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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 (one of his MIT Sloan courses, Hands-on Deep Learning, is now freely available on MIT OpenCourseWare). 

Rama believes that AI knowledge should be accessible to everyone and shares his expository work at https://ai.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.

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Verner and Ramakrishnan win Jamieson Prize

May 9, 2025

Emil Verner and Rama Ramakrishnan were each awarded the Jamieson Prize for Excellence in Teaching, established to honor educational innovation and excellence. The Jamieson Prize for Excellence in Teaching Award is the most prestigious teaching prize offered by the School. The award was established in 2006 and is awarded each year to two MIT Sloan faculty members, as well as two electrical engineering and computer science faculty members, for their contributions to educational excellence at MIT.

The prize was announced for Verner and Ramakrishnan at the 2025 MIT Sloan Excellence in Teaching Awards for the 2024-2025 academic year.

Ramakrishnan wins MIT teaching award

June 13, 2024

Rama Ramakrishnan, professor of the practice in the Operations Research and Statistics Group, has won a 2024 Teaching with Digital Technology Award from MIT for his innovative use of digital tools in his teaching.

These student-nominated, student-judged awards recognize faculty and instructors who have effectively used digital technology to improve teaching and learning at MIT. This recognition also gives the MIT community the opportunity to learn from their innovative practices.

The awards are co-sponsored by MIT Open Learning and the Office of the Vice Chancellor. This year students submitted a total of 136 nominations, and six winners were selected.

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Ideas Made to Matter

Looking ahead at AI and work in 2026

Experts in artificial intelligence from MIT Sloan are keeping an eye on the human-LLM accuracy gap, AI guardrails, and other trends.

Jan 21, 2026
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Ideas Made to Matter

Scaling AI for results: Strategies from MIT Sloan Management Review

AI really can pay off. But leaders must take a systematic approach, understand how the technology works, and let their team leaders determine how it’s used.

Jan 7, 2026
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Press MIT Sloan Management Review

AI coding tools for knowledge work: What executives need to know

Professor of the practice Rama Ramakrishnan wrote: "Many executives are aware of agentic AI coding assistants like Claude Code but assume that these tools are relevant only to software developers. This assumption is rapidly being proved wrong. It turns out that the features that make AI coding tools useful for programmers can be equally valuable for knowledge work that involves no programming whatsoever."

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Press The Economist

How to avoid common AI pitfalls in the workplace

The unpredictability of AI's strengths and weaknesses means that it takes time to develop intuition for how to use the technology. Painful lessons are learned in the initial rush to adopt AI. Avoiding these painful lessons means solving a variety of technical issues. Yet the hidden costs of doing so are easily overlooked, says professor of the practice Rama Ramakrishnan.

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Press Bloomberg Law

AI risk, return high among corporate board priorities

Generative AI uses should be taken on more carefully because they carry greater risks, said professor of the practice Rama Ramakrishnan. "The first mistake is being overly aggressive and essentially deploying the LLM for a task without enough scrutiny," he said. On the other extreme, Ramakrishnan said, are people "who are so apprehensive about the hallucinations and the error rates, they literally are paralyzed. They don't want to do anything."

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Press MIT Sloan Management Review

How LLMs work: Top 10 executive-level questions

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."

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Executive Education Course

AI Adoption

The AI Adoption: Driving Business Value and Impact 6-week course from MIT Sloan equips you to move from AI awareness to AI transformation throughout your organization. You'll map AI technologies to your critical business challenges and opportunities, navigate adoption barriers, and build sustainable co-creation practices that amplify human capability rather than replace it.

  • Aug 19-Oct 6, 2026
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Executive Education Course

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