For many, this transition is accompanied by feelings of insecurity and added pressure, often associated with the need to prove competence in a new role. In this context, access to tools that speed up the organisation and reading of data can make for a safer and more effective adaptation.

It's not a question of technology replacing leadership, but of accelerating the learning of those who are still building it. More than just a support for decision-making, AI's ability to help team managers consolidate and cross-reference perspectives coming from different stakeholders (leaders, peers, subordinates and self-evaluations), and transforming them into a clear, balanced and constructive message, acts as a tool for the leader's own development. In this context, it makes it possible to reduce the initial cognitive load and create space for reflection, empathy and more conscious and considered decision-making.

Additionally, by supporting the preparation and structuring of higher quality feedback conversations based on concrete evidence, the AI co-pilot allows the new leader to guide these conversations with greater certainty and intentionality, accelerating the building of trust in their position, and promoting faster and more consistent learning with each feedback cycle.

Finally, and still in this context, AI can also play a decisive role in structuring more robust and strategically aligned Individual Development Plans (IDPs). Based on historical data and past organisational patterns, AI makes it possible to identify relevant performance metrics capable of supporting the new leader in defining clear, realistic and measurable priorities for each team member, reducing the subjectivity often associated with these processes.

As well as supporting the initial definition of IDPs, AI can play a decisive role in their ongoing personalisation and in empowering the leader themselves as a facilitator of development. By analysing real-time data on individual progress, engagement and learning preferences, AI makes it possible to adjust IDPs dynamically, ensuring that they remain relevant, motivating and aligned with individual and organisational goals. This intelligent monitoring not only reinforces the effectiveness of the plans, but also offers the leader insights valuable insights into the impact of their development decisions. By receiving alerts about obstacles, emerging opportunities or changes in team performance, the leader is invited to reflect, adapt and evolve in their own practice, becoming an active part of a continuous learning cycle. In this way, AI not only supports the growth of employees, but also accelerates the maturing of the new leader as an agent of human development.

Complementing the design phase, AI can also support the execution of IDPs by automating operational tasks that make it easier to monitor the process. These include signposting key dates for previously agreed 1:1 conversations, suggesting opportune moments for feedback through short surveys, and centralising relevant information at a single point of access. This type of support contributes to greater consistency and continuity in the monitoring of plans, allowing the leader to maintain focus on the development of their employees without losing visibility of the progress and commitments made over time.

At the same time, and focusing now on the individual perspective, by integrating the different learning styles and rhythms, AI boosts the ability to adjust such development plans to each person's motivations, skills and latent potential, making it possible to design highly personalised development paths without losing sight of the organisation's broader objectives.

Despite its transformative potential, the use of AI in people management contexts raises concrete risks that require attention. On the one hand, there is the possibility that algorithms will reproduce or amplify existing prejudices in historical data, perpetuating inequalities. On the other hand, the lack of transparency in the operating criteria of the systems, often described as “black boxes”, makes it difficult to understand and validate the information generated. There are also legitimate concerns about data privacy and security, since these technologies operate with sensitive information about performance, behaviour and individual potential. Therefore, for AI to work as a true co-pilot and not as a substitute for human judgement, it is essential to guarantee the transparency of the criteria used, the explainability of the recommendations generated and active supervision by leaders. Only in this way will it be possible to ensure that the technology reinforces (and does not compromise) trust, fairness and the quality of decisions, promoting leadership that is more conscious, inclusive and consistent with the organisation's values.

In this sense, it is also important to invest in training leaders to develop digital literacy and ethical skills, enabling them to interpret AI results critically and ensure that they are applied fairly and in line with the organisation's culture and values.

In short, the integration of AI into the development of new leaders represents less of a paradigm shift in leadership and more of an evolution in the way it is learnt and exercised. By functioning as a coherence and alignment mechanism, AI does not replace human judgement, but amplifies the leader's ability to learn more quickly, lead with greater confidence and transform development intentions into actionable, consistent and sustainable results-oriented plans.

Catarina Rego, Senior Consultant, SHL Portugal
Paulo Leitão, Director of Specialised Recruitment, Clan

Published in Human Magazine on 4/2/2026