As organizations embed AI deeper into everyday operations, a critical question is moving to the forefront: Who controls the knowledge and intelligence created along the way?

In the Forbes article “We Are Renting Our Brains, And Nobody Reads the Lease,” technology writer Jason Snyder examines the growing risks of AI and SaaS vendor lock-in—from model deprecation and data portability to the loss of institutional knowledge accumulated inside systems an organization ultimately does not control.

Career Highways CEO Liz Eversoll contributes an important distinction to that conversation: organizations need both portability and explainability. They need the ability to act on their own data and take it with them, but they also need to understand and trust the decisions AI systems make while that data is being used.

That distinction becomes particularly important in workforce technology. Skills data represents both an organizational asset and an individual’s professional identity. When AI influences decisions about skills, roles, mobility, and opportunity, organizations need more than an answer—they need governance, traceability, and the ability to understand how that answer was reached. As Liz explains in the article, an AI system may be capable of making a decision without those foundations, but it may not be capable of defending it.

The Forbes article explores why control, portability, explainability, and trust are quickly becoming fundamental requirements for enterprise AI.