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Business Analysis for AI Transformation
Published 6/2026
Created by Igor Arkhipov, Analyst's Corner
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 66 Lectures ( 8h 18m ) | Size: 9.4 GB
Learn Business Analysis for AI. Apply structured business analysis to lead AI Transformation projects.

What you'll learn

How to perform business analysis for AI transformation initiatives

Define Requirements to different elements of an AI solution: system prompt, sensors, tools, skills, guardrails and evals

Distinguish between deterministic and stochastic elements of solutions

Orchestrate and align manual and automated parts of the transformation

Apply structured risk management and ethics governance to AI transformation

Perform organisational change management planning in support of AI transformation

Overcome organisational resistance to change and inertia to implement an AI strategy
Requirements

General understanding of IT and software development concepts is required (e.g. integration, API, UI vs back-end)

Knowledge of or experience in business analysis or project management roles is expected

Experience using generative AI tools as an end user will be helpful

(optional) access to Jira and Confluence with enabled Rovo studio will be needed for an optional assignment but is not required to complete the training
Description
So, you've been assigned to your first AI-automation project. May be your customer support team plans to rely on an AI-support agent to ease the volume of incoming calls, or your operations team wants an AI solution to help route internal processes, or the delivery service needs help with order dispatching...
What seems like a standard business analysis problem (identify the needs, elicit Requirements, scope the solution, and ensure it works) becomes tricky once you introduce a new piece of technology for your project, not to say get involved into helping your organisation embark on the journey of its wide-scale adoption.
This course is designed to turn you into that essential Business Analyst who can translate business problems into functional, ethical, and high-quality business solutions powered by AI. You will learn the power and limitations of modern AI technology, develop skills to define Requirements for different types of AI automation, learn how to support AI-strategy development, and perform change management needed to embed AI.
What we will cover

Foundations & Architecture:We'll start with the state of AI and the architecture or modern AI solutions and you'll learn why technical knowledge is not optional for a modern business analyst.

Functional Requirements:We will discuss how the Requirements for AI products are elicited and validated. This is the core of our work. We will cover the approaches to defining Requirements for system prompts, sensors, tools, data, skills and human oversight.

The Practicum:We will look at a few end-to-end case studies and examples, including scoping a simple automation project that aims to help business analysts write better Requirements using AI. I called this solution "Poppy"

Guardrails, Ethics, and Evals:An AI solution without a safety net quickly becomes a risk and a liability. We will dive into frameworks for risk management, ethics, and comprehensive evaluation of AI solutions; and will learn to formulate Requirements to guardrails and design evaluation rubrics for AI.

Change Management:We will look at the people's side of AI automation. A perfect technical solution fails if the organisation isn't ready. We'll look at AI strategy, stakeholder analysis, and how to overcome the resistance that comes when automation changes the nature of work.
AI is a powerful tool and has a lot to offer, but it is up to us to harness that power and put it into good use.
By the end of this course, you will be well equipped to perform business analysis and manage a backlog of Requirements for a solution that has AI elements in it. By learning from a combination of video lessons, articles and industry resources, you will know which questions to ask and what to pay attention to so you cover both technical and organisational elements of an AI transformation.
During the training, we will explore 3 case studies

Scoping anAI solution to support doctors in a hospital's Emergency Room with patient triage - we will use this case study in theoretical lessons to learn how to use the Requirements canvas to elicit different types of Requirements.

During our practicum, we will review areal life implementation of an AI solution that improves the quality of software Requirementsas part of software development lifecycle - implemented using Rovo, Jira, and Confluence; orchestrated via Atlassian Flow Automation.

And as a part of your assignments you will elicit Requirements for and assess the preparedness of an AI solutionhelping a financial organisation investigate potential fraud.
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What this is not: this course is not a training on "how to use AI in daily business analysis work" nor is it a training on "how to build your own agent". In this training, we will assess AI as a solution to business problems, and will go through the stages of continuous refinement and re-assessment of what makes that solution acceptable and which technical and non-technical changes need to happen to successfully deploy and adopt it.
Designed for people leading the change, this course will be especially helpful for business analysts, product owners, business leaders and project managers.
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This course forms a part of Analyst's CornerBusiness Analysis Capability Ladder - a structured multi-step approach to building strong business analysis skills and expertise.
It consists of 4 distinct rungs tailored to people at different stages of their professional lifecycle

Foundation: Learn the ropes of business analysis | Build the baseline for professional career

Progression: Deepen your analysis expertise | Scale your toolkit and analytical rigour

Specialisation: Develop strategic specialisms | Cultivate niche expertise in high-value domains

Leadership: Gain authority and leadership | Lead business analysis for your team or organisation
Each rung consists of multiple training courses and an assessment; finishing the whole Ladder provides the depth of practical knowledge that rivals traditional academic BA programs.
This course is one of the three courses on theSpecialisation rung.
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Note: Analyst's Corner is anEndorsed Education Provider™by IIBA®, which means the materials and references to IIBA® and its publications used in this course are licensed for us to do so. By enrolling in this course you support legal use of intellectual property and contribute to the development of business analysis profession.
Analyst's Corner is not a regulated academic body or university. Our "BA Capability Ladder" is a proprietary professional development framework focused on practical, high-impact skills based on industry standards and best practices; and is not part of the formal higher education sector.
Generative AI was used in creation of some visual materials used in the course: Google Gemini and Google Flow.
All the photos used are provided by Unsplash.
All the trademarks belong to their rightful owners. Any references to third party products & services or elements of popular culture are done for educational purposes only, i.e. in fair use.
Who this course is for

Business analysts working on AI projects

Change managers supporting AI transformation

Business managers and leaders in charge of AI transformation

Product owners taking over AI products

Project managers responsible for AI automation projects

Anyone who is genuinely curious about AI and AI application to business
Homepage

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https://www.udemy.com/course/business-analysis-for-ai-transformation

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Business Analysis for AI Transformation

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