France Hoang, a former White House Counsel, Army Special Forces veteran, and now the co-founder and CEO of Boodlebox, brings a unique perspective forged by a lifetime of service and leadership, now focused on one of education's most urgent questions: How do we get the human-AI relationship right? They dive into why the traditional educational model—information, struggle, assessment—is fundamentally disrupted by AI, and the dangers of students outsourcing their critical thinking. France outlines the three pillars of being "AI ready" and explains why educators are more important than ever, not less. He shares powerful stories from campuses using Boodlebox to create transparent, ethical AI collaborations, resulting in zero academic integrity cases and dramatically improved student comfort with AI. For any leader wondering how to move from simply providing AI access to truly transforming teaching and learning, this conversation is a masterclass in strategy, ethics, and human-centric innovation.   Key Takeaways The Goal is a Partnership, Not Just a Tool: AI in education should aim to create a human-AI partnership that extends and amplifies human potential, allowing students and professionals to spend 80% of their time on high-value creative and critical work, not administrative drudgery. Educators Are More Important Than Ever: In the age of AI, the educator's role is not diminished but elevated. They are the essential source for building domain expertise (being better than the AI), teaching responsible AI enablement, and fostering the durable human skills (critical thinking, creativity, collaboration) that AI cannot replicate. AI Readiness is a People Problem, Not a Platform Problem: True institutional AI readiness is not about buying software or providing access (students already have that). It's a cultural and pedagogical transformation that requires partnership, piloting, peer-to-peer learning, and a multi-year rollout focused on integrating AI thoughtfully into teaching and learning. Reintroduce "Productive Struggle": Since AI tools are designed for ease and productivity, educators must intentionally design learning environments that reintroduce challenge. Platforms like Boodlebox allow for guardrails and transparency, letting teachers see the process of how students use AI as a thought partner, not just the final product. Start with Pilots and Use Cases, Not Campus-Wide Rollouts: The most successful AI adoption starts small. Identify a high-impact use case, partner with a group of pioneering faculty, and let success grow organically through peer influence. Avoid the "solution in search of a problem" approach of broad, untargeted rollouts. Measure Human Impact, Not Just Usage: While metrics like logins are important, true success should be measured by qualitative human outcomes aligned with the institution's mission. This includes changes in student confidence, job interview success stories, ethical AI use, and the quality of collaborative problem-solving. Equitable Access is a Foundational Concern: There is a real risk of a "digital divide" where students who can pay for premium AI tools get better outcomes. Institutions have a responsibility to provide equitable, high-quality AI access to all students to ensure opportunity is based on merit and work, not on financial resources. The Future is Personalized, Differentiated, and Portable: AI enables a future where learning is personalized at scale (like a TA for every student), differentiated by discipline (e.g., AI simulations for history, data analysis for chemistry), and portable—allowing students to take a curated toolkit of their AI-augmented academic work with them into their careers as a lifelong learning resource....