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IBM

As the expression goes, "There’s no AI without IA." In other words, enthusiasm for AI has led many to jump in head first. But without a strong technology foundation, companies could be setting themselves up for obstacles. 

As Rob Thomas, IBM Analytics general manager, wrote recently in Venture Beat:

The evolution of the auto industry is similar in form to the currently nascent world of artificial intelligence. And like the auto industry, in order for AI to flourish, organizations must adopt and embrace a prerequisite set of conditions, or building blocks. For example, AI requires machine learning, machine learning requires analytics, and analytics requires the right data and information architecture (IA). In other words, there is no AI without IA. These capabilities form the solid rungs of what we call the “AI Ladder” — the increasing levels of analytic sophistication that lead to, and buttress, a thriving AI environment.

AI currently mimics and improves the human function; said another way, it brings human features to technology. In the consumer world, that is mimicking speech, vision, and daily interactions. In the enterprise, it mimics and improves enterprise functions, such as logistics, marketing, finance, operations, and HR. While it is similar in concept, the difference is as stark as the Cugnot Steam Trolley and a Tesla.

Enterprise AI is about solving sophisticated business problems in highly dynamic environments. This requires an understanding of well-defined use cases and starting points, as well as an acknowledgment that, per MIT professor Erik Brynjolfsson, “the bottleneck now is in management, implementation, and business imagination."

Of course, the entry points for AI vary from organization to organization. In some cases, companies jump directly to the top of the ladder and adopt established AI technologies for specific use cases. But in many others, organizations begin to build out their enterprise AI environment by getting their IA in order.

To provide fluidity and avoid Brynjolfsson’s bottlenecks, organizations have three distinct foundational areas of technical advancement to embrace and exploit: hybrid data management, unified governance and integration, and data science and business analytics.

Think you know something about machine learning? Think it will solve all your company’s problems, make cars fly and stop the voices in your head? 

We’re betting you could use a little help, so much so, that we’ve designed a short four-question quiz that will reveal the gaps in your knowledge and finally, yes, finally, admit you need expert advice. 

Click here to assess your skills:

Your assessment? 

It’s time to get serious about machine learning. 

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