Enterprise AI Deployment & Governance

For engineering leaders and IT: deploying AI engineering platforms in your organization — SaaS vs. self-hosted, SSO and RBAC, organization isolation, audit trails, compliance regimes, and a governance model that survives audit.

Private cohorts & on-site
Format: 2-day (8:30 a.m.–4:30 p.m.)
Level: Senior/Management
Location: Scheduled on demand · on-site at your facility or a regional venue
Date(s): Not yet scheduled for open enrollment. Get notified when it is, or book it privately for your team.
Includes: Certificate of Completion · printed slide binder · take-home reference text

Get notified when this course is scheduled

One email when dates are set. Or skip the wait: run it as a private cohort, on-site at your plant.

Talk to us about a private cohort
  • One email, no sequence
  • Never shared
  • Reply within one business day

Faculty

Faculty details for this seminar will be announced with the full schedule.

Fees

Early: $1,895 (payment 4+ weeks ahead)
Standard: $2,095 (check/ACH) · $2,165 (card)

Group discount: $200 off per attendee for 3+ from the same organization.

Also Available

  • Corporate on-site delivery at your facility
  • Private cohort sessions
  • Digital curriculum licensing

Seminar Overview

AI engineering tooling fails in enterprises for governance reasons, not technical ones. This course is the deployment playbook: choosing between SaaS, self-hosted, and private cloud; wiring enterprise identity (SSO via OIDC/SAML with Okta, Azure, Google); role-based access; multi-tenant organization isolation; data residency; and the audit and compliance reporting regulators and customers expect.

Day two builds the operating model: usage policy for engineering AI, verification gates, cost and capacity management across model providers (including local deployment options for sensitive work), and the compliance ledger as evidence infrastructure. Executives leave with a deployment decision framework; IT leaves with the technical wiring plan.

Ideal Learner

  • VPs, directors, and chief engineers owning AI adoption decisions
  • IT and security leaders responsible for deployment and data governance
  • Quality and compliance officers in regulated industries
  • Program managers running digital-engineering initiatives

Learning Objectives

  • Choose the right deployment model: SaaS, self-hosted, or private cloud
  • Wire enterprise SSO, 2FA, and role-based access correctly
  • Design organization isolation and data-governance policy
  • Stand up audit trails and the compliance ledger as evidence
  • Build the governance model: policy, verification gates, and review cadence

Consulting Sessions

Seminar attendees can sign up for individual consulting sessions with the instructor. Sessions are free for registered attendees, first-come first-served — sign up when registering by calling 248-539-0473 or during the seminar.

Seminar Outline

  • SaaS vs. self-hosted vs. private cloud — decision factors
  • Data residency and customer-NDA requirements
  • Multi-tenant organization isolation in practice
  • Model routing: cloud providers and local deployment
  • SSO: OIDC, SAML, Okta, Azure, Google
  • 2FA and role-based access design
  • User lifecycle and offboarding
  • Audit trail configuration and review
  • Usage policy for engineering AI
  • Verification gates and sign-off chains
  • GDPR export/erase and restrictive security headers
  • The compliance ledger as evidence infrastructure
  • Pilot design and expansion criteria
  • Cost and capacity management
  • Training sequencing with the Academy tracks
  • Executive dashboard and reporting

More in Track K — Platform, AI & IT Enablement

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