Many argue that artificial intelligence (AI) is the new electricity. This domain of technology promises to achieve business efficiencies comparable to those obtained when the great factories of the 20th century went online with electrical power at the end of the second industrial revolution.
The similarities between artificial intelligence and electricity are evident. Both provide new power to business processes by reducing the amount of energy necessary in different parts of a production or value chain. However, where access to electrical power caused an approximately linear displacement of manual labor, the potential business impact of AI is more complex and pervasive.
And where power could be connected to a production process and create value at the flick of a switch, AI needs leadership in order to make its mark.
MIT professor Erik Brynjolfsson makes the following statement on what prevents a faster implementation of AI in businesses, in a recent interview with The Wall Street Journal (1.3.18):
It is not because the technology is lagging. It really has to do with the organizational side, the culture, and the co-invention of business processes that takes a lot longer.
In other words – the implementation of AI in business is closely linked to leadership.
The leadership factor
Leadership itself will likely not be automated anytime soon. But those leaders who successfully apply AI technology in their businesses will probably replace those who don’t.
So, what leadership skills are essential for a successful paradigm shift?
I believe that those leaders who manage to combine the right mix of technological insight, empathy and business understanding, provide the best conditions for a successful integration of new technology and human resources.
A competent business understanding is essential, because AI is well equipped to replace and automate some business tasks and processes. It is a primary goal for any leader to establish a deep understanding of how the business processes relate to each other and to identify possible and suitable targets for automation. However, real leadership entails something beyond good analytical skills and a thorough business understanding. Authentic leadership involves human insight, the ability to put oneself in the shoes of others and understanding the interplay between the technical and human resources in the workspace.
When aiming to replace human efforts with machine learning in a given business process, one will initially need to reinforce a formalization of employees’ behaviors and task execution.
This lies at the core of artificial intelligence – algorithms need well-sorted data to deliver.
The initial phase of automation, i.e. streamlining work tasks and sorting information according to strict protocols, requires a strong degree of formalization on workflow. This in order to reduce unwanted noise in the data sets constituting the very foundation of the automation process.
There has been a great deal of research on the impact of a high degree of formalization of behavioral- and task execution and the findings are not uplifting. A high degree of behavioral regulation is related to a reduced inner motivation, lack of happiness, resistance to innovation and a higher degree of job absence and turnover.
In her excellent book “Strategic competence leadership”, Professor Linda Lai points to these findings, and provides the following statement:
In a knowledge-driven organization there is also a limit to how far the standardization of tasks can go without also expressing that human competence and judgement is no longer needed.
Right here is the challenge which at heart is fundamentally different from what previous industrial revolutions the past century have presented*. The difference rests at the high level of knowledge that is currently going through massive changes. At the brink of the fourth industrial revolution, with AI leading the charge, not only jobs within manufacturing carries a risk of displacement, but also knowledge-heavy jobs within health, law and accounting.
Are you an empathetic leader?
Here is where the significance of empathetic leadership comes into play. Empathy is the stepping-stone of the type of sensitive communication needed to counter the challenge presented in the quote from Linda Lai a few paragraphs earlier. The challenge is to initiate a process of change requiring a strong degree of standardization – while not creating the impression that competence and judgement are not needed.
This requires managers who possess technological expertise, business understanding and empathy.
The latter is critical; how else could one successfully embed and implement a process of change which in its essence threatens jobs and in some work tasks removes the human touch altogether?
Competence and judgement will still be critical ingredients for the integration of AI operations with human resources in a business setting.
In 2008, alongside American author, inventor and futurist Ray Kurzweil, engineer and physician Peter Diamandis co-founded Singularity University. This is an interdisciplinary University with a mission to assemble, educate and inspire leaders who strive to understand and facilitate the development of exponentially advancing technologies to address humanity’s greatest challenges.
Peter Diamandis, Executive Chairman, emphasizes the importance of human competence in the initial phase of artificial intelligence. He singles out the ability of AI to provide great solutions to complex workflows armed with huge amounts of data, while making sure to point out the perspective that AI still, and in many years ahead, will be unable to ask the right questions.
We will still need a human touch in the shape of curiosity, insight, creativity and judgment.
* The large scale industrial implementation of electricity also lead to a displacement of labor, but this displacement primarily took place within manufacturing, took a relatively long time to roll out globally and had quite a few positive health effects with the elimination of hazardous works tasks. The electrification of manufacturing mainly targeted blue-collar jobs, like globalization made short order with the same type of jobs in the US the past decade.
** I am asking this question to a future form of artificial intelligence, which hopefully will be answered with a loud and clear “yes” in the next 10-15 years.