Leidos, a major defense and intelligence contractor with 47,000 employees, has made AI governance the core foundation for its AI strategy. Rather than treating governance as a necessary brake on innovation, the company partnered with Trustible to build a centralized, automated system that delivers speed, clarity, and control at enterprise scale.
Before the partnership, Leidos faced the same challenge many large organizations encounter: governance processes designed for smaller portfolios could not keep pace with growing AI demand. Reviews took weeks, documentation lived in silos, and central teams struggled to maintain visibility into how AI was actually being used across business units. As the company’s AI portfolio expanded into mission-critical defense, intelligence, civil, and health programs, these fragmented processes became a real drag on deployment speed.
Trustible provided the platform and expertise to change that. Leidos now operates a single system of record that gives governance teams clear visibility into every AI use case, automates risk tiering, and routes reviews to the right stakeholders based on impact. Low-risk use cases move in hours or even minutes, while higher-risk systems receive the deeper scrutiny they require. The approach has already compressed initial governance intake timelines dramatically while maintaining rigorous oversight and auditability.
This is more than a tooling project. Leidos is deliberately building governance that scales with the business and prepares the organization for the next phase of AI — agentic systems that act autonomously. The partnership shows how a large, highly regulated enterprise can turn governance from a source of friction into a genuine force multiplier for innovation.
“The scale of our organization requires a complementary scale in AI Governance. We need to move in lockstep with the business, no matter how many AI use cases that entails. Trustible allows us to streamline our intake and management using a range of tools like batch processing, pre-built risk cards, and more. These are major unlocks for us that get more effective the more we scale“
— Geoff Schaefer, VP of AI Strategy & Governance at Leidos.
Key Terms
AI Governance Platform — Centralized system that provides visibility, risk assessment, workflow automation, and auditability for AI use cases at enterprise scale.
Risk Intelligence — Automated risk tiering and mitigation recommendations based on system complexity and impact.
Agentic AI Readiness — Preparing governance processes for autonomous AI agents that can take independent actions rather than just generate outputs.
Centralized System of Record — Single source of truth for all AI use cases, replacing fragmented spreadsheets and email threads.
Conditions Driving This Change
Large organizations like Leidos are under intense pressure to scale AI while operating in highly regulated, mission-critical environments.
The volume of AI use cases is growing rapidly across business units, making fragmented, manual review processes unsustainable.
Mission-critical programs in defense, intelligence, and healthcare demand both speed and rigorous oversight, creating a tension that traditional governance could not resolve.
Documentation and risk decisions previously lived in silos, making enterprise-wide visibility and pattern recognition nearly impossible.
Regulatory expectations for AI accountability continue to tighten, requiring clear audit trails and demonstrable controls.
The shift toward agentic AI systems means governance must evolve from reviewing static models to overseeing autonomous agents that take real actions.
Internal teams need to move at the speed of the business without sacrificing control or compliance.
Legacy processes that relied on spreadsheets, email threads, and manual routing simply could not scale to the number of use cases Leidos was managing.
Leadership recognized that governance done right could become a strategic advantage rather than a bottleneck.
These conditions created the exact need for a modern, automated governance platform that could deliver both speed and control.
What Governance Looked Like Before
Before partnering with Trustible, Leidos managed AI governance through fragmented, manual processes. Each business unit handled its own documentation and reviews, leading to duplicate work and inconsistent standards. Central governance teams spent significant time chasing spreadsheets and email threads just to understand what AI systems existed and where they were deployed.
Reviews routinely took weeks, even for relatively straightforward use cases. There was limited visibility into risk patterns across the enterprise, making it difficult to apply consistent controls or learn from past decisions. Documentation lived in silos, so leaders lacked a single source of truth when they needed to assess overall AI exposure or prepare for audits.
The existing approach worked reasonably well when the AI portfolio was smaller, but it began to break down as the number of use cases increased. Teams faced a constant trade-off between moving fast to meet business needs and maintaining the rigorous oversight required in regulated environments. Governance felt like a brake on innovation rather than an enabler, even though everyone understood its importance.
What’s Changing Now
Leidos has fundamentally changed how it approaches AI governance by implementing Trustible as its centralized platform. The company now operates a single system of record that provides complete visibility into every AI use case across the enterprise. Governance teams can see exactly what systems exist, where they are deployed, and how risk decisions are being made without chasing down scattered documents.
The platform automates risk tiering, surfaces relevant mitigations, and routes reviews to the right stakeholders based on impact. Low-risk use cases now move through intake in hours or even minutes, while higher-risk systems receive the deeper scrutiny they require from a senior AI Governance Board. All decisions are captured with clear audit trails, creating transparency and accountability at scale.
Trustible’s tools, including batch processing and pre-built risk cards, have become more effective the larger the program grows. The partnership also positioned Leidos to prepare for agentic AI by embedding governance directly into autonomous workflows. Policy management and AI frameworks translate regulatory requirements into living controls that can evolve as rules change. Governance is no longer a separate step that slows things down — it is now integrated into how the company builds and deploys AI.
Our Take
AI Governance Take
Leidos has shown that strong AI governance does not have to slow innovation. By partnering with Trustible, the company created a scalable, automated system that delivers enterprise visibility, compresses review timelines, and prepares the organization for agentic AI — all while maintaining rigorous oversight.
This case study proves that governance, when designed with scale in mind, becomes a genuine competitive advantage rather than a bottleneck. Organizations that treat governance as foundational infrastructure will be able to deploy AI faster and more confidently than those that treat it as an afterthought.
GAIG tracks platforms in the AI Governance Platforms, AI Risk & Controls, and AI Governance Frameworks categories that help large enterprises achieve this level of visibility, automation, and scalability.
