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An interview with Dr. Srijith Rajamohan
Srijith Rajamohan, Staff AI Research Scientist at Sage
Dr. Srijith Rajamohan is a Staff Research Scientist at Sage AI, where he leads data science efforts within product teams, collaborating with Product Managers, Data Scientists, and ML Engineers to develop innovative solutions that address key business challenges. He plays a cross-functional leadership role, staying up to date with the latest research and sharing insights across Sage AI to ensure best practices are applied. With prior experience at NerdWallet, Databricks, and Virginia Tech, he brings a wealth of knowledge to his current work. His research interests include Natural Language Understanding, Reinforcement Learning, and MLOps.
In the first installment of the “Bringing AI to Your Campus: A Thought Leadership Series,” Dr. Srijith Rajamohan, a Staff AI Research Scientist at Sage AI, shares his insights on AI’s growing role in higher education. With a background in academia as a Computational Scientist at Virginia Tech, Dr. Srijith highlights the unique challenges faced by universities when integrating AI technologies. He currently leads the Accounting LLM project at Sage AI, focusing on creating domain-specific language models to address accounting challenges. Dr. Srijith emphasizes the need for AI literacy among students, the importance of responsible AI usage, and how organizational culture plays a critical role in AI adoption. He advises decision-makers to partner with experts, cultivate the right culture for AI, and recognize the inevitability of AI’s impact on education, stressing that those who don’t embrace AI will be left behind.
Welcome to the inaugural post of “Bringing AI to Campus: A Thought Leadership Series,” where we explore AI’s transformative impact on higher education. Through interviews with AI leaders, educators, and industry experts, we want to help everyone learn from each other and grow the positive impact of AI in higher education and the world.
In this first interview, I spoke with Dr. Srijith Rajamohan, Staff AI Research Scientist and tech lead for Sage AI’s Accounting LLM project. With experience in academia and industry, including years as an educator at Virginia Tech, Dr. Srijith offers valuable insights into AI’s role in higher education. We discussed his journey, AI’s impact on campus, and how to integrate AI in university settings.
Before entering the industry, Dr. Srijith spent six years as a Computational Scientist at Virginia Tech, where he was involved in education, research, and academic consulting across various fields. This experience gave him a deep understanding of the unique challenges and opportunities institutions face when integrating technologies like AI.
“The concerns in academia tend to be quite different from the industry,” he noted, emphasizing how his background helps bridge the gap between these worlds.
Currently, Dr. Srijith leads the Accounting LLM project at Sage AI, where his team recently deployed a financial accounting-trained Large Language Model (LLM). This model aims to solve accounting-related challenges for Sage’s product teams, representing a groundbreaking application of AI in this domain.
“We’re training various domain-specific LLMs to address accounting challenges,” he explained, showcasing how AI can be tailored to meet specific needs.
Dr. Srijith observed that today’s students are increasingly tech-savvy, especially with AI and machine learning. “Back in the day, our AI literacy was very low. Now, it seems everyone knows how to use ChatGPT,” he said. However, this brings challenges around data privacy, ethical considerations, and responsible AI usage.
We discussed how AI tools like ChatGPT could enhance productivity in academic settings. Dr. Srijith emphasized that effective AI usage should be an essential skill for all students: “There should be a level of proficiency with these tools upon graduation, knowing how to use them effectively—and more importantly, when not to.”
Dr. Srijith stressed the importance of organizational culture in adopting AI technologies. He suggested an iterative approach: “The adoption culture for AI requires a mindset change. It’s not a one-time software solution—Generative AI is still evolving.”
Drawing from his experience, Dr. Srijith shared three key pieces of advice: