“The Microsoft Fabric implementation program gave our data engineering team a structured path from legacy pipelines to a modern lakehouse architecture.”
Enterprise Program Brief
AI Business Analysis and Workflow Design
Define an implementable AI-enabled workflow with measurable acceptance and control requirements. Proposed instructor-led duration; delivery subject to environment and lab validation.
VNode ITeSPractitioner / specialist
Download Program Brief (PDF)Program Snapshot
Engagement scoped to cohort
Duration32 hours
FormatPrivate cohort
LevelPractitioner / specialist
Course CodeA01
- MCT-led delivery
- Private cohort / virtual ILT
- Typical response: 1 business day
Scoping call typically scheduled within one business day
VNode ITeS delivers AI Business Analysis and Workflow Design as an MCT-led VNode ITeS program for Business analysts, Functional consultants, Process owners. Typical duration is 32 hours (Private cohort). Delivery stays scoped to how your teams will actually use the platform after the room empties. Private cohorts can shift emphasis by role mix, workspace or repo constraints, and rollout timing.
Audience Profile
Built for these roles
Business analysts, Functional consultants, Process owners
- Tailored Team Delivery
Overview
Executive overview
Define an implementable AI-enabled workflow with measurable acceptance and control requirements.
Environment and licensing
Spreadsheet or document editor Synthetic scenario pack Approved AI interface only where used; paper-based comparison available Delivery depends on environment and lab validation. This outline does not include step-by-step lab instructions.
Prerequisites
- AI and discovery fundamentals
- AI and Generative AI Foundations, or equivalent demonstrable experience
- Business Process Discovery and Requirements, or equivalent demonstrable experience
Program Outcomes
Capabilities your teams will gain
- Design the AI-enabled workflow and implementation backlog
- Link normal, ambiguous and failure scenarios to acceptance
- Specify information boundaries and consequential-action approvals
- Present a stakeholder-ready requirements and decision pack
Enterprise Delivery
Private cohort delivery
VNode-designed, vendor-aligned instructor-led program. Scope role mix, delivery format, and rollout goals for your cohort.
Curriculum
Curriculum roadmap
Proposed instructor-led duration; delivery subject to environment and lab validation.
- AI opportunity and workflow diagnosis
- AI requirements and information contracts
- Controls and measurable acceptance
- Business analysis capstone
1Module 1 · 8 hours
AI opportunity and workflow diagnosis
+
Module 1 · 8 hours
AI opportunity and workflow diagnosis
Compare alternative workflow designs and justify where AI is useful.
Task suitability
- Decompose the workflow into decisions, information and actions
- Choose which steps need probabilistic assistance
Baseline
- Measure time, error and exception baselines
- Record where measurement is unreliable
Deterministic alternatives
- Compare rules, search, workflow and agent alternatives
- Explain why AI is justified for each selected step
Stakeholder impact
- Map effects on users and process owners
- Identify new failure modes and review responsibilities
Concept and design 4h · applied exercise 3h · review 1h. Included within module duration; no extra hours. Refine during delivery planning without silently changing published course hours.
Applied exercise: AI opportunity and workflow diagnosis
Compare alternative workflow designs and justify where AI is useful.
Expected output. AI suitability and workflow analysis
Acceptance. The proposal explains which steps change and how improvement will be measured.
2Module 2 · 8 hours
AI requirements and information contracts
+
Module 2 · 8 hours
AI requirements and information contracts
Write requirements for normal, ambiguous, unsafe and failed interactions.
Inputs and outputs
- Specify required inputs and output contracts
- Define how incomplete or conflicting inputs are handled
Grounding
- Identify grounding sources and content owners
- Set freshness and permission requirements
Uncertainty
- Represent uncertain responses and no-answer outcomes
- Avoid accepting fluent unsupported answers
Exceptions and escalation
- Define tool errors and escalation paths
- Document exceptions separately from the normal journey
Concept and design 4h · applied exercise 3h · review 1h. Included within module duration; no extra hours. Refine during delivery planning without silently changing published course hours.
Applied exercise: AI requirements and information contracts
Write requirements for normal, ambiguous, unsafe and failed interactions.
Expected output. AI requirements and exception catalogue
Acceptance. The requirements cover ambiguity, information gaps, unsafe requests and failed actions.
