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Writer's pictureJohn C. Reynolds, PhD

Why is the Understanding of AI Critical to Leaders?

This article is the third installment of a series titled "Leading in The Algorithmic Revolution: The Impact of Artificial Intelligence on Leadership"


The algorithmic revolution, and specifically the subset AI, if realizing the opportunities and benefits already mentioned, will shift the paradigm for leaders and their leadership style in attempting to lead this “symbiotic relationship” developing between humans and machines. Leaders will have to learn, adopt, and adapt to this evolving revolution by promoting their soft skills in order to effectively utilize, motivate, and influence people in a world of algorithms and intelligent systems. How this is accomplished will be through the leading/changing of an organizational culture that grows to embrace digital transformation by encouraging learning (risk), experimentation (innovation), and learning (wisdom) - attributes not presently feasible through the use of algorithms (today!) Leaders will need to influence their greatest asset, people, that they are not being replaced by AI, but are being displaced to areas where humans cannot be replaced - creativity, innovation, empathy, imagination, etc. This shift will require leaders to home their “soft skills” to create the chemistry needed for engaged, thriving, and flourishing workforces. The era of emotional intelligence (EQ) will be the dominant skill set in leading this dance of change. All leaders are familiar with the importance of human-centric leadership, but a fast summary of four that are critical in times of uncertainty and change.


1. Honesty


Employees are people, and in order to “give their all”, especially when there are shifts in work that are as rapid and misunderstood as AI (a robot is going to take over my job), they have to be able to trust their leaders. To trust, there must be transparency and honesty. People are looking for genuine, honest, and trustworthy leaders. For many leaders, who do have these qualities, the challenge is showing them!


2. Adaptability


Constant change requires leaders to be agile and adaptable to rapidly changing contexts and conditions. If a culture of learning and innovation is to be fueled, unexpected change and adaptation through learning is inevitable. The difficulty for the leader is that as the impact of the adaption cascades through the organization, it is often perceived as a lack of focus and consistency in the leader’s vision or goals. Thus the importance of honesty precedes adaptability. 


3. Vision


Who can forget Alice in Wonderland’s question to the cat of  “Which road shall I take?” The cat replies, “Where are you going?” to an answer of  “I don’t know.” The final response is, “Then it really doesn't matter what road you take.” A vision that inspires meaning and purpose for the organization is non-negotiable to leadership, and if AI and its utilization or integration of is, the organization must share the vision. An example of a vision is Stanford University Healthcare, “To be a national leader in the study and implementation of artificial intelligence technologies to solve specific, practical problems in healthcare.” 


4. Engagement


Leaders in change as rapid, critical, and different to the workforce as the impact of AI is must be intentional in being overly engaged with their teams and the organization. Being guardians of the vision, purpose, and culture of the organization while being champions of the new future and the strategies to achieve that future requires continual engagement. Communication, empathy and support, inclusion and transparency, celebration and admissions of failure show courage, build trust, and gain loyalty in the hardest situations - if the leader and the workforce are constantly engaged.


There are many soft skills needed to be an agile leader in any change process, however, when there is the perception that work will be replaced with AI technology, the need is even more important. A reminder that AI is not “just” a change project; it is a shift in culture.


[Continued in Part 4]

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