How smart machines will redefine the role of knowledge workers


Developments in technology and the advent of AI will fundamentally transform the role of knowledge workers, predicts Unit4 chief product officer Ivo Totev.

Cyber workers army needs you? © Tatiana Shepeleva - Fotolia.comThe more technology in business, the better – this is the common view. Different developments have so clearly transformed the ways we communicate, shop, share information and learn that there are many good reasons for the enthusiasm. However, what receives far less attention is how these new technologies impact workers and their productivity.

Technology and the knowledge worker

Knowledge workers take on many roles – so many in fact that in 2011, Businessweek suggested that everyone is a knowledge worker to a degree. Management writer Peter Drucker coined the term, describing knowledge workers as:

High-level employees who apply theoretical and analytical knowledge, acquired through formal education, to develop new products or services.

Clearly, communication technologies play an important role in the life of a knowledge worker, but the value of technology to such workers is more complex. For instance, modern technologies can automate repetitive tasks. This, in turn, has created a range of more cognitive work opportunities, such as the retail store owner who no longer has to manually take inventory but now works with an integrated inventory management and point-of-sale system.

Rise of the smart machines

The role of smart machines is growing. According to Gartner’s report, Top Strategic Predictions for 2016 and Beyond: The Future Is a Digital Thing, by 2018 more than three million workers will have a ‘robo-boss’ and nearly 50% of the fastest-growing companies will have more smart machines than employees. The research firm also predicts there will be six billion machines connected to the Internet and each of them will require support. It is a huge market. However, the manner in which these machines impact worker productivity is another story.

Trust is one of the biggest issues. While the effectiveness of these smart machines is certain, most people simply do not trust machines to do the proverbial ‘heavy lifting’. Repetitive tasks and simple automations, such as generating and emailing reports, may fall within most people’s comfort level. But trusting a smart machine to deliver your Amazon order is something very different. Take smart cars for example. Many people are resistant to trust an autonomous vehicle, even though, according to

A Virginia Tech University study commissioned by Google found that the company’s autonomous cars crashed 3.2 times per million miles compared with 4.2 times for human drivers.

For the near- and mid-term it’s more realistic that we might let smart machines and automated capabilities take the lead where outcomes are relatively clear. In this sense, newer technologies take on more of an augmentation role than one of automation, as Thomas H. Davenport and Julia Kirby explain in a recent Harvard Business Review article:

Automation starts with a baseline of what people do in a given job and subtracts from that. It deploys computers to chip away at the tasks humans perform as soon as those tasks can be codified. Augmentation, in contrast, means starting with what humans do today and figuring out how that work could be deepened rather than diminished by a greater use of machines.

This will change the role of the knowledge worker at a functional level.

Knowledge workers and AI

It has been widely acknowledged that replacing human sensibilities with tools and machines is nearly impossible, but there have been developments. Pervasive computing and the ability to collaborate at any time of day is giving rise to ‘humanoid robots’ – people who are directly connected to their devices through wearable technologies like Google Glass and smart watches – and smart machines that have artificial intelligence or AI-type capabilities.

As chief digital officer at IMS Health Richie Etwaru explains:

Artificial Intelligence (AI) will go beyond the reactive automation tools we have today into predictive automation tools, creating/replacing the ‘knowledge’ needed. I know what you are probably thinking, how many folks will lose their jobs to Artificial Intelligence? The answer is simple, none permanently. This was the exact fear we had at the beginning of the Industrial revolution … Manual jobs lost were replaced with upgraded knowledge jobs.

In other words, AI may mean that more complex tasks like installing or tweaking new software can be automated, and some predictive automation may be added on. This will surely make certain jobs obsolete, but it gives rise to a new class of careers: visionary workers.

While many workers did lose their jobs, many more found their work transformed. Granted, a pizza delivery driver may lose his position when a delivery drone is introduced, but that replacement gives rise to new jobs, like drone programmer or maintenance technician.

The face of knowledge work is changing. Developments in technology and the advent of AI will likely transform the role of the knowledge worker today, much in the same way the Industrial Revolution did away with much factory labor. Alex Stratis, research analyst at IDC says:

Jobs are going to be outdated and roles are going to disappear, but we should also be thinking what new things will develop. There’s a speech by Sir Kenneth Robinson, recipient of the Benjamin Franklin Medal of the Royal Society of Arts, that says that children today in education are going to be retiring in 2065 or 2070 and we don’t know what professions they’ll be going for, we don’t know what kind of job they’re going to be doing.

This uncertainty does not mean that AI is something to fear. Technology takes away tedious tasks and frees both time and resources that can be applied toward new developments, even for knowledge workers – and that is good for everyone.

This topic was discussed by a panel of industry thought leaders during a roundtable debate hosted by Unit4 at its annual Connect conference.

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