Risk Landscape Briefing
A concise opening view of AI security exposure, policy pressure, vendor risk, and executive accountability.
Friday 06 Nov 2026 | 1:00 PM-2:30 PM Central
AI Security, Governance, and Trust
Cohort: Security and RiskNine executives clarify the security controls, governance model, policy boundaries, and trust signals required before AI expands across the enterprise.
90Minutes from 1:00 PM to 2:30 PM Central
08Moderated governance questions
09Executives in the room
01Invite path into the cohort
Operating format
A working room for leaders protecting trust while AI adoption accelerates.
The session is designed for executives who need practical governance, security clarity, and decision rights without freezing useful AI work.
Governance Operating Exchange
Moderated prompts let leaders compare policies, controls, review gates, incident response, and trust-building mechanisms.
Controls and Cohort Path
Qualified participants identify governance questions for deeper research, sponsor fit, and 2027 summit programming.
The room
Where security, governance, and business speed have to meet.
The discussion does not treat governance as paperwork. It asks what leaders need to know, approve, monitor, and communicate so employees, customers, boards, and regulators can trust AI-enabled work.
- Audience
- CISOs, CIOs, legal leaders, risk leaders, compliance leaders, data leaders, and executives accountable for secure AI adoption.
- Access
- Invitation-only, capped at nine executive participants for a moderated exchange rather than broadcast attendance.
- Outcome
- A clearer map of the controls and governance decisions needed to let AI scale responsibly.
Featured lineup
Featured guests, authors, and partners for this conversation.
When a featured registration includes an approved bio photo, it appears here from the live registration profile for this event.
Moderated questions
The governance questions leaders need answered before AI expands.
Each question is built to expose practical controls, policy gaps, and trust decisions rather than abstract risk language.
What AI use is actually happening?
How do leaders discover sanctioned, unsanctioned, embedded, vendor-provided, and employee-created AI activity across the organization?
Which AI risks deserve executive escalation?
What should rise to the board, the C-suite, legal, security, or risk committees before a use case moves forward?
How do we classify AI use by risk?
What separates low-risk productivity support from regulated, customer-impacting, employee-impacting, or mission-critical AI work?
What should vendors have to prove?
Which security, privacy, data-use, model, audit, indemnity, and resilience questions belong in AI vendor review?
Where does human review become mandatory?
Which AI outputs require approval, sampling, escalation, or documented human accountability before use?
How do we prepare for AI incidents?
What does incident response look like for data leakage, harmful output, prompt injection, model failure, or vendor disruption?
How do we build trust with employees and customers?
What should leaders disclose, document, explain, or prohibit so people understand when AI is being used and why?
How do we govern without freezing adoption?
What operating model lets useful AI move quickly while high-risk work receives appropriate review and control?
Run of show
A direct path from risk visibility to decision rights.
The session compresses security framing, peer comparison, and next-step qualification into one focused executive hour.
Risk baseline
The moderator frames the AI control questions leaders need to settle.
Governance diagnostic
Each leader compares policies, controls, vendor review, and trust practices.
Controls roadmap
Participants identify which governance issues deserve deeper cohort work.
Invitation only
For executives ready to make AI trustworthy enough to scale.
Access is curated by the MOJO AI Summits team. The November 6 room is intentionally small so leaders can speak plainly about exposure, control, and trust.