If a sales or other line-of-business executive in your enterprise isn’t talking about artificial intelligence these days, it’s time to ask why — and get them on board. We’re operating out of excuses when it pertains to shifting to advanced transformative technologies. Solutions such as AI are now readily available, and businesses no longer need to make heavy investments to stay ahead in today’s digital economy. Furthermore, it’s getting impossible to do business without transformative digital technologies. It’s only a matter of will, of education, and evangelizing of the new horizons these technologies open for the business.
Automation is getting us there. John Roese, global chief technology officer at Dell Technologies, states that transformative digital technologies are now a necessity, but there simply aren’t enough people to hold an enterprise competitive in the 2020s. “It’s a scale issue,” he defined in a recent interview revealed by MIT Technology Review. “Without autonomous operations, it becomes impossible to hold up with the growing opportunity to become a more digital business using human effort alone.”
The choice is clear, he provides: to meet demands for greater IT capacity, “we could either try to hire exponentially more people, or we could do it in a different way, which is to divide up the work between people and machines in a more creative and efficient way.” The fine news, Roese continues, is “you don’t have to be digitally forward in your capability set. You do not need a giant data science team. You do not need to develop your own software. You do not need to construct your own infrastructure. You can consume it from any number of sources of supply that are actually delivering to you highly advanced and almost turnkey outcomes for many of the situations.”
That applies to IT team sizes as well, he continues. “From an infrastructure perspective, a company today that has a small IT organization but is embracing autonomous operations can deliver a much bigger, more scalable infrastructure.” In addition, today’s IT teams “can extend more capabilities to the edge, can have a multi-cloud strategy, and can do it probably faster and better than a giant organization of experts 2 years ago.”
Over the past 2 years, there’s been a “progressive shift towards smarter systems, more autonomy, different consumption models,” Roese says. This is paving the way towards technology democratization. “Several years ago, in order to execute a digital transformation successfully, you had to do most of the work. There were no turnkey products available. Companies were not necessarily set up to do it for you in a way that was easy to consume without tremendous quantities of expertise inside of your company.”.
As a result, everybody is participating in technology decisions and implementation. For example, it’s actually common to hear the head of sales talk about AI these days, he says. “If it isn’t happening in your company, you probably ought to ask why. Because selling is a relationship between you and your customer, but there’s a third party that can help you — and that third party is data and artificial intelligence that can give you better insights and be more contextually aware and more responsive to your customer.”
Roese provides that “it’s engaging to see how these technical terms like AI and machine learning and autonomous operations are now part of the business dialogue. I think most business leaders understand there’s that third party in the relationship. It’s not just them and their customer, it’s the technology that they use that can ultimately change the economics and the performance of their part of the business, whether it be sales or services or engineering or IT.”
Even just a couple of years ago, advanced technology such as AI was the province of companies with deep sources and gifted in-house staffs. “They had to be able to capture the talent pool to really develop their own technology or to be really down in the weeds,” Roese says. “It was a have-and-have-not scenario. Fast forward till today, clearly, we nonetheless need smart people. But now, companies with much smaller software development teams using low code applications and containerization and automation tools can develop really interesting software assets with a much smaller footprint.”
So, “instead of having to have a giant data science team to develop your full tool chain, a much smaller data science team and analytics team can actually use the platforms and capabilities that exist out there,” Roese explains. In addition, these platforms enable smaller teams “get almost better work done than what companies could do 2 years ago.”
With the democratization of advanced technology, successful digital adoption needs to be tied to a human-machine partnership. “The sheer scale of digital transformation tasks exceeds the human capacity of your IT organizations and the budget that you have to use just pure human effort,” says Roese. “This inevitably leads you to looking for ways to shift the work into autonomous systems, into the infrastructure, into the technology so that that scarce resource of human capacity can nonetheless hold up with the high-level objectives,”