Teaching AI to Think like an Investor

Investment research is a tangle of Bloomberg terminals and Excel spreadsheets, a flurry of earnings reports, analyst memos, and endless data that investors use to weave together insights from patterns. The process of compiling a basic overview of a company takes a staggering amount of time before anything can even be analyzed. While artificial intelligence can process thousands of documents faster than most analysts, it is an inherently human strength to make sense of the fragmented context that informs quality investment research. But what if technology and human ability could be combined to streamline the processes across investment firms? 

Chicago Booth alumnus Vibhav Viswanathan, MBA ’17 is seeking answers as he explores how AI can elevate human reasoning in fields where judgment still matters. After encountering the strengths and weaknesses of investing firms firsthand, Viswanathan targets the bottlenecks of investing and teaches AI to harness complex investment data at scale. "The pre-LLM era meant building solutions with narrow applicability, technical barriers, and an inherent lack of customization," he said. His solution? Rather than developing yet another specialized AI tool, Viswanathan sought to overhaul the infrastructural framework behind investment data.
Consider the integration between applications that Windows or MacOS provides on a computer. It’s digital transactions are so seamless they have become nearly imperceptible. Similarly, Viswanathan created Pascal AI as an operating system that specifically targets the weaknesses in investment research. As it stitches together databases and builds AI agents customized to every fund, Viswanathan’s tool unifies and extends a firm’s capabilities, highlighting AI’s potential to transform industries.

From Investor to Builder

Shortly after graduating from Indian Institute of Technology, Kharagpur with a degree in computer science and statistics, Viswanathan found himself face to face with the investing world at Boston Consulting Group in Mumbai. It was his first glimpse into a world he'd come to know from many angles. Soon thereafter, he sat in classrooms at Chicago Booth School of Business, where the economic and strategy courses he took and the network he created became the foundation for his entrepreneurial success. 

Upon graduating from Booth, Viswanathan joined Amazon Web Services, where he led product development for AI/Machine Learning solutions. The role gave him a direct insight into the potential and limitations of the new technology, and the ability to refine effective LLM techniques at scale. Equipped with applicable experience from a patchwork of different experiences, Viswanathan combined his experience in investing with experience in AI product design to create Pascal AI.

As Pascal AI grows, it is clear that a fundamental understanding of the technology behind it drives the company’s success. “How firms move ahead with AI adoption will shape whether they keep pace with the market,” he said. Amid technological development, there is often a level of fear as people wonder what will happen to their job. And while most roles will be impacted by AI, every technological shift has created new opportunities. From the industrial revolution to the birth of excel, new positions and jobs have emerged, and we have adapted. As he plays a role in changing what the role of an investor looks like, Viswanathan exemplifies that those who thrive in a changing landscape are those who understand the current technology—and who draw on that understanding to inspire growth.

By providing a unified research interface and making data so more accessible, Viswanathan hopes to level the playing field for smaller firms in the industry. The time that analysts once poured into simply researching an investment is being cut in half by facilitating faster, more informed analysis. Formats are standardized with a unified data model, and information is updated in real time. “Instead of spending days piecing together fragmented data, analysts may spend more time validating insights, debating strategy, and engaging directly with clients or portfolio companies.” Viswanathan emphasized. “Their work will increasingly be about judgment, not assembly.”

The foundational DNA of Pascal AI is simple: autonomy with accountability. This philosophy runs deep within the company. AI learns to research, analyze, and flag risks, while employees at all levels are given autonomy in their decision-making and oversight. As AI handles technical tasks, people retain responsibility for final decisions and the outcomes that follow.

Viswanathan illustrates this approach with a simple principle from his career: "The number of calls you make per day is usually under your control. The quality of the calls is too. But the outcome of the call is often not." At Pascal AI, this mindset translates directly: measure and reward the inputs you can control, trust that outcomes will follow. It is not about technology replacing jobs; it is about using technology to elevate human outputs.

Backed by Booth

For Viswanathan, the impact of attending Booth did not start with the classes he took, but with the people he met. “Many of my classmates have been incredibly supportive,” he recalls. “They have become angel investors, opened doors to customers and even introduced me to people that I have hired.” The Booth community is a guiding pillar that reflects how Pascal AI was built, with collective curiosity and leadership in opportunity.

Booth faculty were just as formative for Viswanathan’s vision. In Professor Austan Goolsbee’s class on platform competition, he encountered a case study on technological integration that posed a key question: Is it better to build broadly, or focus on a specific problem a system solves? What began as a theoretical exercise became a real strategic decision as Pascal AI took shape, ultimately capitalizing on the strengths of a single-homing platform built on specificity.

Now, Pascal AI has been deployed by more than 25 firms across the US and Asia Pacific. As he encountered the frictions of regulations across jurisdictions and continents, he thought back to lectures from Raghuram Rajan’s International Corporate Finance class. "It is completely different when you sell in Singapore to Hong Kong, to New York, to London," Viswanathan explains. “I am now experiencing for myself a concept from Rajan’s class, where we explored the complications of establishing an enterprise for a global company.” Theory is put to practice as he navigates technicalities of global markets and navigates across cultures, regulations, and expectations.

The Booth environment, which prepares business leaders to adapt and guide others through change, encouraged Viswanathan to think independently while taking responsibility for the impact of ideas. That same principal guides Pascal’s team today. AI agents operate autonomously, equipped with market knowledge and learning capabilities, but humans remain accountable for oversight and judgment.

The Formula for Success

Pascal AI is part of a broader technological transformation, and one thing is clear: Adaptability and the ability to lead through change are key to keeping up.

His advice?  “If you want to be a leader and a forward thinker, you are the one who must create the path for everybody else. You have to lean in and perhaps you'll find your own entrepreneurial way and create a path for yourself.”  With AI developing more rapidly than ever before, this moment represents a rare intersection where preparation meets opportunity, and the results can be transformative.

Booth’s new AI and machine learning courses now give students the foundation to do exactly that, equipping future leaders to understand, adapt, and thrive in the technological frontier that Viswanathan is getting to know from the inside out.