The (Somewhat) Hidden Costs of AI

Andy Jordan is President of Roffensian Consulting S.A., a Roatan, Honduras-based management consulting firm with a comprehensive project management practice. Andy always appreciates feedback and discussion on the issues raised in his articles and can be reached at [email protected]. Andy's new book Risk Management for Project Driven Organizations is now available.

  Artificial Intelligence  

Artificial intelligence has become a major disruptor remarkably quickly. Just a few years ago, it was still pretty much exclusively theoretical, but now it is being implemented in most organizations across multiple departments and functions.

It continues to evolve as the technology advances and organizations learn how best to leverage it, but it is clearly becoming an integral part of how enterprises operate. However, there is still one very large unknown. That’s how much all of this AI is going to cost.

I’m not talking about the obvious costs—software licenses and support, training, implementation services, and so on. I’m not even considering the potential human cost of lost jobs and forced role changes. Those are both hugely important, but they are also fairly high on the list of priorities for organizations looking to leverage AI.

I want to focus on something that has the potential to be much more significant, but isn’t as obvious.

The cost of running AI
It takes a lot of processing power to run AI engines. They need access to huge amounts of data to train themselves, and they produce data at a rate unlike pretty much anything else.

Anyone working in or around IT has heard the adage “storage is cheap,” and for the best part of the last couple of decades, it has been. But the tremendous amount of storage required …

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