Artificial Intelligence is transforming organizations across every industry. However, many businesses are rushing toward AI adoption without fully understanding the range of technologies available or how to determine which approach best fits their needs.
Today, AI conversations are often dominated by Large Language Models (LLMs) such as ChatGPT, Claude, Gemini, and DeepSeek. While these technologies are powerful, they represent only one category within a much broader AI landscape. The challenge for organizations is not simply adopting AI, but selecting the right AI approach for the right business problem.
In this session, internationally recognized thought leader Scott Ambler will demystify the AI ecosystem and explain how machine learning models are created using data and algorithms. Participants will explore the differences between predictive AI, generative AI, and other AI approaches, while learning when each should be used and when alternative solutions may be more effective.
The discussion will also examine how Business Analysts play a critical role in AI initiatives by helping organizations understand business objectives, analyze requirements, identify appropriate solutions, and ensure that AI investments deliver measurable value.
Rather than focusing on technology hype, this session provides a practical framework for evaluating AI options and selecting solutions that align with organizational goals, operational realities, and business context.
Attendees will leave with a clearer understanding of the AI-development lifecycle, common AI use cases, and how to avoid the costly mistake of applying the wrong technology to the wrong problem.
Learning Objectives
By the end of this session, participants will be able to:
- Understand how business process analysis fits into the AI-development lifecycle.
- Identify factors that influence the selection of AI algorithms.
- Recognize when Large Language Models are appropriate and when alternative approaches may be more effective.
- Understand the differences between predictive AI and generative AI.
- Evaluate common business use cases and determine suitable AI strategies.
- Explore situations where non-AI or non-machine-learning solutions may provide better outcomes.
Course Outline
Understanding the AI Landscape
- The evolution of AI technologies
- Common misconceptions about AI
- Why AI is more than Large Language Models
How AI Models Are Created
- The relationship between data, algorithms, and models
- Understanding machine learning fundamentals
- Building AI solutions from business requirements
When LLMs Make Sense—and When They Don't
- Strengths and limitations of generative AI
- Appropriate use cases for Large Language Models
- Common implementation mistakes
Choosing the Right Algorithm
- Matching business problems to AI approaches
- Predictive AI versus Generative AI
- Evaluating business context and constraints
Common Business AI Use Cases
- Customer experience
- Process automation
- Forecasting and decision support
- Risk management and analytics
Beyond AI: Alternative Approaches
- When traditional analytics may be sufficient
- Non-machine-learning solutions
- Avoiding unnecessary complexity
Audience
This session is ideal for:
- Business Analysts
- Product Owners
- Data Analysts
- Data Scientists
- Project Managers
- Digital Transformation Leaders
- AI and Innovation Teams
- Technology Professionals
- Anyone involved in evaluating or implementing AI solutions
Session Overview
Date: Thursday, September 17, 2026
Time: 7:00 PM – 8:00 PM Eastern Time
Format: Virtual Live Session
Duration: 1 Hour
Instructor Profile
Data Methodologist | International Keynote Speaker | Author | Agile Data & Agile Modeling Expert
Scott Ambler is a Data Methodologist with Ambysoft Inc. and one of the world's leading voices on Agile Data, Agile Modeling, enterprise architecture, and modern data practices. He has spent decades helping organizations improve the way they build, manage, and leverage technology and data assets.
Scott is an internationally recognized keynote speaker and the co-author of more than 30 books covering software development, agile methodologies, data management, and digital transformation. He previously served as Vice President at the Project Management Institute (PMI), where he helped shape thought leadership and professional practices across the global project management community.
Known for translating complex technical concepts into practical business guidance, Scott helps organizations understand how technology decisions affect long-term business outcomes. His work focuses on helping enterprises make smarter decisions regarding data, analytics, artificial intelligence, and organizational agility.
Scott's sessions combine deep technical expertise with practical, real-world insights, making advanced topics accessible and actionable for both business and technology professionals.
By registering for or attending this event, participants agree to comply with the Participant Code of Conduct. The organization reserves the right to restrict, suspend, or terminate participation when an individual's conduct materially interferes with the educational objectives of the program or negatively impacts the learning experience of other participants.