Achieving Real Business Outcomes from Artificial Intelligence

Foreword

Enterprises are under the impression that they’re on their way to using artificial intelligence. They’ve set up a few machine learning models and have had new algorithms work their way into previously deployed Software as a Service applications. Inside the organization, it feels like they’re checking all the right artificial intelligence (AI) boxes.

But the true end goal of AI in the enterprise is something much more sophisticated. Oliver Ratzesberger and Mohanbir Sawhney expressed it succinctly in their book, The Sentient Enterprise (Wiley), noting, “Our objective is to position the enterprise in such a way that analytic algorithms are navigating circumstances and making the bulk of operational decisions without human help.”

With the exception of a few Bay Area tech giants, the industry hasn’t experienced highly proficient natural-language processing, image-based detection, or other skills that would enable this next generation of AI to drive significant business outcomes instead of just performing basic business tasks.

Imagine if AI platforms could identify and bring together data sources and then explain to their human counterparts the “why” behind the recommendations—something like AI for data engineering and data science. Or, imagine if chatbots could interpret problems and provide solutions using natural language that satisfy buyers more quickly and more effectively than current call centers. Imagine if key business functions were being driven by algorithms with ...