AI…What are we waiting for?


AI…What are we waiting for?

State of Cloud: Trends & Predictions

Cloud has allowed for the rapid expansion and adoption of AI technologies. But some are still hesitant to embrace it.

A blog post by David Linthicum, managing director, chief cloud strategy officer, Deloitte Consulting LLP

I’m one of many people who will tell you that artificial intillegence (AI) is nothing new. In fact, I was an AI analytics technician directly out of college at the age of 22. I’m now 56.

Why did it take so long to adopt AI as a mainstream enabling technology? One word: Cloud.

State of Cloud: Trends & Predictions

AI of the 1980s was way too expensive for most commercial businesses. It required a million-dollar buy-in, even if you leveraged timesharing services (AKA the model T of cloud). The emergence of cloud technology suddenly made AI affordable and more useable at the same time.

Today we have access to huge amounts of AI power, all with a much easier way to leverage AI technology and often at the cost of what we pay for lunch. The new cloud-based AI allows us to punch above our weight and make systems learn things that once did not have learning capabilities.

So what are people waiting for? While cloud answered the question of “how,” people are are still grappling with the question of “why.”

I’m seeing a few reasons why we’re not adopting AI right now, despite the new and much-improved price. First, there is concern around the potential human impact that AI will bring to the job market. If AI can think like us, it will eventually take jobs. Why risk jobs?

Nowhere is that more apparent to me than in the driving industry. Self-driving overland trucks, on-demand car services, even local self-driving delivery will begin to appear later this year. In this industry alone, AI could disrupt millions of jobs. This shift is o concerning that some industry leaders are calling for an AI tax.1 The theory is that companies will pay for the use of AI, and then taxes will go toward retraining and unemployment compensation.

Second, we look at the impact of moving to AI. Those who won’t directly benefit from AI, or have traditional systems that are so old it will be costly to modify, are sitting this revolution out for now. But for others, AI will be the disruption they need to enter a market dominated by major brand players. They see it as a redistribution of market share, very much like the disrupters that have already changed several major market today. Examples would be taxis vs. ride share and hotels vs. home share. Organizations that are slow to move on AI may be forced to adopt the technology down the road in order to defend marketshare and stay competitive.

While we can’t quickly solve the problems that may arise with AI-powered businesses, it is interesting to note that we’ve been here before.  The industrial revolution meant that farming and commodity production became largely automated, and that had an impact on the economy and jobs.  So did the rise of the automobile and rapid transportation methods.  There is plenty of historical evidence that individuals and organizations will adapt.

End notes

1 Murayama, Keiichi and Sato, Hiromi. “Robot taxes will help keep humans employed, Bill Gates predicts.” Nikkei Asian Review, 3 Nov. 2018, Murayama, Keiichi and Sato, Hiromi. “Robot taxes will help keep humans employed, Bill Gates predicts.” Nikkei Asian Review, 3 Nov. 2018,

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