Executive Certificate in AI Strategy and Product Innovation

The six-month Executive Certificate in AI Strategy and Product Innovation from MIT xPRO offers an integrated learning journey combining two specialized programs — the Designing and Building AI Products and Services program and the AI Strategy and Leadership Program: Thriving in the New World of AI. This unique experience blends technical expertise, product innovation, and strategic leadership, providing a structured learning experience that enables professionals like you to develop AI-driven products, implement AI solutions at scale, and drive sustainable business growth.

As AI adoption accelerates across industries — from health care and finance to manufacturing — it is enhancing automation, operational efficiency, and innovation. However, successful integration requires more than just technological advancement — it demands a strategic approach that aligns AI initiatives with overarching business objectives to drive meaningful impact. Led by MIT faculty and industry experts, the program combines real-world examples, case studies, and hands-on projects to help you apply AI strategy and product management principles to real-world challenges. The comprehensive curriculum provides practical tools, industry insights, and actionable frameworks to successfully navigate AI adoption within complex organizational environments. Designed for technology professionals, business leaders, entrepreneurs, and consultants, it bridges the gap between innovation and impact, equipping you with the skills and frameworks to drive meaningful change in an AI-first world.

The Executive Certificate in AI Strategy and Product Innovation will enable you to:

• Build a roadmap to integrate AI and data into your organization 

• Design transparent and accountable AI processes 

• Evaluate leadership mindset, innovation, and adaptability 

• Plan for an AI-driven future across all organizational levels 

• Understand machine learning (ML) algorithms by identifying supervised, unsupervised, and reinforcement learning and their key uses 

• Differentiate neural networks, including CNNs, DNNs, and RNNs, based on structure and application. 

• Explore generative AI (gen AI) by understanding transformer models and when to use them in business 

• Assess the AI design process through its four key stages and best practices 

• Study human–AI interaction to see how human input enhances AI decisions 

• Build an AI business case with strategy, cost-benefit, and implementation planning