Putting AI to Work: A Practical Training Course for Product Managers
1Summary
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.
2Objectives and target group
- 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
3Course Content
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