An in depth look at why the grand majority of chatbot implementations fail to deliver the value you were promised

September 16, 2020

3 Min Read


By show of hands, how many IT or Business Unit executives out there have read an article in your favorite business technology periodical that stated:

“If you don’t embrace the AI wave now, you will be drowned by your competition?”

It’s ok, no one can see you raise your hand… besides, you are in good company.

Many companies out there have become early adopters based on industry trends that are constantly presenting themselves in our research, our vendor relationships, and our eager staff recommendations. The business of staying relevant is a pressure cooker, and AI has turned up the heat for many organizations.

Often the business problem to proverbially “crush” with a new technology is obvious, but more often than not it can also result in a hammer looking for a nail. Now if you are serious about finding that nail, your friendly neighborhood tech vendor will surely aid you in your quest, but if you take nothing else from this blog series, take this one nugget: Know the problem you are trying to solve. You may think this is obvious, but I can’t count the number of calls I have been on with customers who are interested in AI, and upon my query about what business problem they are trying to solve, respond with “Well, what have other companies like ours used it for?”

There is the obvious response of whipping out the infamous “Use Case List”, neatly sliced and diced by company size and vertical, but my response more often is “Is this a strategic investment directive for this fiscal year?” What is the driver behind the request? If you don’t have the driver you cannot succeed, and call me crazy, but I like to understand what constitutes success for an undertaking like this. And there you have it, the theme of this blog series… Success. How do you achieve it, and how to avoid its evil twin brother who has a significantly longer name: Another Failed IT Project with Unclear Goals because of Misplaced Expectations of a Fledgling Technology.

In this series we are going to take a practical look at Conversational AI as a solution to a problem along with the process of identifying that problem. We will discuss the value proposition that was established/promised by your AI vendor, e.g. Better customer interaction, cost avoidance, better utilization by SMEs, etc.

We will examine how Conversational AI addresses or fails to address some of those expectations, as well as if they will ever be able to do so. We will also take a reflective look at the overall readiness of an organization and how that affects a typical AI project from inception to completion, and give you some valued thoughts on how to proceed from where you are in your journey to achieve that elusive Success!

We will see you again and look forward to our next installment: Part II – The Value Proposition (or so I am Told). Until then!

With over 17 years of experience in the IT industry, with the past 10 years in consulting, Dennis brings a wealth of practical know-how to the management, operation, and salesmanship of a services or software product based organization. Dennis’s career has progressed from Junior Developer through the roles of Development Lead to Architect and Enterprise Architect, and eventually to Project/Program Manager, Practice Director, and Pre-Sales Lead – all within the Microsoft technology stack. Dennis is extremely comfortable and thrives in front of executive and technical customers, bringing a professional and concise presence at any phase of the sales cycle or project.

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