Artificial Intelligence is no longer the stuff of science fiction. But what is it? A.I. is one of the most polarizing technological innovations of the past 50 years, not simply because it involves physical or infrastructure ramifications but also because it evokes ideological dilemmas as well: workforce rebalancing - will we be replaced, etc? When one thinks about AI, one of the most popular misconceptions is the image of  giant sentient robots bent on destroying the human race. These issues have divided popular opinion into two distinct groups - those in favor and those strongly against the advancement of A.I. research. However, one commonality shared by each of these opponents is a lack of understanding around what A.I. really is and how it can be utilized to make the world a better place.

Let's start with a brief history. The concept of Artificial Intelligence has been around nearly as long as the computer itself. Alan Turing, in his essay "Computing Machinery and Intelligence" first posited the question about machine learning, suggesting that it is theoretically possible that machines can think. His concept became known as the "Turing Test" - when a conversation between a machine and a human becomes indistinguishable, the computer is considered to be intelligent. Of course, at the time, computers were the size of a studio apartment. But let's try walking before we run...

A.I. has certainly evolved since its inception but need not be overly complex. A.I. can be as simple as an augmented search index. Imagine creating metatags of your most important web content, then curating that data through an autonomous search advisor. If a user queries a string of phrases (e.g. What is my account balance?), an automated response is triggered. This is basically the role of a chatbot. Chatbots can sit on your main site and provide the first line of assistance to a customer. Further, they can help escalate inquiries to more specialized human operators if needs be. Chances are, you already have an automated voice routing system for incoming phone calls. This is not that dissimilar.

Building a chatbot can be as complex as you like. From basic keyword or tag recognition all the way to natural language processing to speech-to-text and emotional cue recognition. What is important is starting somewhere - especially if you think your business is too small to use this technology. Would you rather have 5 customer service reps be fielding general questions and balance inquiries, or divest their energy instead into prospecting, reducing attrition or even proactive customer acquisition and up-selling?

Lets take this one step further. Imagine creating an index of all the items in your product catalog. Now, group those items into relational tables or product sets- e.g. T-shirts and jeans, sweaters and scarves, etc. Now take this intelligence and layer it on top of your customer information database, identify the gaps in your product saturation and be able to provide an informed set of product recommendations to your to your customers based on purchase history. Sounds daunting? Sounds like an impossible task? This is what an AI system is designed to do: crunch big data and identify patterns. This information can equip your call center or client facing reps with a deeper level of customer insight. 

Although the concept has been around since the 1950's, we are only beginning to understand the practical applications of A.I. If you have questions about this, know that you're not alone. We are on the cusp of something extraordinary and the onus is on us to define the marketplace. 

Questions? Comments? We're here to help... sound off below! :-)