Professor M.S. Krishnan on Digital Transformation, the Future of AI, Tesla, and More

Krishnan began developing a framework for connecting technology and business in the late 1990s. At the dawn of the “dot com” boom, his research primarily focused on how software design could improve business functions and make business technology integration more efficient.

“At the time, there was a big disconnect in terms of how companies could implement technology. Many companies spent a lot of money on technology but couldn’t actually implement it to create business value,” said Krishnan.

Due to this disconnect, Krishnan began to question the purpose of technology and software in the information age. In collaboration with the late Professor C.K. Prahalad, he worked on a series of papers that were published in Harvard Business Review, Sloan Management Review, and Optimize, culminating in their widely popular book, The New Age of Innovation: Driving Cocreated Value Through Global Networks.

The book identified the theory N (sample size) =1 shaped by the technology trends. This means that if companies want technology to be truly impactful, the end goal should be the complete personalization of products and services. To do so, CEOs, executives, and managers at every level need to create a “digital transformation” of their company. To achieve this digital transformation, a firm must weave technology and customer data-driven insights into every aspect of their businesses.

In many ways, Krishnan and Prahalad's initial work predicted much of the modern tech boom. Their work is incredibly important now as more companies integrate technology into their essential operations to make their products increasingly personalized and customizable. Using the N=1 framework, Krishnan is now highlighting a number of companies he identified as embracing digital transformation through the adoption of generative AI, machine learning, data virtualization, and more.

In one recent study, Krishnan explores how the education technology company Gooru uses machine learning and GenAI to create personalized learning pathways for K-12 students. By illustrating their technology strategy, Krishnan shows how the application, which came out of Google, creates a level playing field where all students can achieve their academic goals, no matter what level of proficiency they start at. Like Google Maps, The Gooru AI engine generates a personalized learning pathway for each student to reach their destination.

In another study, Krishnan highlights Tesla’s use of technology to individualize every customer's experience in the purchasing, driving, and maintenance processes. He shows how Tesla leverages proprietary technology — such as its custom software for operations, battery interface, autonomous driving, and infotainment — and machine learning to deliver personalized experiences for all its customers, something that other automotive manufacturers have struggled to replicate.

In both cases, Krishnan argues that companies have to balance customer feedback and the development of technology to achieve digital transformation and personalization.

“Customers are always going to have some challenges, and there are constant new technological trends evolving. Digital transformation is about intentionally moving towards making the experience more personalized by weaving new technology applications to solve customer challenges and deliver value,” shared Krishnan.  

However, as machine learning and GenAI help companies personalize their products and services, the tools themselves are also becoming more niche.

“I think we'll move to more domain and industry-specific generative AI and large language models. The healthcare industry will have an LLM, consumer packaged goods, education, etc,” shared Krishnan. “However, because companies will protect their own data, every large organization will create its own LLM with the private data. That's why generative AI is interesting because it can actually get to be more personalized while also leveraging the broader knowledge. Eventually, we may all have our own individual GPTs.”

One example is the University of Michigan, which rolled out a U-M GPT called Maizey, an AI tool created with proprietary data specifically for faculty, students, and staff.

Although new technologies such as GenAI and machine learning have had an immense impact in such a short time, Krishnan warns that guardrails are necessary, especially as our use of these tools becomes more essential.

“There are downsides to AI. Privacy is a big issue, and of course, protections need to be in place. Another challenge is the copyright issue, it could be a big legal challenge. Those challenges will be there, and we will evolve to find solutions and regulations. But they will not stop the train,” shared Krishnan. “The competition with technology and AI and intelligence is at the global level. Hence, one country may also be left behind if there are very tight regulations. I believe it will positively evolve. But there is no way to go back and do business the way we did in 2015.”

In a global business world shaped by new and evolving technology, Krishnan’s work with the Business + Tech Initiative at the Ross School of Business serves to shape and guide the next generation of business leaders to understand the capabilities of digital transformation.

“In order to be successful in digital transformation, you need to have talent that understands both business and technology. And there is a premium for that talent. The motivation of our programming at Business+Tech is to create opportunities for students across all the colleges at U-M to be better prepared as business leaders. You don't have to roll up your sleeves and code, but you need to have the curiosity to understand the capabilities of technology and what it can do for different industries. You have to learn how to ask the right questions.”