Most product teams are under pressure to “do something with AI”, but that pressure rarely comes with a clear answer for which AI feature is worth building, or how to ship one responsibly. This course exists to replace that vague pressure with a workable process: spotting genuine AI opportunities, evaluating them against customer value, and working with engineering and data science teams to turn them into shipped, measurable features rather than demo-only prototypes.

Delivered by Arab British Fellowship Training Academy within its Product Management Courses, the programme covers ChatGPT and generative AI use cases, machine learning fundamentals for non-technical product managers, automation opportunities, and the ethics, privacy and governance questions that come with putting AI in front of real customers.

• Separate genuine AI opportunities from features built just to follow a trend.
• Build an AI strategy that connects to real product vision and roadmap.
• Evaluate practical use cases for ChatGPT and generative AI in a product context.
• Understand machine learning fundamentals well enough to work with technical teams.
• Identify automation opportunities that genuinely improve customer experience.
• Prioritise AI features by customer value, not technical novelty.
• Measure the performance and real impact of AI-powered features after launch.
• Address ethics, privacy and governance questions before they become a crisis.

Target Audience

This course is suitable for:

• Product Managers and Senior Product Managers
• Product Owners and AI Product Managers
• Technology Managers and Digital Transformation Leaders
• Business and Data Analysts
• Innovation and Software Development Managers
• Startup Founders
• Professionals responsible for AI-enabled product development

Module 1: Beyond the Hype: What AI Can Really Do for a Product

• Fundamentals of AI in product management
• Business value versus AI trends
• The AI product lifecycle

Module 2: Building an AI Strategy That Fits the Roadmap

• Developing a genuine AI strategy
• Identifying real AI opportunities
• Prioritising AI initiatives against the roadmap

Module 3: Generative AI and ChatGPT in Practice

• Understanding generative AI capabilities and limits
• Practical use cases for ChatGPT
• AI-assisted design and workflow optimisation

Module 4: Machine Learning Basics for Product Managers

• Core machine learning concepts, explained simply
• What AI models need from data
• Evaluating model performance without being an engineer

Module 5: Automation That Actually Helps Customers

• Identifying automation opportunities
• AI-powered customer experiences
• Balancing efficiency with customer trust

Module 6: From Idea to Shipped AI Feature

• Cross-functional collaboration with engineering and data science
• Validating AI features before full build
• Launch strategies for AI-powered products

Module 7: Measuring What AI Features Actually Deliver

• Defining AI product metrics
• Tracking adoption and monitoring performance
• Iterating based on real usage

Module 8: Responsible AI and What Comes Next

• Ethics, privacy and governance in AI products
• Managing AI-specific risk
• Scaling AI-powered products responsibly