AGM-AIEBA: AI-Enabled Business Analysis Training

Module 1: Leveraging Generative AI as a Business Analyst

Generative AI is transforming the way business analysts work, offering new opportunities to streamline analysis, automate tasks, and generate data-driven insights. This module introduces how GenAI enhances business analysis by improving efficiency, refining decision-making, and supporting documentation. Business analysts can leverage AI to understand market trends, optimize stakeholder communication, and draft clear business requirements. By integrating GenAI into their workflow, professionals can focus on higher-value strategic tasks while AI handles routine analysis and documentation, making business analysis more agile and impactful.

Module 2: Understanding Generative AI (GenAI)

In the Understanding Generative AI (GenAI) module, candidates will explore the fundamentals of generative AI and its role in business analysis. They will learn what generative AI is, how it creates data-driven insights, and why it is becoming essential for business analysts. The module covers the ethical considerations of using GenAI, ensuring responsible and unbiased application in decision-making. Additionally, candidates will examine the limitations of GenAI in business analysis, understanding where human judgment remains crucial. By the end of this module, they will have a solid foundation in GenAI and its practical implications in the business world.

Module 3: Using Generative AI

In the Using GenAI module, candidates will learn how to leverage generative AI tools to enhance business analysis. They will explore various GenAI tools designed for business analysts and understand their capabilities and applications. The module will guide them in selecting the right tool based on specific business needs and analytical tasks. Additionally, candidates will develop the skill of writing effective GenAI prompts to generate accurate and meaningful insights. By the end of this module, they will be equipped to integrate GenAI tools into their workflow for improved efficiency and data-driven decision-making.

Module 4: Enhancing Your Business Analysis Skills with GenAI

In the Enhancing Your Business Analysis Skills with GenAI module, candidates will explore how generative AI can elevate their business analysis capabilities. They will learn to apply GenAI in key areas, such as understanding customers, analyzing market trends, and gaining insights into new domains. The module covers techniques for drafting business analysis requirements, proofing documentation, and creating business documents with AI assistance. Candidates will also develop skills in writing effective AI prompts, streamlining stakeholder interviews, and generating reports, emails, and correspondence. By the end of this module, they will be equipped to leverage GenAI for more efficient and data-driven business analysis.

Module 5: Don’t Fear GenAI as a Business Analyst

Generative AI is not here to replace business analysts but to empower them with smarter tools and deeper insights. By integrating GenAI into business analysis, professionals can enhance efficiency, make data-driven decisions, and focus on strategic thinking rather than repetitive tasks. Embracing AI as an ally rather than fearing it will open new opportunities for innovation and career growth. The key is to leverage GenAI responsibly while maintaining the critical human judgment that makes business analysis invaluable.

Module 6: Business Analysis Foundations & Stakeholder Engagement

Business analysts play a crucial role in digital transformation by bridging the gap between business needs and technology. This module covers the fundamental skills and mindset required for effective business analysis. It also delves into stakeholder management, emphasizing clear communication, collaboration, and alignment with business goals. Additionally, it explores change management strategies to help organizations navigate the challenges of digital transformation smoothly.

Module 7: Agile Business Analysis & Requirements Management

With the rise of Agile methodologies, business analysts must adapt to a more iterative and flexible approach. This module explains the differences between Agile and traditional business analysis while focusing on key Agile concepts like user stories, backlog prioritization, and continuous feedback loops. It also covers essential requirements-gathering techniques such as interviews, workshops, and surveys. Participants will get hands-on exposure to industry-standard tools like JIRA, Confluence, and Miro to enhance collaboration and efficiency.

Module 8: Data-Driven Decision Making & Digital Solutions

Business analysts must leverage data and technology to drive strategic decisions. This module introduces business process modeling techniques like BPMN and SIPOC to improve workflows. It also explores business intelligence, data analytics, and emerging technologies like AI, cloud computing, robotic process automation (RPA), and blockchain. Finally, it covers essential business analysis tools such as SWOT analysis, PESTLE, MoSCoW prioritization, wireframing, and prototyping, enabling analysts to provide data-driven insights for digital transformation initiatives.