This chapter covers
- Composition of AI teams
- Cross-functional collaboration in the team
- Communication with business stakeholders
- Communication with customers and users
- Differences between business-to-business and business-to-consumer contexts
Product builders and managers need to be excellent communicators, balancing the needs and priorities of diverse stakeholders to bring a product vision to life. But when it comes to AI, this role becomes even more nuanced and challenging. AI products introduce new layers of complexity—interdisciplinary teams, inherent uncertainty, and the intricate dynamics of human–machine interaction. To succeed, you need to go beyond facilitation, turning into an educator, translator, and AI advocate.
Mark, a thoughtful and detail-oriented product manager at a growing logistics company, is navigating these challenges firsthand. His latest assignment is to lead the development of a predictive analytics platform designed to augment and improve supply chain management. The platform will help supply chain managers anticipate demand, optimize inventory, and reduce waste by using machine learning models trained on customer orders, historical trends, and even external factors such as weather patterns. It’s a bold, innovative project, and Mark is excited to take the reins.