Artificial intelligence (AI) seems to be on everyone’s mind. It powers natural language recognition within voice-powered assistants like Siri and Alexa, beats world-class Go players (Google AlphaGo), and enables hyper-targeted e-commerce and content recommendations across the web, as we see with Amazon and Netflix.
But recently, AI has begun actively expanding its footprint within the enterprise. Executives are trying to more fully comprehend what AI is and how they can use it to better capitalize on business opportunities by gaining insights into their data and engaging with customers more productively, thereby honing a competitive edge.
AI is the frontier of enterprise technology, but many misperceptions remain about what it is and how it works. Part of the confusion stems from the fact that AI is an umbrella term that covers a range of technologies — including machine learning, computer vision, natural language processing, deep learning, and others — that are in various stages of development and deployment.
The use of AI for dynamic market-based pricing and targeted marketing has been spreading through corporations for a while, but actual AI computing where machines think like humans is still years in the future. The various possibilities prompt a range of reactions from people who understand AI’s disruptive potential.
So, is enterprise AI just an over-exposed and under-delivering concept about to fall off a cliff and into Gartner’s Hype Cycle Trough of Disillusionment? Or is it the holy grail of business innovation that will leave companies without it in the dust of tech transformation?
In an attempt to answer these questions, we commissioned a survey of over 650 IT decision makers at large enterprises working across industries in the U.S., the U.K., Germany, and France, ranging from directors to C-level executives, to gauge their pulse. We asked a host (Read more...)
This is a Security Bloggers Network syndicated blog post authored by The Cylance Team. Read the original post at: Cylance Blog