A Taxonomy of Managerial Mindsets Toward AI Collaboration

In every company, at every conference table where the implementation of artificial intelligence is discussed, there are people sitting next to each other who look at the same tool and see completely different things. For some, AI is a strategic partner; for others, a useful machine or a threat. The question is not which of them is right. The question is how to create synergy between these perspectives.

A study recently published in Technovation by NAWA DIGIT researchers offers something valuable: a map of these differences. Based on data from 472 professionals, the authors identified four distinct managerial profiles that differ not only in their attitude towards AI, but in their entire way of thinking about human-machine collaboration.

AI Trailblazers see AI as a strategic partner. They actively integrate it in various areas of activity and experiment. For them, AI is not a tool, but rather a member of a team.

AI Strategists combine AI insights with human judgment in a structured and thoughtful way. They do not trust blindly; they do not reject in advance. They are looking for balance, systems, and procedures that will allow them to harness the potential of AI without losing control.

Pragmatic Adopters use AI selectively, mainly where high efficiency is important. They are not enthusiasts, but they are not skeptics either. They treat AI like any other tool: useful when it works, redundant when it doesn’t.

AI Skeptics remain cautious. They emphasize the importance of control, transparency, and the dominance of the human factor. They see risks where others see opportunities. Their skepticism does not stem from ignorance. They often understand technology better than enthusiasts, but they also care more about the consequences.

Importantly, none of these profiles is “right” or “wrong.” Each brings something important. Trailblazers drive innovation and show what’s possible. Strategists build systems that allow for scaling success. Pragmatists make sure that enthusiasm does not obscure a sober calculation of costs and benefits. Skeptics ask questions that others prefer to avoid and often protect the organization from mistakes that would go unnoticed.

The problem arises when the organization does not recognize this diversity. When it assumes that all managers should think the same. When it deploys AI “for everyone” in a way that fits only one profile. A Trailblazer in an organization that requires justification for every experiment will be frustrated and unproductive. A Skeptic in a culture that punishes caution will either leave or remain silent. The organization will then lose a person who could have warned it of the risks.

The study also shows something important: managers working in organizations that actively promote experimentation with AI report higher satisfaction with the results. But this does not mean that it is enough to encourage experiments. It is about creating an environment in which different approaches can coexist and mutually correct each other.

How to do it in practice? First, recognize that the diversity of approaches exists and is natural. Second, design AI deployments with different profiles in mind, rather than assuming that one size fits all. Third, create spaces where Trailblazers can experiment without paralyzing the entire organization, but where Skeptics have a real say in decisions about the scale and scope of implementations.

This requires more than a technology strategy. It requires understanding that AI adoption is a social process, not just a technical one. That people’s mentalities are as important as the capabilities of algorithms. And that an organization that can manage a diversity of attitudes toward AI will ultimately be more resilient and innovative than one that enforces unanimity in either direction.

Full article: https://www.sciencedirect.com/science/article/pii/S0166497226000544

This post is part of the project “People and Algorithms in Organisations: Competences to Work in the Digital Environment”, funded by the NAWA – Narodowa Agencja Wymiany Akademickiej (Polish National Agency for Academic Exchange).

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