As if straight from science fiction, artificial intelligence (AI), perhaps the buzzword of the 21st century, has become, for many, simply this nebulous catchall idea of computers magically making things work on their own. As a society, we’re slowly but surely overcoming our Stanley Kubrick-esque fears of AI and have come to trust and even rely on it to handle some of the biggest datacentric and information-heavy challenges that were once left up to intuition and guesstimation.
From product inventory at scale to civil engineering, global health crises to sports scouting, we have acknowledged the limitations of the human mind when it comes to digesting voluminous data points. But in the mainstream notion of AI, its utility is still largely siloed within what we consider data-dependent challenges: how much product to order, when is the optimal time to begin the commute, whether or not to refinance, and the like. Because of this, we are overlooking a larger and more intangible component of society that at its heart is also being revolutionized by AI: leadership.
Since the dawn of civilization, leadership has been the key differentiator between success and failure—of nations at war, of corporations, of government, of innovation, and of innumerable other verticals. As a society, we are constantly bombarded with quotes and dictums about effective leadership and its virtues. But the challenge in quantifying good leadership is the perceived intangibility and elusiveness of what constitutes it.
Enter data and modeling. In the human experience, leadership has been reliant largely on intuition. Certainly, people can develop better intuition through experiential learning and by being a student of their vertical, so it is no coincidence that the aforementioned leaders were successful—to a degree. But to AI, each person, each situation, and each variable is a data point ready to be analyzed. So, by strategically integrating machine learning and AI, it is instantaneously revolutionizing leadership within some of the most prominent and important areas of society—namely defense, health care, education, and human resources—ultimately leading to better outcomes for a better world.
Take the following scenarios:
The CEO of a large corporation has thousands of employees, each of whom has social and emotional needs, growth trajectories, health factors, and skills, and the company must attract and retain the right individuals to be profitable while remaining a desirable place to work.
An Army sergeant is given a squadron of soldiers with the goal of leading them through basic training, dividing them into the duties that suit them, and deploying to an overseas base for a specific mission. The sergeant must see the gaps in readiness against that mission and address them for each soldier.
A teacher has a classroom full of different students with different needs, skill levels, home situations, levels of confidence, and dietary and health stipulations, and they must all pass the same standardized test in order to keep the school funded.
In all of these cases, the leader’s success, the team’s success, and the initiative’s success are measured by the final outcome. But these “successes” all hinge on the leader’s ability to intuitively shuffle the right people into the right roles and to provide the right type of direction, incentives, and supervision. In some cases, they must even detect and prevent health, social, or emotional to protect the individuals and the health and morale of the group.
Having an AI system reveals the gaps across every dimension associated with successful outcomes and provides actionable leadership guidance. Leaders often have access to hundreds of snippets of information that can lead to conclusions about the needs of each person, but the volume of this information is nearly impossible for the leader to comprehensively act on.
Although leaders have certainly succeeded in these exact scenarios for centuries, failure is always a major risk, especially as other mitigating factors, such as budgets, timelines, or public health crises, begin to close in. AI gap analysis, paired with recommended actions, makes this complex analysis more actionable.
The data is readily available and massive, but humans alone are incapable of processing it adequately. As a society, making the best use of the information at our disposal is critical to achieving the best results. AI holds the key to effective leadership, and as we look to the future of the corrugated industry, we must not only embrace it but also demand it.
Richard Boydis founder and CEO of AI and machine learning company Tanjo Inc. and co-founder and CEO of Ultisim Inc., a simulation learning company that utilizes gaming technology and AI. He was the keynote speaker at SuperCorrExpo 2021.