I retired from my long, 37-year career at IBM in June of 2007. At the time, I had already become affiliated with MIT’s Engineering Systems Division, and was looking forward to the graduate seminar that I’d be teaching that fall at MIT on Technology-based Business Transformation.
“This course covers how to leverage major technology advances to significantly transform a business in the marketplace,” read the course description. “There is a focus on major issues a business must deal with to transform its technical and market strategies successfully, including the organizational and cultural aspects that often cause such business transformations to fail.” As a concrete case study, I planned to disscuss my personal experiences leading IBM’s internet strategy in the mid-late 1990s.
The internet ushered a historical transition from the industrial economy of the previous two centuries to a new kind of knowledge-based digital economy. Advances in information technologies and globalization were among the major forces propelling this transition. Thomas Friedman’s The World is Flat became an international best-seller in 2005 by nicely explaining the implications of this new age of globalization, including the ten flatteners that brought it about, such as the explosive growth of the Internet in the 1990s and the rise of outsourcing, offshoring and global supply chains.
But, as explained by MIT economist David Autor in “The Polarization of Job Opportunities in the US Labor Market,” technology and globalization had a major disruptive impact on US workers. While employment opportunities and earnings increased significantly for high-skill technical and management occupations that required a college education, they declined for mid-skill production and administrative occupations. “The decline in middle-skill jobs has been detrimental to the earnings and labor force participation rates of workers without a four-year college education,” wrote Autor.
To help prepare their students for an increasingly unpredictable and complex world, a number of engineering and business schools started moving into territory more traditionally associated with the liberal arts: multidisciplinary approaches, an understanding of global and historical context and perspectives, and a greater focus on leadership and social responsibility. They started asking themselves how to best complement an education primarily focused on quantitative, analytical, and technical hard topics with seemingly soft topics from the liberal arts like design, creativity, and critical thinking.
For example, in January of 2010 the NY Times published “Multicultural Business Theory. At B-School?,” an article about Roger Martin, who at the time was dean of the University of Toronto’s Rotman School of Management. For over a decade, Professor Martin had been advocating “what was then a radical idea in business education: that students needed to learn how to think critically and creatively every bit as much as they needed to learn finance or accounting. More specifically, they needed to learn how to approach problems from many perspectives and to combine various approaches to find innovative solutions.”
Similarly, Ernest Wilson, — former Dean of USC’s Annenberg School of Communications and Journalism, — wrote a 2015 HBR article about his research to better understand the key competencies companies were looking for. As part of their research, Wilson and his colleagues asked business leaders around the world what attributes executives must have to succeed in the rapidly changing digital economy of the mid-late 2010s. Their research found that the traditional hard skills typically provided by engineering and business schools were necessary, but no longer sufficient.
Future leaders must be strong in technical and business skills. But these must be complemented with a unique set of attitudes, perspectives, experiences and other so called softer skills. Good leaders need to be good strategic thinkers and must have strong social and communications skills. The study identified five such specific leadership competencies:
- Adaptability: Mental agility and resilience in ambiguous situations; flexibility when dealing with change; thinking beyond the black-and-white to the gray areas; asking unexpected questions that might lead to better solutions.
- Cultural competence: Capacity to think, act and move across multiple functions, silos and global cultures.
- 360-degree thinking: Holistic thinking; capable of seeing the big picture and recognizing patterns that might lead to new and better solutions.
- Intellectual curiosity: Constantly learning and growing; willing to risk and experiment in order to come up with creative new solutions to problems.
- Empathy: Strong emotional intelligence; effective listening and collaboration skills; superior communication skills; being inclusive and considering the views of others across a variety of disciplines, cultures and perspectives.
Once more, we are in the midst of a historically transformative transition. The transition to the age of AI will be at least as big and consequential as the transition from the industrial economy to the internet-based digital economy of the past several decades. The machines of the industrial economy made up for our physical limitations, — steam engines enhanced our physical power, railroads and cars helped us go faster, airplanes gave us the ability to fly. But now, technology is being increasingly applied to activities requiring cognitive capabilities and problem solving intelligence that not long ago were viewed as the exclusive domain of human.
How should universities,such as MIT, now respond to and adapt to these major changes?
