Enterprise GenAI Deployment: From Internal Pitch to Production-Approved Ship
“Build AI tools your enterprise will actually let you ship.”
Architect, secure, and justify internal GenAI tools that pass your security review board, survive a data governance audit, and answer the CFO's ROI question
One-time · Lifetime access · Certificate included
- ✓6 modules of content
- ✓36 concept slides
- ✓18 practical exercises
- ✓24 quiz questions
- ✓Capstone project
- ✓LearnAspire certificate
Learning Outcomes
What you'll learn
The day after you finish
The day after completing this course, you will walk into your security review board or transformation steering committee with a working internal GenAI tool, a defensible architecture diagram, an IAM integration plan, a completed compliance decision log, and a three-slide ROI justification — and you will be able to answer the hard questions without stalling.
Who this is for
- Senior IT architects leading AI adoption inside regulated enterprise environments with existing IAM, data classification, and change management frameworks
- Digital transformation leads who have completed AI proof-of-concepts and are blocked at the security review, procurement, or executive justification stage
- Senior developers and technical leads embedded in enterprise delivery teams who need to build LLM-powered internal tools that meet audit, access control, and data residency requirements
Prerequisites
- Hands-on experience calling LLM APIs (OpenAI, Azure OpenAI, or equivalent) and building at least one prompt-driven application — this course does not explain what an LLM is
- Working knowledge of enterprise IAM concepts including OAuth 2.0 / OIDC flows, role-based access control, and either Azure AD or Okta administration — token scopes and group claims are not introduced here
- Familiarity with your organisation's data classification tiers, a cloud platform's networking primitives (VNet, private endpoints, or equivalent), and basic containerised deployment — you should have shipped something to a non-production enterprise environment before starting this course
Curriculum
6 modules · full breakdown
🤖 Part of: AI Engineering Path
Capstone Project
Production-Ready Internal GenAI Tool Package
Learners select a real internal use case from their own organisation — document Q&A over classified internal knowledge bases, AI-assisted ITSM triage, contract review acceleration, or equivalent — and produce a complete deployment-ready package. This includes: a working tool prototype with IAM integration wired to their identity provider, scoped RBAC on outputs, and a structured audit log; a system architecture diagram annotated with trust boundaries, data classification labels, and network egress controls; a deployment pattern decision log documenting the managed API vs. self-hosted vs. open-weight trade-off against their specific data residency and procurement constraints; a data governance and compliance attestation covering residency, retention, model training data rights, and breach notification obligations; and a three-slide executive presentation with quantified ROI, risk framing, and pre-answered CISO and CFO objections. The tool must be deployable into the learner's own enterprise environment without additional architectural rework.
What you'll deliver
A ZIP package containing: (1) annotated architecture diagram, (2) IAM integration specification with RBAC matrix, (3) working prototype code with audit logging instrumentation, (4) completed compliance decision log using the course template, and (5) the three-slide executive briefing deck — all scoped to a real internal use case from the learner's organisation