David De Cremer is Dunton Family Dean of the D’Amore-McKim School of Business and Professor of Management and Technology at Northeastern University. He is also the author of Leadership by Algorithm: Who leads and who follows in the AI era? and The AI Savvy Leader: 9 ways to take back control and make AI work. In an interview with Forbes Indiahe explains why leaders need to manage AI-driven transformation rather than delegating it to technology experts. Edited excerpts:
Q: What are the leadership challenges surrounding AI adoption?
Companies today consider not using AI to be the biggest risk, and this pressure puts enormous pressure on business leaders. They have to get used to using this new technology, but don’t understand it well enough. Therefore, they delegate the management of the AI adoption process entirely to the technology experts. In reality, however, business leaders cannot delegate the responsibility for an AI adoption strategy. If they do, the wrong questions are likely to be asked because the business side of the technology is missing. We are already seeing the results: many companies are pouring significant money into AI, but are not able to extract adequate value from it.
By adopting a technical mindset over everything else when launching AI adoption programs, the transformation process is viewed as a purely technological endeavor. The human factor is ignored and organizational goals and purposes are not aligned with the use of AI. I wrote The AI-savvy leader to reverse the trends I’m seeing in the companies I’ve worked with, the data I’ve reviewed, and the executives I’ve spoken to. I want to bring executives back into the AI conversation and remind them that their leadership skills are essential if they want to make AI a real value creator for their organization.
Q: How would you define an AI-savvy leader?
An AI-savvy leader needs to have a fundamental understanding of AI, which includes learning about AI on two levels. First, learn the basics of what AI is and what it is not. For example, AI does not understand the meaning and application of the concepts it learns, and it is not an active participant in society like humans. On the other hand, AI works faster and more consistently on tasks where complete information is available and, with the new LLMs, can help generate content to achieve higher levels of performance. Second, understanding what AI can do provides a foundation that allows you to next think about what AI means and looks like in your business context. In particular, knowing the strengths and weaknesses of AI will help you drive your discussions with technical experts about what type of AI you should use and why. So being an AI-savvy leader goes beyond mere programming experience. Of course, you need to understand that AI relies on data and that most AI applications in companies today are likely to be supervised (human supervision). Therefore, a basic knowledge of statistics is a must. Crucially, leaders understand why human intelligence is not the same as artificial intelligence. This is the fundamental foundation that will help them develop a narrative that clarifies the use of AI in light of the relevant business issues. By acquiring this narrative, they will also be better able to design and implement strategies to use it in complementary and ethical ways.
Q: How can leaders make AI a value creator?
Leaders need to understand the importance of data, statistics and different types of AI, while also realizing that to minimize risk, they need to involve people in the use of this intelligent technology. Those who fear AI will not build a culture where there is room for experimentation and mistakes, and will therefore not encourage a mindset that allows for experimentation with this intelligent technology. As a result, companies will not learn the potential that AI can bring to them.
Also read: What Indian managers should know about Generative AI
Q: How important is a human-centered approach to AI?
What people often forget is that AI, even today at the height of large language model (LLM) applications, is still a tool. So how will you, as a business leader, use this tool to create positive impact for your business and stakeholders? Two perspectives dominate. The first sees AI as a primary means of increasing efficiency in everything they do. The problem, however, is that this perspective creates work cultures where people feel pressured to align with the machines’ decisions, rather than the other way around. Employees in such AI-centric workforces will resist and refuse to participate.
Only when humans and AI work together can we create long-term value. To achieve this, we need a behavioral, human-centered approach where AI is developed and deployed in a way that aligns with the way humans work, think and make decisions. Business leaders must therefore demonstrate that they see AI as a means, not an end.
Q: How can leaders drive collaboration between humans and AI in an inclusive way?
When leaders focus primarily on automation strategies (cost-effective strategies), they signal that the organization considers AI more important than human capital, which makes employees nervous. Leaders need to put themselves in this situation and develop a narrative that presents the use of AI as relevant to organizational goals. In this way, they convey the message that the organization has the right intentions, while simultaneously presenting AI as a tool that creates more flexible and supportive conditions for employees to grow and perform better in their jobs, increasing employee trust in the technology itself. So leaders in the AI era need strong emotional intelligence combined with the right change management skills, where they involve employees in the adoption process and promote their sense of control and autonomy.
Executives or technology experts? Who should take the lead when it comes to data-driven decision making?
Data can help leaders make better decisions—but data is just that: data. Every organization still has to decide whether data is relevant and useful, and that requires judgment that is a uniquely human skill. Deciding when to stop looking at the data and apply it to decision-making requires knowing how to align AI with business goals. That means business leaders taking the lead by asking the business questions that need to be answered, while tech experts deploy the right technology and make the right data available.
Q: How relevant are soft skills on the path to AI?
Organizations benefit from soft skills because they increasingly rely on critical thinking, emotional judgment, and problem-solving skills to understand what concrete value AI can bring to the organization, how it can be applied, and how it can be used to meet the needs of customers from different geographic and cultural backgrounds. In fact, we are moving toward a “feeling economy” where soft skills will have a greater impact on individuals’ income than their hard skills. The problem is that if we put AI first and people second, neuroscience says we will pay less attention to soft skills and ultimately make them worse. We need to put them front and center and keep training them.
Q: Can business schools play a role in preparing leaders for an AI future?
Business schools have a central mission to educate our future leaders to be AI competent and create business value by using AI in a human-centered and responsible way. As a dean of a business school, I have implemented the mission to educate socially responsible business leaders who can act, navigate and create (as entrepreneurs and innovators) in a technology-driven environment. To fulfill this mission, business schools must provide students with a combination of AI competence and competence in human behavior. More than ever, future leaders need to be trained to be agile and adaptable, to ask the right questions, to reflect and think critically, and to always let their thinking be guided by a moral compass that puts every business decision in the right context. These skills will prepare students to adapt to the new colleague AI.
