How AI Will Transform the Future of Work in IT

Taking central stage as a conversation topic for businesspersons, techies, and politicians alike, the role of artificial intelligence has become a controversial topic with many theories on how it will impact work. To some, AI appears to be a holy grail, unlocking productivity and letting people focus on putting their creativity to a more just use, while to others it appears to paint a dystopian picture of the world. As AI takes hold in IT and DevOps, as well as in IT processes, we believe there is one fundamental shift IT jobs are headed towards.

The Barriers to Entry

In today’s age, coding is hailed as the equivalent of literacy and is becoming an ever-increasing priority for students and professionals alike. Though the message is pervasive that future jobs will require everyone to code, we think that view is bit extreme and can’t be generalized across all sectors. However, in IT one analogy applies: those who have tech expertise and those who don’t are like the haves and have nots.

Since the Dotcom bubble, developers have been idolized as the most valuable resources in an organization and are treated as such, leaving teams that support developers—like manual testers, business analysts, and technical writers—to be overlooked. Consequently, people in these roles are becoming discontented, often learning to code halfway through a career to keep up.

Explosive Complexity in IT Systems

While today’s workforce is becoming more technical to keep up with the demands of the rapidly changing IT landscape, the reality is that application landscapes have grown in size and complexity at an accelerating rate, with teams having to manage more moving parts than ever before, many of which they don’t control.

To solve these problems, companies will need to build or adopt products that abstract many of the tasks we deem value-add, turning to new technologies like AI to simplify and scale the jobs that development teams do today and avoid getting bogged down by these systems. We already see the seeds of this change taking place in the adoption of cloud technologies and DevOps initiatives. And just like we don’t see modern IT jobs centering around kernel development, the majority of future IT jobs won’t focus on writing code but on managing large software factories. IT has no choice but to move away from handcrafted, unmaintainable systems into industrial software development teams. In order to get there, intelligent systems akin to software factories must lead the way and change the type of work teams do.

Redefining Jobs and Converging Roles

To enable the software factories of the future, jobs will need to morph to keep up; however, they won’t be purely coding based. Rather, they will focus on managing large systems and understanding how the system works, using an intelligent system to focus on outcomes and not tasks. Jobs will require both a rudimentary idea of how computers work and some technical expertise. The leverage that great processes and scalable technology create will have a powerful impact, enabling teams to pair great developers with lean but savvy operations teams, dramatically simplifying the development process and allowing it to scale.

The technology fabric that weaves together these business and operations jobs will be powered by an artificial intelligence that allows teams to redefine value-added activity—from building software well to creating well-designed and smart systems that scales over many platforms. Many jobs we see today will converge into a few roles that are not based on tasks but on knowledge.

Let’s look at a concrete example of how autonomous testing is impacting the role of testing.

  1. Low code: Our system only requires the user to have a basic understanding of how requirements need to translate into user stories, eliminating the need to write hundreds of lines of code every day to test. Instead, users interact with the intelligent system, telling the machine what to do and letting it do the hard work.
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  2. Smart Systems: Because the system is intelligent, people aren’t writing code, spending time reworking the system, or applying maintenance today by looking for other places to test. Moreover, they act in tandem with the rest of IT’s processes, having the context from triggering new builds to knowing what to maintain.
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  3. More Participation: As AI bridges the technical gap required in many jobs, more people will add tremendous value to development teams without needing to have a computer science PhD. In the case of autonomous testing, developers, BAs, and product managers alike can be more productive than the best automation engineers on the market today. Those great at understanding quality can fully test software, great automation engineers can focus on developing more critical applications, and great teams can let intelligent systems eliminate a critical bottleneck and focus their precious time on the critical details without getting lost in the noise.

As AI-powered intelligent systems begin to take hold across the development life-cycle, enterprises will evolve to keep up and focus on attracting the right talent to lead the way, transforming the skills of their workforce to scale up intelligent systems, focusing on outcomes rather than activity.