Artificial intelligence initiatives are springing up in almost every industry and generating a huge market in their wake. Gartner predicts that AI augmentation will generate $3.9 trillion in business value by 2022 alone. What’s more, Gartner says that AI promises to be the most disruptive class of technologies during the next 10 years, driven by increases in computational power, advances in storage technology, the availability of new data and the ubiquity of deep learning toolkits.
However, despite all of the momentum for AI, turning the promise into business value isn’t as easy as flipping a switch. Organizations making the journey to AI face a multitude of complex choices related to data, skillsets, software stacks, analytic toolkits and infrastructure components. Each of these choices has significant implications for the time to value associated with AI initiatives.