In the past few years, artificial intelligence (AI) has played an increasingly prominent role among the startups making their pitches at the annual MIT delta v Demo Day event.
“We’re thinking of AI as another new tool in the toolkit,” Macauley Kenney, SM ’16, (Entrepreneur-in-Residence, Martin Trust Center for MIT Entrepreneurship) told MIT News. “In some ways the world is moving a lot faster, but we also need to make sure the fundamental principles of entrepreneurship are well-understood.”
Hugo Huang, SFMBA ’20, did not participate in MIT delta v during his time in Cambridge, but he has lived what Kenney spoke about and what the Demo Day teams have demonstrated. He continues to live it as public cloud alliance director at Canonical, the open-source software developer behind the popular Linux system Ubuntu.
“Digital transformation has driven humanity’s reshaping of the world for almost half a century, and that process is now accelerating as we hit a pivotal point. GenAI is poised to lead humanity into an entirely new chapter of transforming the world,” says Huang.
Dreaming big
Before joining the MIT Sloan Fellows MBA program in 2019, Huang earned engineering degrees from Nanjing University of Science and Technology, which at the time was the only institution in China advancing millisecond-level pattern recognition. His graduate advisor, Chunkan Tao, introduced him to early-stage research on pattern recognition, computer vision, and industrial applications of AI. As early as the 1990s, Tao’s lab had already collaborated with MIT on applying pattern recognition techniques to medical microscopic diagnostics.
“I feel very fortunate that I got into this area of study when I did,” says Huang. “I was able to dive deep into AI and understand how much it could change the world.”
Huang’s studies inspired him greatly. He dreamed that one day AI would break through the limits of industrial use cases and enable everyone to enjoy a better life.
I’ve always been strong in strategy and execution, but I lacked the systematic financial and analytical management skills. I needed to integrate those capabilities to identify the next growth trajectory for AI and to lead teams beyond existing boundaries.
“I should know more about the business and the people, as well as how to organize a team, tackle certain business problems, and merge engineering into specific industries. I wanted to understand how I could better leverage my technology background to help them solve big problems,” he says.
Instead of immediately applying to business schools, Huang joined the Chinese technology company Huawei as an engineer. There, he took part in—and eventually led—a wide range of initiatives that applied AI to real business problems: optimizing 3G network performance with AI, reducing energy consumption in telecom equipment, and transforming the way sales and HR resources were managed.
An urgency to understand
At Huawei, Huang progressed from managing small teams in China to bigger divisions in Italy and India, then back in China. He advanced step by step, learning more about business and management with each new role.
It was around this time that Huang first considered applying to MBA programs. But with so much forward movement at Huawei, he postponed school to work in the company’s then-new corporate leadership program at its headquarters in Shenzhen. There, he would use cutting-edge AI technologies to help lead the digital transformation of Huawei’s global sales organization. The role also gave him direct access to the vice president of Huawei’s largest business group and other top executives—including Huawei’s founder, Ren Zhengfei—and, most importantly, the chance to learn from them firsthand.
By the end of his fourth year in Shenzhen, Huang reconsidered school. The projects he led played a central role in Huawei’s strategic transformation, helping the company double its revenue from $50 billion to $100 billion in just four years. Feeling that he had graduated from the “Huawei global university,” he applied to the MIT Sloan Fellows MBA program. The following year, Huang was accepted into the Class of 2020. When he left Huawei, he carried with him the encouragement of then-rotating chairman Xu Zhijun, who told him, “Go build another Huawei of the AI era.”
At MIT Sloan, Huang reflected on his accomplishments at Huawei and his dream of AI to help everyone. “From the entrepreneurial standpoint, I was still missing key pieces to unlock my dream,” he says. Once in Cambridge, however, Huang was exposed to myriad alternatives for what his next steps might be. The first was his decision to focus his studies on finance and business analytics, and he enrolled in both the Finance and Business Analytics Tracks at MIT Sloan.
“I’ve always been strong in strategy and execution,” he adds, “but I lacked the systematic financial and analytical management skills. I needed to integrate those capabilities to identify the next growth trajectory for AI and to lead teams beyond existing boundaries.”
Growing at, and beyond, MIT Sloan
Throughout the program, all new MIT Sloan Fellows reflect on their career journeys and think about what their next steps might be. The intensive 12-month education for mid-career professionals is designed to foster such reflections, both individually and with your peers.
Huang not only learned a great deal about himself, but he also learned a lot about his international classmates and their distinctive educational and entrepreneurial experiences.
“Many of them faced even more challenging situations than I had,” he says. “It’s such a diverse group, and a good resource for myself and my future growth.”
Five years on, Huang remains in touch with many in his 2020 MIT Sloan Fellows cohort. They provide each other with life updates, share valuable information and expertise, and network across their respective industries.
He also continues to lean on what he learned at MIT Sloan to advance his work at Canonical, including the company’s joint innovation with Google, where Huang plays a significant role in leading projects such as GPU and TPU enablement. As a leader in AI, Huang feels a responsibility to help more executives and decision-makers understand the evolution of the field. Guided by MIT’s “mens et manus” philosophy, he has put this belief into practice in many ways—for example, his 2023 Harvard Business Review article helping CEOs navigate GenAI cost decisions. He is now collaborating with Google teams on a forthcoming book for decision-makers on how to build AI systems: the AI Infrastructure Playbook.
“MIT Sloan’s ‘step-in, step-out’ philosophy keeps me grounded in the work, yet always looking up to chart the way forward,” he says.
