More tasks in organizations are being automated these days, including in IT. Automation and autonomous systems aren't synonymous, though. Autonomous systems are a subset of automation, but people tend to confuse the terms. Understanding the impact of autonomous systems on the IT group first requires a clear understanding of what those systems are.
For example, the Oracle Autonomous Database is just one product that could disrupt at least part of IT's status quo because it does three things autonomously: self-management, self-security, and self-repair. Collectively, those things reduce the need for IT to apply patches, managing databases and infrastructure so DBAs and others who used to perform such tasks have more time to improve data models, work with developers to improve database access, drive more value from data, etc. (For the purposes of full disclosure, this author does some work with Oracle).
For example, the big selling point for any type of automation is eliminating or minimizing human error. A lot of IT automation is happening in the cloud today, so the general cloud benefits apply: manual management is minimal, cloud provides higher reliability than in-house data centers, operational efficiency improves and, usually, total cost of ownership (TCO) is lower. Cloud can also provide better security than on-premises equivalents, albeit not inherently as part of a basic service.
What differentiates autonomous systems from more traditional forms of automation is machine learning. However, PwC New Services and Emerging Technology Leader for China, Japan and the U.S. Scott Likens said in an interview that most people still think of autonomous systems as business-rule programmable.
Understanding the spectrum of automation is wise because marketers will use the terms "automation" and "autonomous systems" interchangeably either intentionally or by mistake. It's therefore important to validate and verify vendors' claims to truly understand the potential impact of their products on IT. Responsible consultants do that, and it's one reason why enterprises hire them to help with automation initiatives or other initiatives involving automation.
So, what's so special about autonomous systems?
A lot of traditional automation and robotic process automation (RPA) are accomplished using business rules, so it's understandable why people might think the same concept applies to autonomous systems.
Self-repair is one example of an autonomous system feature: the system identifies an issue or the high probability of a potentially imminent issue, and just deals with it. The operation may be transparent enough that humans remain blissfully unaware of what is actually happening. In their view, the database just works.
"I think there are few autonomous systems [today]. It’s more automation strung together versus true autonomous systems that are smart enough to adjust and adapt themselves," said Likens. "We’re seeing a lot of momentum and we’re doing this ourselves, having autonomous bots look at how to optimize other bots. Automations are great, but you have to optimize those and you have to autonomously do that or you’re still waiting for a human."
While automation in all of its forms, including autonomous systems, reduces the need for humans to do rote, repeatable tasks, the impact of those systems is not a static. As machine intelligence continues to improve, automated and autonomous systems will become more sophisticated which means humans will have to adapt.
Why IT teams should consider their value proposition, again
Given that the only constant is change, it's important for IT leaders and professionals to reevaluate the value they bring as an organization and as individuals periodically. Just about every new technology or methodology has some impact on IT whether it's creating new positions, eliminating old ones or both. Autonomous systems are no different. However, automation tends to be a more career-threatening topic than some other IT-related topics.
David Armendariz, technology division general manager at executive search firm Lucas Group recommends IT leaders work with their teams on "succession planning."
"If I were an IT leader, I'd plan for consolidation and hope people are ready to grow so as we consolidate, they have places to move," said Armendariz. "It may be outside of IT and may involve data-related, business intelligence, or new roles."
Not everyone whose job is impacted by autonomous systems will want to make a horizontal or lateral move to a different role, but many will. When it comes to one’s own career, Armendariz recommends keeping an open mind.
For example, someone with “traditional” IT skills who does not want to move into a different or evolved position might consider putting their skills to work on a contract basis versus reinventing themselves just to keep working for the same employer.
Recruiters should also endeavor to look at available positions and the available talent pool creatively.
"A lot of the focus for us is where we can take humans out to create better quality and you have to do it autonomously or else you don’t get the true value out of it," said PwC's Likens. “I think it's changing from more process-driven skill sets to more optimization-type skillsets which you really didn't have in IT before. There are more engineering skills, so you’re starting to see that blend of data science and mathematics coming into IT to try and solve some of those problems."
The time to plan is now
The automation trend is going to continue and it’s going to get increasingly intelligent to the point of more autonomous systems becoming available. They’re not taking IT by storm yet, but we’ll see more types of autonomous systems in the future.
"We’re doing a lot of research about the workforce of the future, but there's this shift in skills. In general, everyone's digital IQ has to raise," said Likens. "I think is good for humans and society, kind of moving out to that next level of creativity or insights based on what the machines are doing."
Right now, cost is driving the race toward more types of automation, but cost savings alone aren't what make a strategic difference. It's investing the money saved in innovation and new business models.
"Autonomy is going to happen. Self-driving cars are going to change transport, so I think there’s something around this mesh of networks, IoT, cloud. There’s something really happening there we have to recognize and embrace," said Likens.
For more about AI, machine learning and automation, check out these recent articles.Lisa Morgan is a freelance writer who covers big data and BI for InformationWeek. She has contributed articles, reports, and other types of content to various publications and sites ranging from SD Times to the Economist Intelligent Unit. Frequent areas of coverage include ... View Full Bio