Full Report
As AI, model-based systems engineering and digital thread strategies evolve, they're transforming how organizations define and manage requirements across the product lifecycle.
Analysis Summary
# Main Topic
The shift in requirements management driven by the adoption of Artificial Intelligence (AI), model-based systems engineering (MBSE), and Digital Thread strategies in product lifecycle management.
## Key Points
- Requirements are evolving from static deliverables into **living, evolving data** that actively drives innovation, quality, and compliance across the product lifecycle.
- Adopting this new mindset (treating requirements as dynamic data) is critical for organizations seeking to manage rising complexity and seize new opportunities.
- The transformation involves leveraging AI and MBSE to define and manage requirements throughout the entire product lifecycle, supported by the Digital Thread concept.
## Threat Actors
- Not Applicable. (The provided text focuses on technological strategy and industry transformation, not malicious threat actors or campaigns.)
## TTPs
- Not Applicable. (The context describes a strategic technological evolution, not adversarial techniques.)
## Affected Systems
- Product Lifecycle Management (PLM) systems.
- Requirements definition and management tools and processes.
- Systems utilizing Model-Based Systems Engineering (MBSE).
- Digital Thread infrastructure utilized for configuration management and systems integration.
## Mitigations
- Organizations must adopt a **new mindset** regarding requirements, moving away from static deliverables.
- Treat requirements as **living, evolving data**.
- Implement strategies encompassing AI integration and robust Digital Thread deployment to better manage complexity and ensure compliance.
## Conclusion
The modernization of requirements management through AI and the Digital Thread represents a strategic imperative for industrial companies. Success hinges on organizational acceptance of requirements as dynamic, integrated data assets rather than fixed documentation, which positions them better to handle advanced engineering complexities.