Build vs. Buy vs. AI
Navigating Threat Modeling in the AI Era
Unsure what AI threat modeling route to take?
The Challenge: AI and cloud-native development are accelerating how systems are built—but also making them harder to secure. Traditional build-versus-buy decisions for threat modeling are no longer enough. Teams now face a third option: leveraging AI directly. Each approach; building internal tools, using AI-only workflows, or buying a purpose-built platform, comes with unique tradeoffs in accuracy, governance, repeatability, and long-term sustainability. Choosing the wrong path can create security gaps, operational overhead, and misaligned workflows.
The Solution: This whitepaper examines the three approaches to threat modeling in the AI era, helping organizations make informed decisions that scale with evolving architectures. Learn when building internal tools works, how AI can accelerate early exploration, and why a purpose-built platform may provide consistency, governance, and collaboration across teams. Discover practical strategies for integrating threat modeling effectively while maintaining security, accuracy, and traceability.
Who needs this guide:
- Security teams managing risk across distributed and cloud-native systems
- CISOs and security leaders aligning programs with rapid development cycles
- Architects and engineering leaders exploring AI-driven or internal tooling options
- Organizations seeking scalable, repeatable, and auditable threat modeling practices
What’s inside:
- A breakdown of Build, AI-only, and Buy approaches and their tradeoffs
- Guidance on when each approach makes sense based on team size, scale, and architecture complexity
- Insights on AI’s role in prototyping, ideation, and early-stage threat modeling
- Considerations for accuracy, governance, and sustainability in modern security programs