
Discover how AI serves as a co-pilot for business analysts, enabling practical tools, prompts, and workflows to enhance requirements, process design, dashboards, and governance with ethics.
Transform how business analysts use ai as a co-pilot to turn noise into a narrative, with prompts, patterns, and guardrails for trustworthy, responsible decision making.
Discover how AI tools like ChatGPT, Copilot, Miro, FigJam, Excel, Sheets, Jira, and DevOps streamline business analysis. Turn raw data into actionable insights and deliver AI projects.
Discover data privacy foundations, encryption, and secure storage to protect data and personally identifiable information. Embrace artificial intelligence usage with human-in-the-loop decision making and audit trail transparency to build trust.
Discover how generative AI and predictive AI complement large language models, exploring capabilities and limits, with practical emphasis on responsible use and building trust.
AI reshapes every BABOK knowledge area, from planning and monitoring to elicitation and collaboration, enabling predictive analytics for requirements, strategy, design, and evaluation.
Leverage AI for business analysts to accelerate strategy analysis, competitor scanning, capability gaps, and scenario planning, turning raw text into structured insights and a working business model canvas.
Master the prompt blueprint to convert vague questions into precise outputs. Define the role, objective, inputs, constraints, output format, and quality checks for clear AI-driven business analysis.
Explore reusable prompt patterns, critique and improve, refactor to X, traceability mapper, and test case generator that streamline transfer tasks in mobile banking with OTP and clear traceability.
Apply guardrails to reduce hallucinations and ensure verifiability in artificial intelligence outputs for business analysis by defining scope, anchoring sources, and verifying with cross-checks and human oversight.
Draft interview guides and workshop agendas with AI while applying guardrails to ensure data quality, verifiability, and human oversight for reliable, accountable business insights.
Use AI to mine raw meeting notes into structured insights, producing personas, jobs to be done, and pain points that drive better solutions.
Map stakeholders and design communications plans with AI, identifying key actors, classifying their influence and interests, simulating perspectives, and monitoring engagement to deliver targeted actionable insights.
Capture stakeholder needs, translate them into features, and draft user stories or use cases with clear, testable, traceable requirements; AI drafts first, you validate and ensure traceability.
Learn to draft, critique, and validate Gherkin acceptance criteria with AI, applying INVEST and SMART checks to produce clear, testable scenarios for onboarding and verification.
Move from assumptions to assurance by applying AI to improve clarity, completeness, and testability of requirements and strengthen traceability with RTMs, acceptance criteria, and stakeholder validation.
Convert unstructured narrative text into BPMN diagrams using AI through a five-step workflow: collect text, draft with prompts, generate visuals, refine with validation, and realize faster, clearer, traceable processes.
Design the to-be process with AI to reduce waste, improve flow, and manage risks, overlaying preventive, detective, and corrective controls for an auditable, compliant workflow.
Define KPI and OKR basics to turn metrics into actionable outcomes, using semantic metrics, data lineage, and governance to cut onboarding time while preserving fraud control.
Profile CSVs with AI to reveal schema, data quality risks, and PII hints, then transform plain English questions into read-only SQL, demonstrated on a customers.csv sample.
Build a clean, interactive Excel dashboard with pivot tables, charts, slicers, and a timeline to track order status and sales, then use ChatGPT prompts to derive insights and forecasts.
Turn a user story into a lo-fi wireframe and clear ux copy for a mobile-first flow, delivering three usable artifacts, testable screens, and accessibility checks.
Turn a simple scenario into a five-stage journey map with emotions and pain points, then craft a usability test script and use AI to synthesize feedback into themes and fixes.
Apply the Moscow method to classify backlog items into must, should, could, won't, then use AI-assisted WSJF scoring to quantify cost of delay and effort for data-driven prioritization.
Use AI to plan releases by sequencing now, next, later, visualize dependencies with an edge list and a zero-one matrix, and manage a raid log of risks and assumptions.
Master the language of ai and apply tools, ethics, governance to accelerate and transform the business analyst role with a playbook of templates, prompts, and checklists for workshops and reviews.
As AI reshapes the business world, savvy BAs use it to boost productivity. For example, 85% of organizations are integrating AI into their processes, making AI skills crucial for analysts. ChatGPT and similar generative models can expand your thinking and streamline documentation, from drafting requirements to synthesizing stakeholder notes. This energetic, beginner-friendly course shows you exactly how to harness practical AI tools (like ChatGPT, Microsoft Copilot, Google Bard, etc.) for everyday business analysis work – no coding or AI background required.
You’ll start with AI fundamentals (generative vs. predictive AI, LLM capabilities/limits) and learn a structured prompt-engineering approach. Discover techniques and reusable patterns (e.g. “critique & improve,” “refactor,” “test-case generator”) to get reliable outputs and reduce hallucinations. Through hands-on demos, see how AI can automate common BA tasks: drafting interview guides, turning meeting notes into user stories or personas, generating stakeholder maps and communication plans, and writing clear acceptance criteria (Gherkin format) with AI. Learn to convert requirements into process diagrams (BPMN) using text prompts, detect process bottlenecks, and design improved “to-be” workflows. You will also cover testing and validation: AI-assisted test-case generation, requirements traceability matrices, and more.
We then tackle data and tools: use AI to profile CSV datasets, generate simple SQL queries from natural-language questions, and build rapid dashboards in Excel/Sheets – interpreting the results responsibly.
Whether you’re a total newcomer to AI or a BA eager to work smarter, this course will give you the tools and confidence to transform your analysis work. Enroll now to future-proof your career and become an AI-powered business analyst!
What students will learn:
How to integrate ChatGPT and AI assistants into the BA lifecycle (planning, elicitation, requirements, testing) to work faster and smarter.
Techniques for writing effective prompts and applying guardrails (quality checks) to ensure useful, accurate AI-generated outputs.
Using AI to automate deliverables: drafting interview guides, workshop agendas, personas, user stories/use cases, and clear acceptance criteria (Gherkin) with AI assistance.
AI-driven process analysis: converting text descriptions into BPMN diagrams, identifying bottlenecks and RPA opportunities, and designing improved “to-be” workflows.
Data-centric analysis with AI: profiling datasets, generating SQL queries from natural language, defining KPIs/OKRs, and creating Excel/Sheets dashboards with AI help.
Strategic analysis tasks: using AI for market/customer research, prioritization (MoSCoW, WSJF with AI scoring), and building business cases (cost–benefit, scenario analysis).
Real-world tools: hands-on practice with ChatGPT, Microsoft Copilot, Google Bard, as well as business tools like Miro, Excel and Jira.
Who this course is for:
New or aspiring Business Analysts who want to add AI skills to their toolkit.
Current BAs, project managers, product owners, or consultants interested in using ChatGPT and AI to streamline their BA tasks.
IT, data or QA professionals who collaborate on BA deliverables and want to learn how AI can assist in requirement gathering and analysis.
Anyone curious about AI and business analysis who is looking for a beginner-friendly, hands-on introduction.
Requirements:
No prior AI or programming experience required. This course is designed for beginners in AI and business analysis.
Basic familiarity with business concepts (like requirements, user stories, or process mapping) is helpful but not mandatory.
A computer with internet access (to use AI tools such as ChatGPT – free accounts are sufficient but paid account adds more capabilities).
Enthusiasm to learn: just bring a willingness to experiment with AI tools and practice prompting – we’ll guide you every step of the way.