The AI Ladder

Foreword

Over the years, I’ve seen how the right name can help people understand a new and important technology concept. When Rob Thomas first told me about his idea for the “AI Ladder” at a crowded cocktail party during IBM’s Think event, I thought “This is one of those ideas, like Open Source Software, Web 2.0, big data, and the Maker movement, that isn’t just a label, but a map to help guide people into what had previously been Terra Incognita.”

Everyone is talking about “AI” these days, but most companies have no real idea of how to put it to use in their own business. They just know that they want some of what sounds like magic. But no vendor can help pull AI out of your company like a rabbit out of a hat. The companies who have succeeded have ascended what Rob calls the “AI Ladder.” First, that means understanding what business problem you are trying to solve. Next, you need to get your data in order. And that doesn’t just mean your traditional sources of business and customer data. AI isn’t just about your existing data; it might require creating or acquiring data from other sources that are relevant to your business problem, and that can be used to train the AI models that will then be used to understand and respond to that data in the real world. Think about the enormous amounts of data that needed to be collected to build today’s speech and image recognition capabilities. You need a data architecture that can support disparate sources of data.

You also need developers ...