Pundits and analysts have warned that automation will devastate the job market. Much of their focus has been on repetitive, relatively straightforward jobs (such as some kinds of factory work) that a sophisticated machine could easily replace. But could tech pros with more complex roles end up supplanted by software? That’s a very big and scary question.
In late 2017, the McKinsey Global Institute issued a report suggesting that automation will leave many technology jobs relatively untouched. “Workers of the future will spend more time on activities that machines are less capable of, such as managing people, applying expertise, and communicating with others,” that report read. “The skills and capabilities required will also shift, requiring more social and emotional skills and more advanced cognitive capabilities, such as logical reasoning and creativity.”
Other studies have positioned automation as helping tech pros perform their jobs more effectively. For example, one study from Puppet demonstrated that automated tools had taken over roughly a third of testing and configuration-management duties from DevOps specialists, freeing them to pursue more proactive tasks.
But automation won’t prove a good thing for every tech pro. Many companies will look at these labor-saving tools and decide they can get by with smaller teams of technologists. While high performers will benefit from automation, it stands to reason that not everyone will survive when new, more sophisticated platforms come online. With that in mind, here are four tech jobs most at risk from automation and A.I.
For the past several years, various enterprise-centric software companies have focused on building tools that automate the maintenance of IT infrastructure. As those services go live, they reduce the need for IT infrastructure specialists and datacenter administrators. Whereas back in the day, a good rule of thumb was 100 servers per administrator, new software means a single administrator can manage thousands of servers.
Backups, provisioning virtual machines, and security are just three core processes that companies can leave largely up to software. In order to survive, datacenter administrators and sysadmins will need to become more interdisciplinary and creative; that includes learning to code. “When you really think about it everybody now needs to be a software developer,” Joshua McKenty, CTO and co-founder of Piston Cloud Computing, a provider of a distribution of the OpenStack cloud management framework, told Dice several years ago; that advice holds true today.
Help Desk Staff
Earlier this year, Google announced Duplex, an A.I. platform that will call up a restaurant and make a reservation for a user. At the time, Google claimed that it had no intention of expanding Duplex beyond that purpose—at least for the time being.
However, Google is hard at work on a similar system, Contact Center AI, which it brands as an “enhancement” to call-center employees. “We’re working with several of our Contact Center AI partners—including Appian, Chatbase, Cisco, Five9, Genesys, Mitel, Quantiphi, RingCentral, Twilio, UiPath, Upwire, and Vonage—to engage with us around the responsible use of Cloud AI,” read the company’s blog posting on the technology. “This includes best practices such as disclosing when customers are talking to a bot, and education around issues such as unconscious bias and the future of work.”
Talk of “responsibility” aside, it stands to reason that if Google (or any other tech firm, such as IBM) can create an automated assistant with human-like speech, companies will use that to eliminate call-center staff. That’s potentially bad news for help-desk workers, who may find their numbers exponentially reduced by software. However, it may take several years for A.I. to reach a level of sophistication where it can take over any and all customer inquiries (particularly for tech-related issues, which can prove hard to diagnose and solve).
“Are programmers immune from automation?” is one of those long-running debates in tech. Some pundits argue that programming demands a level of creativity and intuition that machines can’t replicate; others insist that the bulk of programming is fairly rote, to the point where automation can take over for many types of coding.
Which side is right? It’s hard to tell at this juncture, although early signs indicate that programming is a ripe target for some kinds of automation. The rise of no- and low-code application builders is just one facet of this evolution; in theory, future software platforms will be able to assemble relatively simple programs with just a few mouse-clicks.
Whether or not programming becomes more automated, the key to surviving as a programmer is to develop skills beyond coding (no matter your skill level). If you can demonstrate incredible problem-solving and critical thinking skills, and pair that with solid emotional intelligence and the ability to collaborate with others, you could make yourself into an invaluable team leader and a strategist. One of the surest defenses against the rise of automation is solid “soft skills.”
This one is a bit more of a stretch, but it’s theoretically possible that data-analytics platforms, enhanced by machine learning, could begin to replace human data analysts. Instead of having a dedicated person to analyze in-house data, businesses could rely on this software in conjunction with employees who receive some training in data analysis.
Again, this is a wilder prediction, if only because research firms generally suggest that the need for data analysts (and data scientists) will greatly exceed demand in coming years, no matter how sophisticated data-analytics tools actually become. But it’s not outside the realm of possibility that “smart tools” could replace the need to hire a “data person” at many firms, particularly those that don’t need quite as much in terms of data analysis.