AI pilot projects: How to choose wisely

AI pilot projects: How to choose wisely

A few years ago, I was listening to a vendor pitch with a group of enterprise IT veterans.

SwissCognitiveThe sell focused on features of an intrusion detection software product and the value of . The vendor said techniques allowed the product to automatically detect threats.

Discussing the pitch afterward, the general sentiment of the group was “I don’t buy it. There is no such thing as magic!” I agreed. As a student of enterprise software, I understood two key things:

  1. Vendors hype the “next great thing” to make it seem more valuable.
  2. Software is very specific. Code has specific instructions and performs exactly as told.

Based on our past software experience, the vendor pitch seemed like snake oil. In our world, software did not figure things out for you. It just followed the rules set for it.

We did not understand the power of , which is turning traditional software development on its head. I’m now convinced that using will quickly become as common as today’s use of databases. Far from viewing it as snake oil, I now understand that is essential to bring businesses to the next level.

How to select the right project – and beat resistance

Selecting the right pilot project is a vital first step because success with is different than with traditional software development. Rather than software performing exactly what it’s told to do, an system learns what it needs to do. That is the opposite of what we are used to, and that creates resistance to investing in .

Start by finding examples of outcomes you want (and you need many of these examples) so the software can learn what it needs to do. This means you must be prepared to explore and be comfortable not knowing why or how something works.

The best way to curb your own resistance to is to work on a use case. For example, a recommendation engine project served as a starting point for one company’s experience. Initially, it was hard to get product managers to attend meetings and provide feedback. But as the project progressed and the managers understood the approach, they all identified multiple opportunities within their own area of responsibility and sought to launch their own efforts.

They began to recognize how could be useful in their roles. This is why selecting the initial project is vital. It demonstrates the power of and and how it can be applied broadly across the business.

is about changing routines, and that will always meet resistance. The recommendation engine successfully connected technology and people to show how can help people achieve objectives.[…]

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