Personality Traits of Knowledge Workers in the Age of AI

Baltas Group

According to the Future of Jobs report, technology is expected to drive major growth in the labour market, and technology-focused specialisms such as artificial intelligence, machine learning and big data are among the areas expected to grow most by 2030.¹ The report’s forecasts and assessments are as follows:^1,2

1. 92 million jobs will disappear under the influence of macro trends, while 170 million new jobs will be created, resulting in a net increase of 78 million jobs.
2. Since the launch of ChatGPT in November 2022, investment flows into artificial intelligence have increased almost eightfold.
3. The adoption of AI applications is spreading at different speeds across sectors, with the information technology sector leading this transformation.
4. While AI-supported jobs are growing rapidly, demand for new skills is also emerging, and this rapid transformation can increase employees’ levels of uncertainty and anxiety. However, higher productivity can be achieved where AI advances by supporting human skills rather than replacing them.

A common misconception about the future world of work is to limit AI adaptation to demographic factors such as age, gender or education level. Yet recent research clearly shows that internal psychological dynamics and personality traits lie behind adaptation.³ For knowledge workers, who need to use AI as an integral part of their work processes, understanding how personality traits shape the way they work will provide important insight in this context.

The chemistry of personality in the AI transformation

As the areas in which AI systems are used expand, the behaviours expected around these technologies also differ according to the job role and the needs of the organisation. The same personality trait can provide an important advantage in one area while pointing to a risk that needs to be managed in another. The two examples below show how different personality traits can shape the way people work with AI.

Example 1

Company X is considering assigning Jamie, a business analyst, to carry out its adaptation to developments in AI technology more efficiently and accurately. Although Jamie’s technical knowledge appears sufficient for this role, the Personova Personality Inventory goes beyond technical competence and offers important clues about how he may work with AI. Accordingly, Jamie:

1. Because of high anxiety and a tendency to be more sensitive to negative stimuli (Low Emotional Adjustment), tends to dwell on problems that may arise during AI integration rather than ignoring them. Possible errors and glitches in the outputs occupy his mind more. However, this sensitivity may cause him to feel more anxiety than necessary and, under pressure, to question his own competence and doubt his decisions.
2. Because he has a high need for social contact and communication (High Extraversion), he enjoys sharing his experiences with AI applications and easily starts conversations that support shared learning. However, his strong desire to share may mean he does not listen actively enough to the ideas and experiences of those around him.
3. Because he does not hesitate to defend his ideas (Low Agreeableness), he openly voices the points on which he thinks differently in decisions and practices related to AI. He does not shy away from saying so when he disagrees with the view adopted by the majority. However, in doing so he may give the impression that he does not sufficiently consider the other side’s perspective, which can make it harder to reach consensus.
4. As a result of his eagerness to explore new technologies (High Openness), he is keen to learn the new tools and methods that AI offers and tends to try out different use cases. However, he may turn to applications that are not yet mature and tend to research and experiment more than necessary.
5. Because of his cautious, detail-oriented working style (High Prudence), he tries to verify AI-generated results rather than accepting them as they are; he checks data sources and systematically tests the model to catch hallucinations (incorrect information) early. However, this meticulous approach can slow down decision-making and implementation.
6. As a result of an approach that values success without turning it into an overly competitive goal (Average Achievement Orientation), he sees AI tools as an aid that supports his performance and improves business results. While focusing on reaching his goals, he does not overlook long-term quality and sustainability for the sake of short-term gains. However, this balanced approach may cause him to progress at a slower pace in environments dominated by high competition and aggressive performance expectations.

Example 2

Company Y is considering assigning Sophie, a business development specialist, to work on AI-supported digital transformation projects. Sophie’s technical knowledge and experience appear sufficient for this role; the Personova Personality Inventory offers important clues beyond technical competence about how she will adopt AI, integrate it into business processes and work with her teammates. Accordingly, Sophie:

1. Because of her resilience to stress and her tendency to experience negative emotions less intensely (High Emotional Adjustment), stays calm in the face of unexpected results in AI-supported processes. She behaves with composure rather than reacting emotionally. However, this calm approach may mean she does not feel the sense of urgency created by some situations strongly enough.
2. Because she prefers to work more quietly and on her own (High Introversion), she prefers to develop her AI-related analyses in work that requires individual focus. She sets out her thinking systematically through the analyses and reports she prepares. However, this quiet working style carries the risk that her views are not visible enough across the organisation.
3. Because she values maintaining harmony (High Agreeableness), she tries to bring the expectations and priorities of different teams together on common ground in AI projects. She adopts a conciliatory approach so that differences of opinion do not damage collaboration. However, to preserve harmony within the team, she may not voice critical concerns strongly enough.
4. As a result of her open but selective approach to innovation (Average Openness), she puts the new tools and methods offered by AI through a benefit-focused filter and is positive about using applications she believes will add concrete value. However, because of her selective stance, she may discover some game-changing technological opportunities and innovations later.
5. As a result of her flexible and fast-moving nature (Low Prudence), she is agile in moving to new AI-supported applications and adapting to changing needs. She puts ideas into practice without waiting for processes to become perfect. However, this speed may lead her to use AI-generated results without verifying them sufficiently or to overlook critical details.
6. Because of her high achievement motivation (High Achievement Orientation), she sees AI not just as a tool that makes her work easier but as a strategic lever that enables higher performance. She explores new areas of use in order to reach her goals more effectively. However, her strong focus on high performance can create intense pressure on herself, and her competitive working style may be perceived as demanding by those around her.

The examples of Jamie and Sophie show that technical competence alone does not determine success in the age of AI. Personality traits make a difference in the areas where knowledge workers will show their strengths when using AI and in the risks they need to manage more carefully. Jamie’s profile supports an approach to use that questions the reliability of AI outputs, values verification and protects quality standards, while Sophie’s profile supports a way of using AI that stays calm in a crisis, adapts quickly to change and accelerates the implementation of new applications. In the AI transformation, the real question should be: “Which behaviour patterns do this role, this business process and this AI use case require?” Some organisations reward controlled progress, while others may encourage rapid learning through trial and error. This is exactly where the core contribution of personality assessment emerges. The aim is to make visible the fit between personality traits and the behavioural expectations of the role, the way AI is used in the organisation and the organisation’s way of doing business.

Conclusion

The fate of the knowledge workers of 2035 will be determined not only by technical (hard) skills but by the personality architectures that blend these skills with AI. However much AI standardises the way we work, the element that manages these systems, bears the margin of error and moves the system forward is still a person’s unique personality profile. In the future world of work, leaders and HR professionals should focus on how to position different personality structures correctly in this new ecosystem created by AI.

Sources:

1. World Economic Forum. The future of jobs report 2025 [Internet]. 2025 Jan. Available from: https://reports.weforum.org/docs/WEF_Future_of_Jobs_Report_2025.pdf
2. World Economic Forum. Future of jobs report 2025: Jobs of the future and the skills you need to get them [Internet]. 2025 Jan 15. Available from: https://www.weforum.org/stories/2025/01/future-of-jobs-report-2025-jobs-of-the-future-and-the-skills-you-need-to-get-them/
3. Sadaf Mubashir A, Altaf W, Kainaat R. Personality traits and attitudes towards artificial intelligence among university students. SRA Journal. 2024;3(2). doi:10.70670/sra.v3i2.690