Gartner: 69% of Routine Manager Tasks to Be Automated within Four to Five Years
February 18, 2020 / Bryan Reynolds
Reading Time: 7 minutes
In a recent announcement, research and digital insights firm Gartner made a bold prediction. The firm expects that artificial intelligence-powered technologies like chatbots and virtual assistants will take on as much as 69% of the average manager’s routine work within just four to five years.
This is a bold claim with a lot of implications to unpack. It also strikes various people in different ways. If you’re working for a manager you can’t stand, the prospects of replacing him or her with a robot might strike glee in your heart. On the other side of the coin, if you’re a manager, this might not sound like fully welcoming news.
The reality of the situation is somewhere in the middle, though.
Freedom from Management? Not Quite
First, let’s talk about the workers’ perspective. Is the coming AI revolution going to dispose of your oppressive manager, finally freeing you from their grasp? Will you report only to a benevolent artificial intelligence that renders fair, impartial judgments, free from human biases?
We hate to break it to you, but no. That’s not likely to happen. The tasks that will get automated are mostly the ones we’d describe as “busy work” today: the stuff that your manager could outsource to an assistant if the budget would allow.
The high-creativity work, which includes the very human act of making ambiguous decisions and choosing between competing viewpoints, continues to elude AI applications. We have every expectation that human managers will retain this work. That’s great news if you love your boss’s decision-making ability (and less great if you don’t).
Not Exactly the Manager Apocalypse
For the managers reading this, you might be tempted to panic when you hear stats like this. Are the robots really going to take over nearly seven in 10 management roles by 2024?
No, not hardly. There’s no need to panic; this isn’t exactly the manager apocalypse.
Make sure to notice the details. Gartner isn’t predicting that 69% of managers will be automated. Nor is the prediction that 69% of all manager responsibilities will be automated.
No, the prediction is focused on routine tasks only. These are things like approving workflows and completing forms. Today’s managers complete many repetitious tasks on a daily, weekly or monthly basis. The ones that don’t require much thought or effort are ripe for automation. And as AI-powered tools continue to increase in capability, more of these tasks than we might expect will start being automated.
Gartner has done plenty of research in the past about what sorts of roles will be affected by AI in the coming years. Job types with high predictability and low “social-creative skills needed” are the most ripe for automation.
Of course, most managerial roles have elements that are both unpredictable and that need significant social-creative skills. Managers who focus here and do well in these areas will always find somewhere to land.
Some Managers Won’t Survive the Transition
The robots aren’t coming for all manager jobs, but that doesn’t mean that all managers are safe.
As AI-powered tools begin automating routine managerial tasks, managers will have more capacity to, well, manage people and processes. And the more capacity individual managers have to do the human side of managing, the fewer managers an organization may need. We may see a redistribution of manager responsibilities, along with a natural culling or attrition of lower-performing managers.
New responsibilities are emerging, too. Someone will need to monitor and provide quality assurance on the work done by AI-powered tools. Managers will probably retain this responsibility: if the tasks were deemed management-level important before the AI transformation, then the results will probably still be deemed a management responsibility.
Another aspect of this point is that not all managers operate the same way or have the same responsibilities.
Some managers got promoted because they were especially high performers. They get stuff done! When given the freedom, these managers tend to gravitate toward measurable tasks and away from soft-skills work.
These are the managers whose jobs could be in jeopardy. If you’re known for completing tasks more than you’re known for engineering creative solutions to problems, you could see those tasks gradually transitioned to AI-powered tools in the next four to five years.
Other managers got promoted because they demonstrated creative thinking or strong people skills. These managers, when given the chance, likely gravitate toward those creative and soft skill tasks.
AI is a long way off from being competitive in these areas. We predict managers who build a name for themselves with their creative problem solving and strong soft skills will be the safest through the upcoming transition.
Which Tasks Will Be Automated?
So which tasks do we expect will become automated in the next four or five years? No one can say with certainty, of course, but here are our top predictions. Remember the chart up above. Anything with high predictability and low social-creative skills needed is a good candidate.
Below you’ll find some of our top predictions. All but the last generally fall into the category of robotic process automation, or RPA. Using a computer (the “robot” in “robotic”) to automatically take care of repetitive tasks is something we’re already seeing. There are tons of advantages, from accuracy and productivity gains to reliability and even compliance.
