AI Risk Table: Governance, Security & Enterprise Exchange

AI Risk Table: Governance, Security & Enterprise Exchange

Enterprise AI adoption is moving exponentially faster than internal governance frameworks. Teams across every major vertical are currently confronting the same high-stakes operational bottlenecks:

Which internal department truly owns an autonomous AI workflow failure?

How do we audit third-party AI vendors whose model training policies remain opaque?

Where does human review remain mandatory before customer-facing deployment?

How do we enforce realistic data boundary policies without pushing employees into "Shadow AI"?

Hosted by Silicon Valley Innovation Network at The Forum inside Enterprise Coworking RiNo, the AI Risk Table is an engineered working exchange designed exclusively for the practitioners responsible for building, securing, auditing, and procuring enterprise AI systems.

There are no keynote speeches, no sponsored vendor demos, and no 45-minute stage panels. The entire evening is structured around closed-door, peer-level decision scenarios.

CONFIDENTIALITY & CHATHAM HOUSE RULE

To protect organizational security and foster candor:

• The Chatham House Rule Applies: Participants are free to use the insights, frameworks, and control strategies discussed during the evening, but neither the identity nor the company affiliation of any participant may be disclosed.
• Sanitized Operational Models: Attendees are explicitly instructed to speak in generalized enterprise architectures and hypothetical scenarios. Never bring or share proprietary code, non-public vulnerability reports, confidential customer data, or active regulatory disclosures.
• Non-Commercial Floor: This is a collaborative working session, not a sales opportunity. Product pitches, lead-generation tactics, and unsolicited software demonstrations are strictly prohibited.

THE 5-TRACK SYSTEM & PRE-ASSIGNED TABLE ROUTING

To avoid repetitive echo chambers, every participant is categorized across two operational axes:

1. Functional Role Track:

• BUILD: AI/ML Engineering, Product Architecture, Technical Implementation.
• SECURE: Cybersecurity, Threat Intelligence, Identity, Infrastructure Defense.
• GOVERN: Risk Management, Legal Operations, GRC, AI Ethics & Compliance.
• OPERATE: Enterprise IT, Systems Engineering, Day-to-Day Tool Ownership.
• BUY: Technology Procurement, Vendor Evaluation, Software Licensing.

2. Current Risk Priority:

POLICY | DATA HANDLING | VENDOR AUDIT | DEPLOYMENT | ACCESS CONTROL | INCIDENT RESPONSE

Zero-Friction Table Rotations:

Upon check-in, your credential badge displays your algorithmically pre-assigned routing code (e.g., Table 2-A → Table 5-C). When the rotation signal sounds, cross-functional groups reassemble in under 90 seconds with a balanced mix of engineering, security, and governance perspectives.

THE WORKING DECISION SCENARIOS

Each table receives curated, reality-tested enterprise case studies:

• Scenario A - The Shadow AI Expansion: Staff across multiple departments utilize unauthorized LLM extensions containing sensitive internal communications. Designing an enforceable tiered-access boundary.
• Scenario B - Third-Party AI Platform Ingestion: An enterprise SaaS vendor integrates third-party generative capabilities. Establishing security audit checklists, sub-processor verification, and contract indemnification.
• Scenario C - The Automated Decision Bottleneck: A mission-critical workflow is automated via an AI agent. Determining escalation triggers, human-in-the-loop audit gates, and override protocols.
• Scenario D - Customer-Facing Hallucination & Incident Ownership: A deployed enterprise model generates a critical contractual error for an external client. Defining incident command, cross-departmental documentation, and disclosure protocols.

DELIVERABLES: WHAT YOU TAKE BACK TO YOUR TEAM

The Enterprise AI Control Decision Canvas: A 1-page executive architecture mapping Trigger → Policy Rule → Technical Guardrail → Audit Frequency.

• The Vendor Security Evaluation Matrix: 15 non-negotiable assessment questions covering training data rights, telemetry retention, and model isolation.
• The 10 Boardroom Governance Questions: An executive briefing document outlining essential AI risk disclosures for leadership and audit committees.
• Post-Event Executive Summary Pack: A consolidated digest of anonymized peer recommendations and control models generated across all working tables.

PROGRAM TIMELINE (6:00 PM – 8:40 PM MST)

• 5:40 PM – 6:00 PM | Credential Check-In, Routing Badges & Staging

Arrive at The Forum, receive your functional role badge and pre-assigned table schedule, and grab artisan roast coffee or light refreshments.

• 6:00 PM – 6:10 PM | Operational Briefing & Chatham House Standards

Rules of engagement, floor mechanics, and framework introduction.

• 6:10 PM – 6:28 PM | Sprint 1: Internal Control Audit (18 Mins)

Facilitated introductions at assigned tables. Each participant outlines their organization's single hardest active AI boundary challenge.

• 6:28 PM – 6:50 PM | Sprint 2: Core Risk Scenario Deconstruction (22 Mins)

Working table deep-dive: dissecting the failure points of the assigned enterprise scenario.

• 6:50 PM – 7:05 PM | Cross-Functional Table Rotation & AI Risk Board Posting

Follow badge routing to your secondary table. Pin active governance questions to the central physical AI Risk Board.

• 7:05 PM – 7:30 PM | Sprint 3: Control Mechanism Design (25 Mins)

Debating viable technical and policy countermeasures with a newly mixed group of engineers, buyers, and CISOs.

• 7:30 PM – 7:55 PM | Facilitated Priority Matching Exchange

Targeted, organizer-facilitated connections based on role alignment and pre-event intake questionnaires.

• 7:55 PM – 8:25 PM | Open Peer Exchange & Board Review

Unstructured, high-signal conversations centered on specific peer solutions pinned to the Risk Board.

• 8:25 PM – 8:40 PM | Strategic Takeaways & Executive Wrap-Up

Consolidation of key control models, follow-up scheduling, and dismissal at 8:40 PM.