There’s a lot of talk about how employees can boost their productivity and effectiveness by handing routine tasks to generative AI. Doing so frees up employees to spend time on activities where humans excel—like innovating, strategizing, and building connections.

What’s often missing from the conversations is that as gen AI changes how employees work and what they work on, it’s also changing how managers must lead.

Here’s why traditional management practices are becoming obsolete in the gen AI era and how managers can evolve to create more meaningful and productive work environments.

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The evolution of management practices

Before talking about where we are now, let’s briefly recap how we got here.

For generations, managers believed the best way to ensure employees were working was to see them sitting at their desks or on the production line. The general belief was that people in seats equated to work being done. Presence was prized over productivity and managers often rewarded those who showed up early and stayed late.

Then COVID shut down offices and scattered employees to work from their respective homes. Managers couldn’t see who was at their desks anymore, so they quickly learned to focus on outcomes. In outcome-based management, success is measured by performance, not presence. Managers give employees clear goals and workers enjoy more autonomy over how they get work done.

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Innovative companies took outcome-based management a step further through taskification. They broke work down into smaller tasks and then distributed the tasks among employees, freelancers, and automation. By doing so, teams immediately gained capabilities, agility, and speed.

If you haven’t practiced taskification yet, it’s time to catch up fast. Jobs are being disrupted again in 2024, forcing managers to adapt once more.

Part of the disruption is caused by the increasing use of gen AI across a wider sweep of roles. Remote work is still popular so leaders must still manage by outcomes, but with a twist. Gen AI is changing the nature of work so much that leaders must also focus on managing by taskification and connection.

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Look beyond productivity gains

The need for taskification and connection becomes clear when you look beyond using gen AI for productivity gains.

Many people think of gen AI as a computer, but it’s not. Gen AI is a large language model. Think of computers as an accurate calculator. When you give it a pile of things to compute, it’ll give you accurate answers in return.

However, gen AI works like a human brain. Like a human, gen AI makes mistakes. It has a faulty memory and can make errors when given lots of calculations. What gen AI is great at being is a tireless work buddy, a work buddy that could completely redefine jobs in a good way.

Let’s look at the middle manager role as an illustration.

The most important thing middle managers do is develop people. Yet research by Capterra shows managers are so bogged down with other tasks that less than half of their time is spent working with their team members.

Bryan Hancock, Global Talent Leader at McKinsey, believes middle managers are victims of bureaucracy. He explained in an interview, “No one woke up in their career and said, ‘Hey, I want to make sure you’ve got the four right forms and this filled out in the right way.’ It’s the processes and controls and ways of working that put middle managers in that area. What middle managers want is more time to take ideas into the world. They want to spend more time coaching team members and less time approving travel.”

Your work buddy, gen AI, can help make that happen by automating administrative tasks. This leaves managers more time to spend developing people. For that to happen, managers must hone their taskification skills. Yes this sounds like a productivity play, and it is. But that’s not all.

The true power of gen AI lets loose when you shift your thinking to understand that…

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Gen AI isn’t digital transformation. It’s change management

Continuing with the earlier example, high performers have traditionally been the ones promoted to middle managers. However, people who are great at their individual jobs are not necessarily good at managing people.

Once you taskify and use gen AI to remove the busywork, you won’t need great admins to manage forms anymore. You will need great coaches to develop people. This means you’ll have to redefine who qualifies as a manager, what their tasks are, and how you measure their success.

All of these changes will create more quality one-on-one time between managers and their team members, which benefits the business. Studies show that the more quality time employees have with their bosses, the better their relationship. The stronger the relationship, the better the employee and the company perform.

In managing an AI-powered workforce, the question isn’t how can I increase productivity? If you want to optimize human potential, ask, how can I build stronger people connections? Answer that well and the productivity gains will naturally follow.

Take attorneys for example.

A new law associate usually puts in long, punishing workdays for four to six years before they crawl up the ranks to become a senior associate. A first-year associate spends their first year researching cases and reviewing and drafting documents. Each year, they do more researching, reviewing, and drafting. Second- and third-year associates may start attending client meetings, strategy sessions, and court proceedings. By their fifth year, they may have learned enough to handle cases on their own.

What if gen AI could pull together research, summarize reviews, and provide initial drafts for documents? That would fast-track how quickly associates learn, so they can begin developing client relationships and attending strategy sessions sooner.

You’re using gen AI to give employees superpowers so they can do what they do best: think, create, empathize, and connect.

Instead of working for five to six years before handling their first case, associates may have the knowledge and skills for independent work within their second or third year. Perhaps law firms may not need four-, five-, and six-year associates anymore. Associates could rise to those levels and provide more value to the company and clients in a fraction of the time.

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Rethink jobs to leverage human skills

Taskifying jobs is so vital for keeping up with changing business demands that the skill has moved firmly from a nice-to-have to a must-have in every business.

But as mentioned earlier, taskification is just part of a successful manager’s focus in the age of gen AI. The second part is building connections. This requires seeking ways to use gen AI to give humans superpowers beyond productivity. Here are a few ways to do that.

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1. Use gen AI as a tireless work buddy

Get creative here and keep the focus on how gen AI can free employees to tap into their strengths. For instance, doctors spend hours a week on paperwork, which gives them less quality time connecting with patients. This negatively impacts patient satisfaction rates.

Gen AI could cut admin time by generating clinical notes from patient-doctor conversations, so the doctor can make more meaningful eye contact during a patient visit, instead of spending their time typing into a computer. Gen AI could also improve patient experieces by reminding the doctor that a patient is retiring this month and then drafting a quick congratulatory email for the doctor to send.

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2. Preserve the job’s meaning

Kelly Monahan, Managing Director of Upwork Research Institute, is 100% behind gaining agility and efficiency through taskification. However, she has one caveat: Taskify in a way that increases, or at least maintains, meaning in the employee’s job.

“Make sure we don’t go back to the industrial era where people become so specialized on one particular task within the organization that they lose sight of the bigger picture,” suggests Monahan in an interview. “What constitutes meaningful work is being able to see the big picture and realizing how your contribution makes a difference.”

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3. Redefine and recast roles

When gen AI removes the busywork from a role, it may change the skills required to do the job. So be sure to think through how applying the software will redefine a role and what success looks like. Then update the job description and the skills required to do it.

You’ll also need to create new roles that don’t exist now because you always need humans behind the AI. You’ll need people to create a system that fits into your processes, people to wrap safety and ethics guidelines around it, and people to manage its use and fix it when it breaks.

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4. Make time for formal training

Research by Asana’s Work Innovation Lab shows that most employees (56%) are taking it upon themselves to figure out how to apply AI at work. Their initiative is commendable, but companies should shoulder part of the responsibility. Not only is providing formal AI training, development, and experimentation at work the right thing to do, but it also:

• Makes it easier to monitor and manage the safe usage of AI and encourages adoption.
• Aligns with how employees prefer to learn.
• Improves worker satisfaction when tied to upskilling opportunities.
• Encourages employees to use AI regularly, which leads to higher productivity gains.

This article originally appeared on Upwork.com Resource Center (Upwork is a company that helps businesses find talent and people find work) and was syndicated by MediaFeed.org.

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