where their product can plug into our sustainment architecture and codevelop a joint solution that is faster and more robust than either could build alone.

Service members at the core.

Let me be very clear, AI does not replace the warfighter; it protects and empowers them. Period. By automating routine diagnostics and logistical tasks, warfighters spend more time on mission critical tasks. The technology is designed to be transparent, providing clear recommendations while leaving final authority in the hands of combatant commanders.

Responsible use of AI (and everything else).

AI is a powerful tool, but it must be employed responsibly. We embed "human in the loop" validation at every decision tier, enforce traceable model provenance, and conduct continuous bias and safety testing. The same disciplined mindset we apply to weapons systems-rigorous testing, certification, and lifecycle support-governs our AI deployments, ensuring technology serves the warfighter without compromising ethics or security.

Bottom Line

From predictive maintenance that foresees failures weeks in advance to AIdriven regional sustainment networks that shrink logistics footprints, AI is turning battlefield logistics into a strategic advantage. The path forward is collaborative: partner with innovators who bring niche expertise, embrace open standards, and commit to responsible deployment.

The result will be a leaner, more responsive sustainment architecture that lets airmen worldwide focus on what they do best-fly, fix, and fight.