EDC CIRCLE · INTELLIGENCE EXCHANGE

Where senior data leaders become the architects of trusted, board-scale AI.

EDC Circle is a limited, invitation-only program for senior leaders responsible for data governance, AI risk and enterprise accountability. Through private masterclasses, peer roundtables, simulations and practical working labs, participants build a governance blueprint they can defend and lead.

Up to 10 leaders · Private monthly sessions · NDA and no-recording standard

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AI is no longer a project. It is a leadership mandate.

Policies, committees and model documents do not prove that governance works under pressure. Leaders need to know where accountability is real, where evidence is weak, how vendor AI changes the risk surface and which gaps should be addressed first. EDC Circle is built to convert that ambiguity into a board-ready plan.

Who it is for

CIOs, CTOs, CDAOs and CDOs owning AI or data risk
Heads and VPs of data governance, quality, lineage or AI governance
Model risk, vendor risk, compliance and technology-risk leaders
Transformation leaders accountable for enterprise AI operating models

Not designed for

General-interest learners
Junior practitioners without enterprise responsibility
Vendors seeking sales access
Participants unwilling to work through confidential operating detail

By the end, answer the questions your board will ask.

Participants should be able to explain:

Which critical data and AI risks are genuinely controlled
Where governance depends on assumptions rather than evidence
Who owns decisions when data, AI or vendors fail
Which weaknesses create the greatest enterprise consequence
Which actions should be funded first
How governance can accelerate trusted AI adoption

Primary deliverables

Enterprise Data and AI Governance Blueprint
Confidential peer maturity comparison
Board-ready gap assessment
Prioritized 90-day remediation plan
Decision-rights and accountability map
Practical diagnostics, question sets and checklists

Program modules

Data Governance Reality Check

Distinguish documented policy from controls that work in practice. Identify hidden gaps across ownership, quality, lineage, access and evidence, then build a prioritized map of the organization's consequential unknowns.

AI Vendor & Third-Party Data Risk Lab

Evaluate how AI-enabled vendors access, retain, reuse and govern enterprise data. Test whether claims and documentation provide defensible evidence, and design practical approval and monitoring conditions.

Lineage, Quality & Ownership Failure Simulation

Trace a simulated failure across systems, vendors, models and decisions. Expose controls that pass while the business outcome fails, and clarify escalation paths and decision rights under pressure.

Board-Ready Data & AI Accountability War Game

Translate discovered gaps into a clear executive risk and investment narrative. Defend governance decisions before a simulated board and leave with a 90-day action plan and forward blueprint.

Format

Four to six monthly sessions
Three-hour in-person working sessions, with optional virtual preparation
Up to 10 qualified participants
Private cohort and member-only materials
No media or recordings
NDA and participation standard
Limited between-session validation and peer exchange

Faculty and mentors

Faculty and mentors are senior operators with direct accountability for data governance, AI risk and enterprise decision-making. Names are confirmed with the individual before they appear here, and affiliation does not imply employer sponsorship.

Investment and cohort details

Program investment, tax treatment, refund and transfer rules and confirmed cohort dates are provided directly to qualified candidates once verified. Travel and accommodation are not included. Enterprise-sponsored groups follow a separate team participation route.

Discuss Enterprise Sponsorship

Turn ambiguous AI pressure into a strategy you can defend.

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Cohort dates, selection timeline and participation terms are confirmed with each candidate before any commitment is requested.