3Module 3 · 8 hours
Controls and measurable acceptance
+
Module 3 · 8 hours
Controls and measurable acceptance
Define acceptance tests and ownership for proposed AI actions.
Human approval
- Define which actions require approval
- Specify confirmation and accountability
Data boundaries
- Map sensitive data and access boundaries
- Identify the enforcing system and owner
Task success
- Define task success and measurable acceptance
- Separate model quality from workflow completion
Evaluation cases
- Create normal, negative and adversarial examples
- Link each test to a requirement
Concept and design 4h · applied exercise 3h · review 1h. Included within module duration; no extra hours. Refine during delivery planning without silently changing published course hours.
Applied exercise: Controls and measurable acceptance
Define acceptance tests and ownership for proposed AI actions.
Expected output. Acceptance and control specification
Acceptance. Every important requirement has observable acceptance evidence and a responsible owner.
4Module 4 · 8 hours
Business analysis capstone
+
Module 4 · 8 hours
Business analysis capstone
Present a complete delivery-ready workflow pack and respond to stakeholder objections.
Prototype review
- Review a bounded prototype against requirements
- Record unmet criteria rather than adding hidden scope
Prioritisation
- Prioritise the implementation backlog
- Map dependencies and review gates
Implementation backlog
- Present workflow and exception decisions to stakeholders
- Respond to a changed business requirement
Stakeholder playback
- Provide ownership, benefits and risk assumptions
- Separate approved scope from future opportunities
Concept and design 2h · applied exercise 4h · review 2h. Included within module duration; no extra hours. Refine during delivery planning without silently changing published course hours.
Capstone: Business analysis capstone
Present a complete delivery-ready workflow pack and respond to stakeholder objections.
Expected output. Assessed AI workflow design pack
Acceptance. The final pack is actionable for engineers and supports stakeholder acceptance.
Capstone
Present a complete delivery-ready workflow pack and respond to stakeholder objections. Assessed AI workflow design pack Evidence of relevant access, quality and risk controls Demonstration and limitations record
Assessment
Scenario-based practical assessment Design the AI-enabled workflow and implementation backlog 30% Link normal, ambiguous and failure scenarios to acceptance 25% Specify information boundaries and consequential-action approvals 25% Present a stakeholder-ready requirements and decision pack 20% Proposed VNode outline-level assessment; no vendor accreditation or completed lab validation implied.
Participant deliverables
- Assessed AI workflow design pack
- Evidence of relevant access, quality and risk controls
- Demonstration and limitations record
Scope boundaries
Step-by-step lab instructions; Runnable solution code; Packaged source datasets; Executed environment validation
Delivery options
Count teaching hours, not calendar days. Exclude breaks. Split into 4-hour or 8-hour teaching sessions; schedule complex project work in contiguous blocks.
Delivery Models
Delivery models
Virtual ILTOnsiteHybridExecutive WorkshopBootcampWeekend
Engagement Fit
Engagement fit
- Private cohort delivery
- Practitioner / specialist practitioner depth
- Business outcome alignment
Enterprise Customization
Enterprise customization
Tailor this program to your organization's priorities: Define an implementable AI-enabled workflow with measurable acceptance and control requirements.
- Private cohort scheduling
- Equivalent-experience entry review
Resources
Program resources
Yes. Most enterprise clients prefer private delivery scoped to role mix, timezone, and rollout timeline. We align lab environments and scenarios to your tenant context where applicable.
Enterprise Proof
Trusted delivery outcomes
“We needed a partner who understood both the technical depth of Azure OpenAI and the governance requirements of an enterprise.”
Banking & Finance
Representative Enterprise Banking Team
The focus was not just on tooling knowledge, but on helping teams work from a shared operating model as they adopted a more modern data platform.
- Clearer platform operating model across teams
- Improved confidence in modern data stack adoption
Healthcare
Representative Healthcare Product Team
The engagement helped product and engineering stakeholders move from interest in AI to clearer implementation choices, security expectations, and prototyping discipline.
- Stronger alignment between product and engineering teams
- Improved clarity on prototype-to-production requirements
Delivery Capability
Enterprise-grade instruction
MCT-led delivery
Programs led by Microsoft Certified Trainer practitioners
Enterprise program oversight
Founder-led specialist delivery with structured rollout planning
Global delivery
APAC · EMEA · Americas · Virtual & Onsite
Implementation-focused
Hands-on labs aligned to production scenarios
