About

Companies are making significant investments in generative AI, but many are still looking for returns on that spending. The challenge is to identify LLM use cases where new efficiencies outweigh the cost and risk of the tools. Rama Ramakrishnan’s practical framework for evaluating use cases provides a systematic way to determine where LLMs can provide a return on investment.


In this webinar, you will learn:



  • The current limitations of LLMs and practices to improve readability.

  • What goes into the generative AI cost equation — understanding and assessing both direct and indirect costs of using the technology.

  • How to assess processes and tasks to find where meaningful efficiencies can be gained.


Webinar Sponsored by:


SAS
When
Thursday, February 13, 2025 · 11:00 a.m. EST (GMT -5:00)
Presenters
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Rama Ramakrishnan
Professor of the Practice, MIT Sloan School of Management
Rama Ramakrishnan is a professor of the practice at the MIT Sloan School of Management, specializing in the practical application of predictive and generative AI techniques for industry problem-solving and the development of intelligent products and services. He has over two decades of experience as a tech entrepreneur and executive, with a track record of founding and leading software companies that were eventually acquired by technology giants such as Oracle, Salesforce, and Demandware.
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Elizabeth Heichler
Editorial Director, Magazine, MIT Sloan Management Review
Elizabeth Heichler is editorial director, magazine, at MIT Sloan Management Review. She will moderate the session.
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