Module 1
AI governance architecture
Define accountabilities, review paths, controls, and escalation structures that survive contact with delivery teams.
Architect Track
AI governance programs for people setting rules, controls, and institutional operating logic
An AI governance and strategy program for CAIOs, risk leaders, compliance teams, and policy stakeholders who need standards-aligned controls, strategy, and sovereign AI judgment.
Audience
CAIOs, risk leaders, compliance teams, policy architects, regulators
Format
Live seminars, governance labs, framework-led sessions
Built for specific operators, not for a generic AI audience
Every track is scoped around a role, a decision context, and the kind of work participants need to leave ready for.
Interprets AI standards in operating terms, not just legal summaries
Covers EU AI Act, NIST AI RMF, ISO/IEC 42001, and sovereign AI patterns
Useful for enterprise, public-sector, and ecosystem-level AI governance
Bridges strategy, risk, architecture, and policy
What participants actually work through
Module 2
AI standards and framework interpretation
Translate the EU AI Act, NIST AI RMF, and ISO/IEC 42001 into operating decisions and organization design.
Module 3
Sovereign AI and institutional control
Examine data residency, policy autonomy, stack control, and national or sectoral AI capability decisions.
Module 4
Governance strategy and assurance
Build a more coherent approach to governance maturity, internal assurance, and long-term AI readiness.
You're a fit if...
Leaders responsible for governance, AI policy, risk, or sovereign capability
Institutions building control frameworks around growing AI adoption
CAIO-adjacent teams that need practical standards interpretation
This is not for you if...
Builders looking primarily for coding and deployment labs
Organizations expecting governance without cross-functional operating change
Teams that only want a legal summary without implementation depth
How the track runs in practice
The outcome is not just attendance. Each track is designed to change decision quality, engineering capability, or institutional readiness.
Framework-led, operator-taught
The program is grounded in current standards and policy regimes, but taught by practitioners working through implementation tradeoffs.
Applied governance labs
Cohorts work through governance cases, organizational structures, and assurance design rather than abstract policy debate.
Institutional governance outputs
Participants leave with clearer control logic, governance priorities, and next-step design decisions.
What this track is meant to change
Outcome 1
A clearer institutional AI governance model
Outcome 2
Better standards interpretation tied to operating reality
Outcome 3
Stronger alignment across strategy, delivery, and policy functions
Practitioner faculty across leadership, build, and governance
Faculty Director
Dr. Jagreet Kaur Gill
AI and Decision Intelligence · Agentic Enterprise Strategy
Leads the academic direction of XDFE with a focus on translating enterprise AI ambition into operating models, decision systems, and production strategy.
Builder Track Lead
Suryakant Tomar
Agentic AI · GenAI Engineering · Multi-Agent Systems
Works at the engineering edge of applied AI systems, helping builders move from experimentation into dependable agentic and multi-agent delivery.
Architect Track Lead
Chandan Gaur
AI Governance · EU AI Act · Sovereign AI Policy
Guides governance, standards, and sovereign AI thinking for institutions that need rigorous strategy, compliance alignment, and long-term operating control.
Leadership Track Lead
Riya Khurana
Applied AI Literacy · Adaptive Leadership · Responsible AI
Helps senior leaders build AI fluency, responsible deployment judgment, and the confidence to lead transformation without relying on abstract theory.
Explore the adjacent pathways in the academy
If architect track is the right fit, start the conversation now
We can route you into the right cohort, advisor workflow, or admissions path based on your role, region, and goals.