.... and the new skills they will acquire !
Our research and discussions on the subject of Artificial Intelligence projects have led us to consider three challenges that frequently arise in organizations that have implemented this new technology. Linked to these challenges is a shift in managerial skills, as described by L. Giraud in an article in Management et Avenir1. These challenges should be seen as a valuable opportunity to upgrade managers' skills. Addressing them from the outset of the transformation process can also accelerate the creation of value for the company.
1. Reorganize your team and create value
The first challenge is to create value. Socially, this is not the time for job destruction, which would be frowned upon. Managers and their teams need to find ways of creating value, drawing on human qualities such as creativity, collaboration and problem-solving.
The first step is toabandon yesterday's profession and entrust tasks to AI. This means abandoning the quest for perfection, which neither man nor AI has ever achieved, and settling for an efficient result. It's time to transform activities, rethink or define "new professions" and redistribute roles. Secondly, the team can look for ways to improve and create value through cooperation and customer service.
It's a time for appropriating new organizations and developing skills in organizational change management, innovation, communication and collaboration.
2. Man-machine collaboration
The second challenge is that managers have to deal with a multi-disciplinary team, at least in functional terms. Indeed, with AI, he or she is integrating AI specialists alongside his or her business collaborators. From data-scientists who will ensure the quality of the data retrieved, and maintain and advance the algorithms used by AI.
Everyone's operating methods and priorities are different, even if their objectives are the same. The manager and his team will have to organize this cooperation over the long term. The team could even be considered polymorphous, insofar as the AI, which makes an important contribution to the team's results, is part of it. The team's mission is therefore to co-opt the AI, develop it and use it operationally. On the other hand, as technology tends to smooth out individual performance gaps,collective leadership becomes essential. Allowing your team's creativity to emerge is an excellent way of doing this.
In connection with this second challenge, managers will develop their basic AI knowledge and leadership skills.
3. Setting the rules
Finally, the third challenge is linked to an ambiguity: when should we trust AI? When should humans take over? As we have seen, AI is a powerful statistical modelwhich can take into account an enormous amount of data for its calculations. On the other hand, it is devoid of common sense and can sometimes produce inconsistent results.
Humans, on the other hand, who innately possess a conscience, know how to be ethical, audacious or, more simply, sensible. Conversely, humans are often subject to numerous biases when making assessments and decisions. It's up to the manager to decide how much initiative to leave to his or her employees, so as to regain control over AI's prescriptions, and to define the rules that will enable them to take advantage of AI, while avoiding blindly relying on it at the risk of losing even more.
This challenge will enable managers to demonstrate their ability to take risks, make complex decisions and be open-minded.
However, they'll have a better grasp of their jobs, as AI will help them manage their time, communicate effectively and make simple decisions. Managers are likely to lose some of their know-how when it comes to gathering information or handling simple tasks, which they'll be handing over to the machine (in much the same way as the calculator has hampered our mental arithmetic skills). But of course, that's no reason to give up.
By Philippe Merckling
1L.Giraud et al. " L'Évolution des Compétences Managériales face à l'essor de l'Intelligence Artificielle", Manag. Avenir, Apr. 2021,