Lockheed Martin needed to unify many disconnected data systems so it could build enterprise AI safely and at scale, because fragmented tools and data silos were slowing both analytics and the next generation of employee-facing AI workflows.
Reported impact
Lockheed Martin simplified its data estate, improved answer accuracy in AI pilots, enabled a large engineering population to build on a secure AI foundation, and expanded AI into internal research, HR, and workflow automation use cases.
IBM helped Lockheed Martin collapse a sprawl of data management, analytics, and business-intelligence tools into a single AI-ready data platform built on watsonx.data, watsonx.data integration, and watsonx.data intelligence. Once the connected data environment was in place, the company stood up a secure AI Factory where 10,000 engineers can build and deploy large-scale AI solutions using IBM Granite models and open tooling rather than relying on isolated experiments. The same foundation also supports watsonx.governance and watsonx Orchestrate for agentic frameworks, virtual agents, and workflow automation, allowing employees to ask natural-language questions of enterprise data, use research copilots, and improve HR interactions through conversational AI. By improving data quality, automating catalog definitions, and centralizing the toolchain, Lockheed Martin turned AI from a collection of disconnected pilots into an operating capability that spans data access, employee support, and process automation across the enterprise.
Enterprise data from Lockheed Martin’s former lakes and analytic tools is integrated into the watsonx.data platform, cataloged and governed, then consumed by AI Factory engineers, Granite-powered applications, research copilots, HR chatbots, and agentic automation workflows.
“46 data systems and tools replaced with one integrated platform.”
“Accessible data fueled the Lockheed Martin AI Factory, a secure AI ecosystem where 10,000 engineers can build”
“Gen AI models built with watsonx have eliminated the need for specialized coding”
“IBM Granite ... accelerates application deployment within the AI Factory”
“rising from 45.45% to 56.8% with prompt engineering and to 66.0% with query optimization.”
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Traceability
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