When we think of great leaders, we turn to famous leaders from history for inspiration, but they did not have to deal with unpredictable disruption AI is causing. The modern leader must not only lead humans, but also autonomous AI agents. They must also guide the organization through the process of adapting to fully utilize AI across all the operations. There is no simple answer to this challenge, but there is a structured approach with six steps that will increase the chances of success.

Figure 1. The steps to being a great leader in the age of AI

Step 1: Learn the three most effective leadership styles

The first step is to learn the three most effective leadership styles and understand the benefits of combining them in various ways. These are servant, transactional and transformational.

Step 2: Learn the typical stages of a project

The modern leader must constantly integrate the latest versions of AI so their role becomes similar to that of a project manager implementing a series of digital transformation projects. Typically, a project has six stages that are forming, storming, norming, performing, adjourning and post-project collaboration.

Step 3: Evaluate the context

While we are fascinated by the capabilities of AI, the role of the context the leader finds themselves in must not be underestimated. The leadership approach must consider the influence of the context on the people and the technology.

Step 4: Choose a business model and a leadership style

The leader needs to think about whether to focus on one of the three leadership styles or combine two of them to get the best out of the situation they are in.

Choosing a proven AI centred business model will offer clarity. There are six proven AI focused business models: first: incumbent focusing on one part of the value chain and disaggregating, second: incumbent absorbing AI into existing model, third: incumbent expanding beyond current model to fully utilise the opportunities of AI and access new data, fourth: startup disruptor focused on one sector, built from the start to be highly automated, fifth: disruptor focused on tech adding a new service such as insurance, and lastly the sixth model is a disruptor that is not tech-focused but has an extensive userbase.

Step 5: Build trust with a clear vision of what the role of AI is

To lead autonomous AI agents, the leader must build trust in them among the team. The leader must be clear on their use and build a consensus around this. The team must be put on a sustainable trajectory for change.

Step 6: Decide what to do at each stage of the project

 Effective leadership today must involve leading on technology as well as people, building trust in the technology, and finding the best combination of leadership styles to get the most out of humans and automated AI agents. These many tasks cannot all be done at once so the leader must have a plan of what they will focus on at each stage.

The steps touched on here are covered more thoroughly in the book. If you want to learn more about Leadership in AI with trust you can buy my book from all good bookshops.

Reference

Zarifis A. (2025) ‘Leadership with AI and trust: Adapting popular leadership styles for AI’, De Gruyter: Berlin. https://doi.org/10.1515/9783111630137

https://www.amazon.co.uk/Leadership-AI-Trust-Adapting-leadership/dp/3111630048

https://blackwells.co.uk/bookshop/product/Leadership-With-AI-and-Trust-by-Alex-Zarifis/9783111630045

There are many benefits for researchers that take part in a project but there are also several challenges that can create a cumulative, negative, effect on their mental health. This research identifies the challenges researchers face in projects, so that the leader of the project can reduce them as far as possible.

Existing research focuses on four stages of a project: Forming, Storming, Norming and Adjourning. This research adds a fifth stage, Post-Project Collaboration, as this stage is implicitly or explicitly a part of most research projects. For example, a post-doctoral researcher expects to be credited for their work even if it is published after the end of the project. The specific challenges for each of the five stages are identified. This enables the leader to focus on a manageable number of challenges at each stage.

Some challenges are in only in one stage of the process, while other challenges are across several stages. It is notable that there is no conflict at the start, but trust is a challenge at the start. This suggests that low trust at the start causes problems later. Therefore, there is a delayed reaction, and once the conflict happens it might be too late, as the trust should have been built earlier.

Figure 1: A model for reducing the challenges for researchers in projects across five stages

Trust is important in several collaboration settings, particularly at the start, until participants familiarise themselves with each other and the project team matures. In research teams, due to the long period of time until the research is published, often over five years, there is an additional, long-term cause for risk and distrust that is only resolved once the research is published.

Trust should be built during the first stage to cover four specific topics: Trust in the leader, process, evaluation method, and trust in being credited in published work.

In the final two stages of the project, adjourning and post-project collaboration, a new vision needs to be communicated effectively as the original vision stops resonating after the norming stage.

For those challenges that cannot be solved outright, the leader of the research project must show an awareness. The leader should be ambidextrous, in the sense of focusing on the project deliverables and the socio-psychological aspects of the teamwork.

Reference

Zarifis A. & Cheng X. (2024) ‘A model reducing researchers’ challenges in projects: build trust first for better mental health’, Cogent Business & Management, vol.11., no.1, pp.1-13. https://doi.org/10.1080/23311975.2024.2350786 (open access)

Financial technology often referred to as Fintech, and sustainability are two of the biggest influences transforming many organizations. However, not all organizations move forward on both with the same enthusiasm. Leaders in Fintech do not always prioritize operating in a sustainable way. It is, therefore, important to find the synergies between Fintech and sustainability.

One important aspect of this transformation many organizations are going through is the consumersʹ perspective, particularly the trust they have, their personal information privacy concerns, and the vulnerability they feel. It is important to clarify whether leadership in Fintech, with leadership in sustainability, is more beneficial than leadership in Fintech on its own.

This research evaluates consumers’ trust, privacy concerns, and vulnerability in the two scenarios separately and then compares them. Firstly, this research seeks to validate whether leadership in Fintech influences trust in Fintech, concerns about the privacy of personal information when using Fintech, and the feeling of vulnerability when using Fintech. It then compares trust, privacy concerns and vulnerability in two scenarios, one with leadership in both Fintech and sustainability, and one with leadership just in Fintech without sustainability.

Figure 1. Leadership in Fintech, trust, privacy and vulnerability, with and without sustainability

The findings show that, as expected, leadership in both Fintech and sustainability builds trust more, which in turn reduces vulnerability more. Privacy concerns are lower when sustainability leadership and Fintech leadership come together; however, their combined impact was not found to be sufficiently statistically significant. So contrary to what was expected, privacy concerns are not reduced more effectively when there is leadership in both together.

The findings support the link between sustainability in the processes of a Fintech and being successful. While the limited research looking at Fintech and sustainability find support for the link between them by taking a ‘top‐down’ approach and evaluating Fintech companies against benchmarks such as economic value, this research takes a ‘bottom‐up’ approach by looking at how Fintech services are received by consumers.

An important practical implication of this research is that even when there is sufficient trust to adopt and use Fintech, the consumer often still feels a sense of vulnerability. This means the leaders in Fintech must not just think about how to do enough for the consumer to adopt their service, but they should go beyond that and try to build trust and reduce privacy concerns to the degree that the consumer’s belief that they are vulnerable is also reduced.

These findings can inform a Fintech’s business model and the services it offers consumers.

Reference

Zarifis A. (2024) ‘Leadership in Fintech builds trust and reduces vulnerability more when combined with leadership in sustainability’, Sustainability, 16, 5757, pp.1-13. https://doi.org/10.3390/su16135757 (open access)

Featured by FinTech Scotland: https://www.fintechscotland.com/leadership-in-fintech-builds-trust-and-reduces-vulnerability/