“Generating sustainable business value with AI demands critical thinking about the disparate philosophies determining AI development, training, deployment, and use,” wrote MIT researchers Michael Schrage and David Kiron in “Philosophy Eats AI,” in a recent article in MITSloan Management Review. “Hardware and software have long been technical disciplines, taught in electrical engineering and computer sciences departments. But AI, with its emphasis on human qualities like intelligence, knowledge, language and reasoning feels like a very different discipline.”
“As a discipline, data set, and sensibility, philosophy increasingly determines how digital technologies reason, predict, create, generate, and innovate,” the authors added. “The critical enterprise challenge is whether leaders will possess the self-awareness and rigor to use philosophy as a resource for creating value with AI or default to tacit, unarticulated philosophical principles for their AI deployments.”
At the recent 2025 MIT Sloan CIO Symposium we held a number of discussions on how individuals and organizations need to now adapt to the age of AI. In particular, I moderated a panel on “The Impact of AI on Jobs and Skills.” One of my fellow panelists was Isabella Loaiza, a postdoctoral associate at the MIT Sloan School of Management, who had recently published an article with MIT Sloan professor Roberto Rigobon, “The EPOCH of AI: Human-Machine Complementarities at Work.”
I had read the article, and written about it in my blog, “How Humans and AI Can Complement Each Other in the Workplace.” During the panel, I asked Loaiza to summarize their key findings.
She said that a lot of what’s been written on the future of work, — both in the academic literature and in media articles, — has been asking: “are machines going to automate most jobs?” And, while this question is important, it’s not the most important thing that we should be focusing on. We need to shift the focus from the machines to the humans by asking a different question: “what human capabilities complement AI shortcomings?”
After engaging in a series of interviews with a wide range of experts, Loaiza and Rigobon identified five groups of capabilities that enable humans to do work in the areas where machines are limited, which make up the acronym EPOCH:
- Empathy and Emotional Intelligence. These capabilities are essential for fostering understanding, teamwork, and a supportive, collaborative work environment.
- Presence, Human Connection and Networking. These facilitate face-to-face interactions and collaboration with colleagues and friends.
- Opinion, Judgment and Ethics. These include critical thinking, moral considerations, and the ability to synthesize information, integrate rational analysis with intuition, and consider diverse perspectives.
- Creativity and Imagination. These capabilities are important for the creation of novel and original ideas and the visualization of possibilities beyond reality.
- Hope, Vision and Leadership. Capabilities in this group include optimism, initiative, grit, perseverance, and the ability to develop a goal and inspire others towards it.
Let me also mention “Exploring the Impact of Artificial Intelligence: Prediction versus Judgment,” a 2017 seminar I attended in MIT by University of Toronto professor Avi Goldfarb based on a recent HBR article with his UoT colleagues Ajay Agrawal and Joshua Gans.
In the seminar, Goldfarb explained that AI is in essence a prediction technology. A prediction or forecast is a statement about what is likely to happen in the future generally based on analyzing data and other information. The dramatically lower costs of predictions are now ushering a 21st century AI-based revolution.
Predictions are one of the key ingredients of making decisions. The other is judgement, the human ability to make a considered decision after evaluating all the available evidence, observations, and arguments. As technology-based predictions become increasingly inexpensive and commonplace, the economic value of human judgement based on sound critical thinking becomes increasingly valuable.
While still in its early stages, AI has already emerged as one of, if not the most powerful technology of the 21st century. AI will have a major impact in just about all jobs and disciplines. This raises a very important question: how do we best prepare a whole new generation of students with the necessary skills for the emerging age of AI?
AI’s transformative powers amplify the need for leaders who can navigate its ethical, social, and philosophical implications with agility and foresight. Its unique ability to mimic human-like reasoning demands a deliberate fusion of the hard and soft skills that today’s leaders must master not just to thrive in their careers, but to responsibly shape AI’s impact on society.
Leading STEM and business institutions have a unique responsibility to help us define the role of humans in a world where intelligent machines will be our ubiquitous partners in most occupations. Rather than a modest expansion of existing programs, this will require a bold, systemic overhaul of STEM and business education — one that embeds critical thinking, and human-machine collaboration into every field of study, thus enabling us to better work with, and alongside AI.