Faculty
Rama Ramakrishnan is a Professor of the Practice in AI/ML. His teaching, research, and advisory interests center on the practical business application of Predictive and Generative AI techniques and in the creation of intelligent products and services.
Rama is a passionate educator and was awarded Sloan's most prestigious teaching award, the Jamieson Prize for Excellence in Teaching, in 2025 and MIT's Teaching with Digital Technology Award in 2024. He strongly believes that AI knowledge should be accessible to everyone and shares his expository work at https://ramakrishnan.com. He is also an AI columnist for the MIT Sloan Management Review and a member of its editorial advisory board.
Prior to joining MIT Sloan, Rama was a tech entrepreneur and executive for over 20 years. He has founded or has been a senior executive in four software companies that have exited to technology titans: Oracle, Salesforce, and Demandware. He is active in the startup ecosystem as an advisor and angel investor.
Most recently, Rama was senior vice president at Salesforce (NYSE: CRM) and chief data scientist for Salesforce Commerce Cloud. In this role, he led Salesforce Einstein for Commerce—the analytics/machine-learning platform that powers Salesforce Commerce Cloud—and was responsible for product management, engineering, data science, and cloud production operations. The Einstein platform uses analytics techniques to predict and influence the shopping behavior of hundreds of millions of unique shoppers monthly.
The path that led Rama to Salesforce started in July 2010 when he founded a startup, CQuotient, to build a data-science-based personalization platform for retail and e-commerce. Backed by funding from Bain Capital Ventures, Rama built and grew the company to a successful exit to Demandware (NYSE: DWRE) in October 2014. As a member of the Demandware executive team, Rama was involved in the successful sale of Demandware to Salesforce in July 2016 for $2.8 billion. CQuotient technology, now known as Salesforce Einstein for Commerce, is one of the top B2C recommendation engines in the world and influences the shopping behavior of billions of consumers annually.
Prior to founding CQuotient, Rama taught analytics at MIT Sloan, was chief scientist and vp of R&D at ProfitLogic, was chief analytics officer and vp of R&D for the retail business of Oracle, founded two analytics companies, and was a consultant at McKinsey & Company.
Rama has a BTech degree from the Indian Institute of Technology, Chennai, and MS and PhD degrees from MIT.
Enterprises racing to adopt AI must be wary of giving into hype, downplaying ethical concerns, and focusing on use cases that won’t generate real value.
Three steps to finding use cases for large language models: Break down workflows into tasks, consider all costs associated with automation, and launch pilots.
Professor of the practice Rama Ramakrishnan wrote: "Some people posit that business leaders neither want to nor need to know how LLMs and the generative AI tools that they power work — and are interested only in the results the tools can deliver. That is not my experience. Forward-thinking leaders care about results but they are also keenly aware that a clear and accurate mental model of how LLMs work is a necessary foundation for making sound business decisions regarding the use of AI technologies in the enterprise."
In a recent paper, professors Michael Cusumano, Vivek Farias, and professor of the practice Rama Ramakrishnan suggested that "as with past market-disrupting technologies, generative AI is starting to reap the benefits of an evolving ecosystem of infrastructure layers and enabling tools and frameworks, along with a rapidly growing set of applications."
"While GenAI promises to revolutionize everything from customer service to product development, its optimal role remains a work in progress."
"A rigorous evaluation process is a key driver of success for LLM application development projects."
Gain a true understanding of what GenAI is, how it actually works, and what it means for organizations. Led by faculty and thought leaders across MIT, including the Sloan School of Management and the Schwarzman College of Computing, who are working and teaching at the forefront of AI, this two-day, in-person course will help executives develop a comprehensive understanding and practical approach to putting AI to work.
