Visibility without suffocation
Useful experimentation often starts below formal governance. Speed and initiative can also create data leakage, maintenance debt, unclear accountability, and systems the organization cannot later inspect.
Governance collection
AI Governance That Survives Contact With Tuesday
Six conversations about policy, shadow use, agent boundaries, contestability, and whether a human can still meaningfully stop the system.
The question beneath the question
Can someone still inspect, interrupt, and overrule the system when it matters?
Governance becomes real when AI enters a workflow on an ordinary Tuesday: employees use tools before policy catches up, agents cross organizational boundaries, predictions affect people who cannot see the model, and high-stakes decisions arrive faster than the human review process. The useful question is not whether a policy exists. It is whether the organization can see what the system is doing, understand its evidence, contest its judgment, and stop it.
The listening path
6 conversations. One unresolved question.
01Listen →02Listen →03Listen →04Listen →05Listen →06Listen →
Krista Snelling
AI Adoption Case Study Masterclass, w/ WCCB’s Krista Snelling & Matthew March
Open with governance as operating practice: policy, employee-led use-case discovery, peer learning, measurement, and human exception review rather than abstract principles.
Rick Caccia
Why “Shadow AI” is the Biggest Business AI Story No One is Talking About, w/ Rick Caccia
Show the Tuesday-morning problem directly: useful tools appear ahead of formal approval, creating simultaneous questions about visibility, sensitive data, compliance, cost, and enablement.
Babak Hodjat
Deep-Dive Into Agentic Workflows, w/ Cognizant’s Head of AI
Translate policy into system design through constrained scopes, confidence thresholds, redundancy, grounded sources, escalation, and separation between reasoning and retrieval.
Dan Botero
The Wild Story of “Octavius Fabrius,” the World’s First AI Agent to (Kind of) Land a Job, w/ Dan Botero
Use a vivid boundary case involving persistent memory, identity, payments, platform participation, and cross-context behavior to test how quickly helpful autonomy can outrun intended authority.
Carissa Véliz
When AI Forecasts Become Self-Fulfilling (and Who This Hurts), w/ Carissa Véliz
Add the contestability test: when a prediction affects opportunity, governance must include privacy, resilience, and a meaningful way to challenge the system’s judgment.
Ankit Panda & Andrew Reddie
The Real Risks of AI and Nuclear War, w/ Ankit Panda & Andrew Reddie
Close at the highest stakes by forcing operational questions about evidence, automation bias, crisis timing, testing, and exactly when a human can veto an AI-supported decision.
Points of tension
What the conversations refuse to simplify.
Human oversight with teeth
A human-in-the-loop matters only when that person has evidence, time, authority, and a real ability to interrupt or overrule the system. Otherwise the approval is ceremonial.
Capability versus contestability
More autonomy and integrated context can increase performance while making sources, boundaries, failures, and affected people harder to see, challenge, and hold accountable.
Carry it forward
Design the override before the emergency.
Operational governance should make the system legible before asking anyone to trust it: known boundaries, inspectable evidence, explicit escalation, revocable authority, meaningful contestability, and a human veto that still works when time is short and pressure is high.