After spending the time and effort to hire a highly qualified and well-paid IT professional, ask yourself how you’d rather have her spend the bulk of her day: maintaining your company’s legacy systems, or mining the data in those systems to unearth competitive insights?
I know which I’d choose. Never before in my 30-plus years in the tech industry has the cost of missed opportunities been so high—and the culprit is often the IT’s organization’s traditional operating model.
That model has IT professionals burning countless cycles installing, tuning, updating, and patching systems instead of performing the kind of high-level technical work that differentiates their company from its competitors. It’s an unsustainable model in this digital economy.
It’s why a new breed of autonomous database, integration, and other cloud services, all powered by machine learning, is so critical to the future of business. These self-tuning, self-repairing, self-updating services finally give CIOs the tools they need to pull their organizations out of maintenance mode and into innovation mode, allowing their people to fulfill their potential.
The benefits accrue far beyond IT departments. Consider which functions add more value across your company: Security experts constantly patching (and re-patching) systems to plug vulnerabilities, or freeing those same experts to work with their chief information security officer and the rest of the C-suite to establish a comprehensive risk awareness and prevention strategy? HR professionals manually matching new hires to managers, or leveraging machine learning to know which new hires from which universities have the best shot at success with which managers? Software developers waiting around for database administrators to install or upgrade the complex databases that support their work, or those developers liberated from that complexity so they can work with their business partners to create new digital products?
You get the idea.
Of course, these new autonomous systems will force many established IT pros out of their comfort zones—at first. The initial reaction of one of our customers was pretty typical: “If a computer can do what I can do, then what do you need me for?”
But then he reasoned that such autonomous systems will give him the opportunity to build relationships with his company’s executives and developers—relationships that can only help his career while helping him deliver more value to the business. Think of it this way: It’s not just that the computer can do what he can without human error; the computer frees him to do what it cannot.
Even if autonomous systems free, say, only 30 minutes of an IT pro’s time each day, imagine what that person could do with the extra time. Even if it’s just time to step back and think about the bigger picture, it could lead to more productivity, a huge win for both employer and employee. It’s in no one’s interests for people to spend the vast majority of their time delivering commodity services.
Let’s face it, tuning and patching a database or any other IT system is a time-consuming and boring task—but it’s nonetheless essential. Automating those tasks won’t eliminate IT jobs; it elevates them. It also will mean that tech pros won’t have to spend nights or weekends updating a system because that’s the only time the system can be taken down for maintenance.
But that transition from operations mode to innovation mode won’t happen by itself.
Companies need to institute training and mentoring programs and adjust their IT organizational structures to prepare and incentivize their most talented tech people to perform higher-level work. “Until you take care of the people and the processes, I believe you can’t really take advantage of all the technologies,” said Gap’s chief IT architect, F.S. Nooruddin, at our launch event earlier this month for Oracle Autonomous Transaction Processing Cloud Service.
Assuming we make those investments in our people, the autonomous IT systems being developed have almost limitless potential, both for companies and their employees. We aren’t pining for the many things replaced by automation in the 1970s and '80s—pink message pads, calculators, typewriters, and telephone switchboards—because the people who relied on them found more important things to do.
As Ray Kurzweil suggested in his landmark book The Singularity Is Near, machine learning and other forms of artificial intelligence aren’t a threat to our existence. Such systems will become an extension of ourselves, allowing us to be more productive and innovative—and our companies to be more profitable.