A Tale Of Robots: From Assembly Lines To Knowledge Workers

Anders Liu-Lindberg

Part 4 in the “RPA and AI in Finance” series, which examines the role that robotic process automation and artificial intelligence can play in finance operations

Once upon a time, there was a robot standing at an assembly line. It knew its part in the process and executed only what it was told. It had many ideas on how to improve the assembly process that could lead to higher quality products made faster. However, no one wanted to listen – until one day, when the factory owner got so tired of endless breakdowns and faulty products and said to the robot standing at the assembly line:

Today begins a new era, one where I will listen to your input and use what you have learned about assembling my product to make improvements. Not only that, I expect you to constantly learn and propose even better ways of doing things. I set you free to improve quality and productivity.

After that, the robot went on to make many improvements and kept surprising the owner with its ability to innovate. The robot had truly transformed from a worker standing at the assembly line, doing its part of the process, to a knowledge worker that keeps learning and doing things even better.

A tale of robots!?! What has that got to do with anything?

You see, this story shows the difference between robotic process automation (RPA) and artificial intelligence (AI). An RPA robot will execute its part of the process or, in the case of end-to-end process automation, a robot will do its small part and form a line of assembly workers to complete the process. They don’t learn. They don’t make improvements. They do only what you tell them to do. With an AI robot, it’s different. This robot will, once you’ve trained it in your process or model, only become better at it. As it learns, it will find the most efficient way of executing the process.

This tale marks the passing in our series from RPA to how to succeed with AI. The next few blogs in this series are a co-creation with Thomas Schultz from Enversion, an AI company based in Denmark. As one of the leading countries in the world for government-mandated electronic invoicing, Denmark is the ideal place to explore the limits of present AI technology and computing power.

We will introduce you to a model of working with AI and take a deep dive into each of the steps. Our ambition is to help you succeed with AI in whichever shape or form you’re considering using it.

A way of working with AI that’ll help you succeed

First, we’ll introduce the model, which consists of five steps. Granted, this model might not be unique to working with AI, yet it’s a prerequisite for increasing your success rate.

  1. If your solution is not solving any business pains, you likely won’t have the perseverance to see it through. Also, gaining support for using AI for the intended purposes will likely not happen.
  1. Choose specific projects, as opposed to just creating a strategy based on using AI for all sorts of different purposes. If you can’t be specific about where and how you’ll use it, you’re just not ready yet.
  1. Explain in simple terms how your AI solution will work. If you can’t explain it like this, you’re also not ready.
  1. Now that we’ve established that you’re ready, you can’t embark on the project with just any Tom, Dick, or Harry. You must reference-check the partners you intend to work with.
  1. Having found the pain to solve, selected the specific projects to work on, done the simple feasibility study, and found the right partner, it’s now time to brace yourself. It’s going to be a long and bumpy ride but, in the end, you’ll succeed because you took all the right steps to get there.

How does this sound to you? Reasonable? Too simple? Well, try it for yourself and let us know how the model works.

This works for finance, too!

In the finance function, there are plenty of projects to choose from. Essentially, pains are everywhere: your cash and bank setup; month-end reporting, including management reporting; or advanced analytics, where smart models are the need of the hour. And as an individual working in the finance function, try to reflect on the “Tale of Robots.” You’ll see that the robots are undergoing the same development we humans did. That means that as the robots develop, we must, too. With AI entering the finance function, you must find a new platform from which you can grow and still have a thriving career. That could be technical accounting or business partnering. Are you ready to begin your own journey?

It might have started with RPA, but AI is coming at us fast, and its entry into all business functions is inevitable. The question is: How are you going to get started? We will lay out the details of the individual steps in the coming weeks to prepare you for successfully working with AI. If you’ve already had some success, why don’t you share your story with us?

Take a look back at previous blogs in our “RPA and AI in Finance” series to learn more about how AI is changing the finance function.

This article originally appeared on LinkedIn and is republished by permission.


Anders Liu-Lindberg

About Anders Liu-Lindberg

Anders Liu-Lindberg is the head of the Global Finance Program Management Office at Maersk and has more than 10 years of experience working with finance at Maersk, both in Denmark and abroad. Anders is also the co-founder of the Business Partnering Institute and owner of the largest group dedicated to finance business partnering on LinkedIn, with close to 5,000 members. His main goal at Maersk is to create a world-class finance function not least when it comes to business partnering. He is the co-author of the book “Skab Værdi Som Finansiel Forretningspartner” and a long-time finance blogger with 20,000+ followers.