Data is everywhere around us. Generative AI and deep learning ensured that the AI winter remains firmly behind us. But why do we still struggle to get value from those technologies? Except for a few tech giants, most companies - even those at the forefront of innovation in other fields, such as the automotive and energy sectors - don't achieve the desired impact. The answer to this is a lack of a new role that is needed - that of a data and AI strategist.
In this course, we'll define the key terms of the AI strategy field. Then, we'll dive deeper into the concrete skills and paths you can take to become one. Finally, the bulk of the course is focused on the 3D model of doing data and AI strategy - a framework you can apply daily as a strategist.
Many of the concepts and ideas are based on my conversations with worldwide leaders in the data and AI strategy field, such as Tom Davenport, Nicolas Averseng, and Doug Laney. Those became the foundation of the Elements of Data Strategy book and serve as a companion to this course (participants get a free copy).
Data and AI strategy is a rapidly maturing field, and there's a first movers' advantage to all of us who dive in head first into this challenging but gratifying new career.