Can we really leave AI and machine learning to it so that we can ponder more strategic matters?

The slightest mention of AI and machine learning (ML) was enough to strike fear into the hearts of many not so long ago.

To be fair it’s not surprising, particularly given the cultural references we’ve been fed over the years – see Skynet (Terminator), Hal (2001: A Space Odyssey), and Ava (Ex-Machina) – it’s little wonder there’s been a smidgen of anxiety.

However, in recent times, technologists have started to acknowledge that AI and ML are actually good at automating the laborious processes we as humans and businesses can’t be bothered with – most of the time they do this more accurately too.

The question still remains though, do we really have anything to worry about when it comes to automating our working lives via ML and AI?

Taken on the findings of a recent PwC report, there’s still some substantial negativity among the general population when it comes to automation, with 60% of people believing that it will take their job (and there are further concerns raised when you start to mention the AI elements). That is really two questions in one though: can we automate everything, and can we make that a full end-to-end process?

Well, we automate for multiple reasons: repeatability, speed, parallelism and removal of operator error. All of these are great reasons; cloud computing followed that evolution only recently and now we have the ability to commission, configure, deploy and make available entire estates in minutes.

After all, whenever we see a branch of computing become popular, we seem to go through a similar curve of manual implementation; then often into a UI to make things easier; then into scripts that get things running manually (but repeatably); then into fully automated processes, and finally the automation of the quality gates around it.

In the last few years alone, we’ve seen that automation has branched out from the early automated builds and unit tests into Security, UI testing, infrastructure, deployment and even regulatory compliance to name a few. Not all of these branches of automation are currently leveraging AI, but over time I predict they will.

Of course, where there’s AI and automation, there’s always the worry that it will somehow “take our jobs”, when often the opposite is true (with a caveat), as when we can deliver more consistently, business value is unlocked sooner and programmes are more likely to succeed and expand.

Unfortunately, some jobs will become obsolete in the short term as a result of automation – the World Economic Forum predicts as many as 85 million in fact. However, according to the same research, 97 million new roles will also be created.

Automation in the form of RPA2.0 (which leverages AI and ML, hence the 2.