AI no longer lives at the edges of organizations. It now shapes how people are identified, evaluated, trained, protected, and governed. As these systems move deeper into enterprises and public institutions, design choices increasingly affect real lives and public trust.

While enterprises and governments work to become their own data and AI platforms, responsibility concentrates with those building and governing these systems. In this context, sovereignty shows up as control over use, accountability for outcomes, and the ability to maintain trust with the communities those systems touch. This conversation with Nate Yohannes explores how that trust is earned and sustained as AI becomes part of society’s most consequential decisions.

Key takeaways:

• Ethics must be embedded in product design: Responsible AI cannot be retrofitted. Ethical considerations must sit inside product teams, alongside engineering and deployment decisions as a core design constraint rather than a compliance exercise.
• Representation is a functional requirement, not a symbolic one: Who is at the table shapes how systems behave in the world. Excluding affected communities from design increases the risk of bias, failure, and loss of trust as AI systems scale.Scale amplifies unintended consequences:
  Many of the most damaging outcomes of technology were not intended. At global scale, intent matters less than foresight, governance, and the ability to anticipate downstream impact.
• Sovereignty requires accountability, not just capability: As enterprises and governments seek to become their own sovereign data and AI platforms, true sovereignty means owning outcomes, governing models and data over time, responding to failure, and maintaining trust with the communities affected by AI-driven decisions.