Conditions ripen for artificial intelligence ascent
A confluence of factors make 2017 the year artificial intelligence (AI) will reach an inflection point in enterprise adoption. Advances in technology enable organizations to treat AI less like an expensive, long-term research endeavor and more like a springboard for agile product development and business model evolution. These advances include the availability of big, rich, trained data sets; democratized access to robust machine learning algorithms through open-source communities and proprietary APIs; and innovations in computing hardware and system architecture. Enterprise IT customers remain more skeptical about the promise of AI than vendors, but most accept AI will factor into their business futures. With a growing array of use cases such as automated, yet human-like, customer service, accelerated diagnoses of complex and deadly medical syndromes, autonomous vehicles and machine-generated investment recommendations, AI is becoming a core element of digital transformation initiatives. As the technical feasibility and business utility of AI come more into focus, the stage is set for AI commercialization. However, a significant gap remains between customer expectations and reality that must be closed for the AI market to flourish.