* Developing and leveraging soft skills: Leadership requires "soft" or "people" skills that machines struggle to replicate. AI is not good at intuitive, holistic decision-making, organizing people around a common goal, or motivating team members to give their best effort
. Leaders need to focus on developing and leveraging these skills to effectively lead human-machine teams.

* Overcoming hidden challenges: Adopting AI technology brings hidden challenges that leaders must confront and solve. These challenges can include employee resistance, cultural impacts, and the need for empathy in managing the transition
. Leaders should be aware of these challenges and develop strategies to overcome them.

* Balancing innovation and resource management: As organizations seek to innovate and remain competitive, leaders must balance the need for technological innovation with the need to manage costs and resources effectively
. They should be strategic about innovation investment and have a deep understanding of the industry's pulse to make informed decisions about technology adoption.

* Strategically mapping out technology adoption: IT leaders should not jump at the first best innovation but wait until the technology is field-tested for the industry. They should strategically map out what technology comes into the organization at a given time to lessen the organizational culture impacts
. This approach ensures that the technology adopted is aligned with the organization's goals and objectives.

* Leading AI teams: Leading AI teams presents its own set of unique challenges. AI teams and solutions are becoming ubiquitous, and leaders need to develop holistic leadership skills to effectively manage these teams
. This includes understanding the capabilities and limitations of AI, fostering collaboration between humans and machines, and ensuring that the team's goals are aligned with the organization's objectives.