As AI-powered RPA tools become more and more powerful, we expect to see them play a bigger role for companies in areas like the following. Here are the management tasks we expect will be largely automated by 2024.
Using AI-powered tech tools to help with processing forms is already here, and it’s a safe bet that in the next five years those tools will take over most or all forms processing in many industries.
It’s easy to understand why. Processing forms is a highly predictable, repetitive task that requires little creativity. Yet in most situations accuracy is at a premium.
This is precisely the sort of situation where humans tend to do poorly compared to machines. Papers get lost on desks or misplaced. A typo in someone’s name on a legal or financial document can cause untold frustration and delays. Handwriting gets messier as the day wears on. Even transposing the data from two lines—something that’s easy for a human in a hurry to do—can create massive problems down the line.
None of these mistakes are common for computers. Some aren’t even possible. As AI-powered tools get smarter about some of the details (like supplying a missing name based on other database matches), expect form processing to become more and more automated.
If you’ve ever dealt with an approval workflow, you’re probably glad to see it on this list. How many of us have dealt with an old-fashioned paper approval process that mysteriously vanished in transit, or sat on someone’s desk for two weeks while they were on vacation?
There’s already a better way than that. There are already technology tools like Microsoft Power Automate (formerly known as Flow) that help to digitize and partially automate the approval process, say, for project charters or new initiatives.
Look for artificial intelligence-powered tools to take the lead on approval workflows. All that’s left to the managers is the reviewing and signing.
Manually Updating Information
Another frequent task of department managers is manually updating information. This could be in internal documentation or in databases, among a host of other possibilities. In most situations, these manual updates are necessary instances that occur sporadically. It’s best to trust one person with the responsibility, and managers often end up with the job.
It makes sense that this is a human task. It’s not terribly hard for a person to open up a database, check an entry to make sure it matches another source, and then make a judgment call about which one is likely more accurate. The first two steps are easy for computers, too. But the last one—making a judgment call in ambiguous situations—is tough.
AI advancements are making it more and more possible to automate this kind of task. By evaluating contextual information (and by processing millions of similar evaluations using machine learning), AI-powered tools are getting much more accurate at these decisions. It’s a safe guess that within five years, we’ll be comfortable trusting AI with these decisions.
Many companies still rely heavily on people to receive, scan, retrieve information from, and eventually store documents. And people have all the same issues here that they do with processing forms (discussed above).
The truth is there are already document management software solutions that can automate much of this process. They can take a user’s scanned document, extract information to predefined database locations, and then tag and file the form.
Put in place a system that can run that workflow automatically when receiving a digital file, and you’ve already pretty much removed the human from the equation.
Yes, humans (especially managers) will continue to play a role in quality assurance, but overall time spent will be greatly diminished.
In most modern payroll systems, the manager’s role in approving payroll has already been greatly simplified. Within a few years, expect AI-powered tools to provide the option of intelligently analyzing timesheets and other payroll documents, generating manager prompts only for unusual situations.
In this example, managers will still have the ability to go in and evaluate payroll issues—there are human resources reasons why managers need this kind of access. But technology can automate much of the process, once again saving time in routine situations.
One job that falls to many managers is analyzing data in some form and charting a course of action based on that data. This data may look like a report, sales information, assembly line efficiency numbers— you name it. There are plenty of situations where someone needs to make a decision, and it usually ends up being the boss.
The only problem? Most people aren’t very good at analyzing data, especially when you consider that today’s applications are generating far more data than ever before.
Analyzing large amounts of data is something that computers are great at. They can move far more quickly through well-organized information than humans can, and they can do it with far more accuracy.
We’re already seeing AI-powered machine learning tools revolutionize data processing and analytics (check out our whole series of blog posts on AI in business if you’re interested), and this trend will continue strongly over the next five years. The capabilities available today will pale in comparison to what AI will be able to do in five years in the area of data analysis.
Where AI, bots, and not-yet-invented automation solutions will ultimately take us remains to be seen. And of course, the workplace overall will continue to evolve along with the technology that’s powering it. If you need a partner for the journey, Baytech Consulting is here for you. Whatever software needs you have, get in touch to see how we can help.