The Human as a “refuge value” and technology are prerequisites for becoming an augmented manager

In addition to the acquisition of a set of human qualities summarized by “softskills”, the post-crisis augmented manager is above all assisted by AI, even if they consider at the same time that AI is less efficient than AI. Human to animate and create cohesion in teams or to be creative.

Although the role of the post-Covid-19 manager is still the same – steering the activity and decision-making – the qualities that managers must possess have radically changed in a few months. The acceleration of societal changes, already at work before the pandemic crisis, and the introduction of new notions of listening, empathy and commitment to the well-being of its employees have increased employee expectations, and consequently the relationship between manager and managed. According to these new precepts, the Mandarin manager or chefaillon becomes a facilitator at the service of his team and the fulfillment at work of his collaborators.

It is this new concept of augmented manager that will make it possible to deal with sudden crises, the uncertainty of an increasingly unpredictable future, and problems with recruiting and retaining employees. According to the annual study by Axys Consultants, in addition to their human qualities, the augmented manager relies on technological tools to accomplish their task. Among these, the automation of managerial tasks comes first and jumps to 44% of the vote (vs. 29% in the 2021 survey which placed it in 2nd position).

Managers place a lot of hope in technology

With a score of 29%, data collection and analysis tools fall back to 2nd place (1st in 2021 with 34%). It is tied with a solution not offered last year: micro learning, fast learning and gamification. On the 3rd place of the podium, we find semantic search engines, but with a higher score than in 2021 (25% against 21%).

In just one year, managers are placing a lot of hope in cognitive technologies (AI, Big data, etc.) than last year. Task automation retains its 1st place, but takes 23% more responses than last year. A jump from 44% to 67%, which, according to the report, is explained by the adoption by almost half of managers of automation tools (47%). In the same vein, the scores for the application of AI and Big Data to help the manager predict his activity and that of his teams more than tripled (41% against 16%), as for that of better anticipating risks (35% versus 13%).

Next comes the possibility of improving collective intelligence through collaborative tools, cited by more than half of respondents (53%). This answer had not been offered in 2021 and the managers had placed the second step of the podium on the establishment of correlations and causal links to assist the manager in his decision-making. This objective has dropped to 6th place in 2022 (with a higher percentage: 33% against 23%).

Acculturation to technological tools is necessary

Finally, in terms of obstacles to the development of new AI and Big Data technologies, respondents seem to be much more aware of the issues and problems. For example, the first handicap mentioned remains the lack of training/acculturation of managers to these tools, but the number of respondents who mention it has more than doubled, going from 33% to 73%. The second obstacle, costs, is cited by 55% of managers, compared to only 11% in 2021. Last year, 2nd place was occupied by the fear of not being able to explain the results (black box effect) of solutions such as the AI. She is now in 3rd place on the podium (37% against 6%).

The question of ethics, which was cited as the 3rd obstacle in 2021, has fallen to 4th place, but with a higher percentage than in 2021 (35% against 21%). Finally, the fear of being replaced by a robot is mentioned twice as often as last year, falling from 20% in 2021 to 10% in 2022. However, even if a better understanding of technologies and their uses has dissipated misunderstandings, technology is not seen as a panacea. For managers, some human abilities cannot be matched by even “thinking” machines.

The added value of data to anticipate

Nearly three-quarters of them believe that a machine/AI will be less efficient than a human in leading and creating cohesion in their teams (73%). Likewise, they consider her to be inferior to her for being creative (65%) and for taking risks (55%). On the other hand, as soon as the data is likely to bring added value by facilitating and making the analysis and prediction more reliable, the relationship is reversed. Managers are thus only 4% to affirm that machines and AI are less efficient than humans in learning from experience, 18% in making reliable decisions, 20% in raising employee skills and 35% in promote collective intelligence.

In light of the figures above, it seems logical that more than half of respondents (57%) favor training in new technologies (AI, ML, machine learning, data science). They then request, at 49%, managerial coaching to develop certain softskills (creativity, risk-taking, entrepreneurship, communication, etc.).

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