How AI adoption has yet to reveal its real potential

Check out the on-demand sessions from the Low-Code/No-Code Summit to learn how to successfully innovate and achieve efficiency by upskilling and scaling citizen developers. From top artificial intelligence (AI) scientists warning that deep learning will push radiologists out of employment, to healthcare professionals heralding that AI will redefine the doctor-patient relationship, to tech executives promising that fully self-driving cars are just around the corner, AI has been marked with plenty of failed predictions in recent years. Despite the remarkable advances in AI, it has yet to play its transformational role in many industries. However, when compared to other technological milestones such as the steam engine, electricity and the internal combustion engine, it is no surprise that AI adoption is slow. Ajay Agrawal, Joshua Gans and Avi Goldfarb, professors at Toronto University and authors of the new book Power and Prediction, believe that we are at a stage where the power of AI is evident but its widespread adoption has yet to come. And to better deal with the challenges that stand in the way of leveraging the power of AI, we must understand not only the applications where it is used but also the systems in which it operates.