AI is management

When everyone works faster

Not so long ago, AI and automation were first and foremost a matter for IT and for the subject areas where the technology was to be used. A task was identified. A solution was found. It was automated. And then you moved on to the next one.

That picture has changed. AI has become mature enough that we no longer only use it to make the individual task or employee faster. We can now use AI to understand and redesign entire processes. And how we work, organize ourselves and solve our core tasks belongs on the management table.

Ask your employees if AI has made them faster. I think most people answer yes. They write faster, find information faster, analyze faster, produce faster. But when each individual employee works faster, the organization does not automatically follow suit. Because the work still needs to continue. From employee to employee. From department to department. From system to system.
And along the way you probably experience the same friction as before:

• The approval is still waiting with the person who is at the meeting.
• The case is still being sent back because an attachment is missing.
• The customer inquiry still changes hands three times.

No one necessarily does anything wrong. You just follow the process.
But AI has also started to deliver on the process, and that is where it really becomes interesting. We can build processes where people, systems, automation and AI work together in new ways. We can redesign the process rather than simply pacing up the pace of the one we have.

That is the decisive shift. The question was before: how do we solve this task faster? Now it reads: what should this process actually look like? And the last question belongs to the management group.

Management is about more than strategy

When we talk about leadership, we often talk about strategy. But management is also setting direction and framework for resources, processes, behavior and culture. All the mechanisms that make the organization move in the desired direction.

AI touches them all at once. Where should people spend their time when technology can take over or support parts of the work? How should work flow through the organization? And what do we reward when productivity is no longer just about how much the individual produces? The three questions look different, but they are the same: how will we organize the work of an organization where AI is part of the workforce?

Here, too, AI can help you

Perhaps you are thinking: how can I as a manager make decisions about the processes? I'm not an expert on them. You don't have to be either, and that is one of the most interesting things about the development we are in the middle of.

Historically, management has relied on reporting, process diagrams, workshops and employees' own descriptions to understand how the work takes place. The problem is that the work described and the actual work are rarely exactly the same.

Today, technology and AI can help us see as-is to a much greater extent, i.e. the process as it actually proceeds today. With access to the relevant data, we can analyze:

• Where does the waiting time occur?
• How many times does a case go back?
• How many variants are there of the same process?
• How many traditions are there?
• Where do employees spend time on coordination rather than the core task?
• Where do the exceptions occur?
• And what patterns hadn't we noticed ourselves?

In other words, we can put a glass plate over the business and look down on the work that is actually going on. What data shows, rather than what we think is going on and rather than what we once wrote down.

And we can start looking ahead

It doesn't stop at as-is. When we know how the process works today, AI can also be used to qualify possible to-be scenarios, i.e. suggestions for how it could look tomorrow:

• What if this approval disappeared?
• What if an AI agent handled the first sort?
• What if information was retrieved automatically instead of being re-typed?
• What if the case itself could route to the right employee?
• What if man only got involved when a professional assessment was needed?

Suddenly, process design becomes more than an exercise in drawing boxes and arrows. We can experiment with what the work could look like. And this is where technology really becomes a management tool. The value lies in the fact that management gets a much better basis for deciding how the organization should work.

The change also affects you

Then comes the part we might be talking about too little. When we change the way employees work, we also change their everyday life. It can be positive: less repetition, less waiting time, more time for the core task and new opportunities for professionalism.

It can also create uncertainty. Responsibility shifts. Tasks disappear or change character. New skills will be necessary. Collaborative relations change.

Here comes the management task again, because the change must be managed. Most people know that.
But dear leader: the change also affects you.

If the employees work differently, you cannot necessarily lead in the same way as before. If the processes become more self-driving, your need for control and coordination changes. If employees can obtain knowledge and sparring directly from AI, your role as a professional sparring partner will change. And moving more responsibility closer to the process, your way of following up changes. The AI change is therefore also a change in the management task itself.

If you haven't taken ownership yet

That's it now.

You must be able to ask the right questions. You can find the difference between models, agents and automations from others, the same applies to the choice of technology, and you certainly don't have to have all the answers yourself.

The questions are about like this:

• How will we work?
• What processes should we rethink?
• What skills should we have?
• What tasks must people continue to solve?
• Where should AI and automation take over?
• What does this mean for our culture, for well-being and for job satisfaction?
• And what does this mean for the way I have to look myself?

You don't need to first understand technology to take responsibility and succeed. You need to understand your organization. You must understand your people. You must set direction. And you must dare to rethink the way you work. Technology is already pushing the limit of what is possible. Now it is the management's job to decide what the organization will use that opportunity space for.

What would I do first?

I would start with one process. Not necessarily the biggest, but preferably one where you already know that it creaks between two or more departments. Get data on how it actually goes. Look at waiting time, backflow, handovers and exceptions. Look at what frustrates employees or customers and what creates value.

Then use AI and process insights to investigate possible new ways of working. And then take the discussion in the management team: if we were to design this process today, with the options we have now, what would it look like? And afterwards: what does it require of the organization, of the employees, and of us as managers?

Sandra Hoffmann is Senior Sales Specialist in KOLLAB and works, among other things, with AI adoption, process insight and competence building at Danish companies and organisations.