As artificial intelligence rapidly moves into investment management, banking, risk analysis and other areas of finance, Cornell has launched an online certificate designed to help financial professionals understand not only what the technology can do, but where and how it can be used effectively.

The AI in Finance certificate, offered through eCornell as a collaboration between the Cornell Duffield College of Engineering and the Cornell SC Johnson College of Business, debuted in spring 2026 with 37 participants. Unlike many online certificate programs built primarily around prerecorded material, the program is taught live online, allowing participants to interact directly with Cornell faculty and industry practitioners.

The idea grew in part from Victoria Averbukh’s experience directing the Cornell Financial Engineering Manhattan program, where Master of Engineering students spend their final semester taking courses taught largely by practitioners working in the financial industry.

Averbukh, who is also a professor of practice in the School of Operations Research and Information Engineering, said conversations with those practitioners increasingly turned toward artificial intelligence – first big data and predictive analytics, then machine learning and, more recently, generative and agentic AI.

At the same time, she saw a gap between the rapidly expanding capabilities of AI and the ability of many experienced financial professionals to understand how those capabilities might fit into their work.

“There are professionals out there who are facing this sort of onslaught of new terminology, new functionality and new models, and they don’t really know what to do,” Averbukh said.

The resulting certificate is intended less as training in a particular piece of software than as a way for professionals to develop enough understanding of AI to make informed decisions about its use. Participants do not necessarily need deep technical backgrounds, Averbukh said, but they do need to understand what AI models are doing, where their limitations lie and how those models differ from technologies developed specifically for financial applications.

“It’s not about coding,” she said. “It’s really to make people more comfortable, to get the terminology under their belts and understand why these models were not created for finance.”

That philosophy is reflected in the curriculum, which progresses from AI foundations and tools to financial use cases, responsible AI, industry applications and leadership. Participants examine applications including investment research, credit risk, fraud detection, compliance, client engagement and operational efficiency, while also considering issues such as hallucinations, data security, regulation and governance. The program concludes by asking participants to identify opportunities for AI adoption and develop strategies for putting them into practice within organizations.

One distinguishing feature of the class is the roster of instructors, which brings together Cornell faculty with senior professionals whose day-to-day work involves AI, finance or both.

Cornell instructors have included Averbukh; Jamol Pender and David Goldberg, both associate professors of operations research and information engineering; Jeffrey Varner, professor of chemical and biomolecular engineering; and faculty from the SC Johnson College of Business. Industry instructors and contributors include Andrew Chin, chief AI officer at AllianceBernstein; Dhagash Mehta, head of applied machine learning research in investment management at BlackRock; Kathryn Zhao, head of API Product at OKX; Mohamed Khalifa, head of AI and innovation at J.P. Morgan Global Private Bank; and Joseph Sommer, a managing director in financial services at EY.

Cornell faculty establish the conceptual and technical foundations before practitioners show how those ideas are being confronted in financial institutions.

“We give you the foundation and then practitioners come in and take it to the next level to share what they’re seeing in the trenches,” Averbukh said.

Pender taught the “What is Data?” and “What is AI in Finance?” portions of the class.

“These courses are exciting and revolutionary because they challenge students to think beyond algorithms and consider the meaning, quality and context of the information they use,” Pender said. He explained that it is not sufficient to know that data is correct; it is also essential to know exactly when the data was generated. In finance, even accurate data can lead to poor decisions when it is delayed, outdated or unavailable at the moment it is needed, according to Pender.

“Helping students understand the relationship among accuracy, timing and intelligent decision-making made teaching these courses especially meaningful and rewarding,” Pender said.

The first cohort met synchronously online. The live format and limited enrollment encouraged questions and discussion, Averbukh said, with sessions sometimes running long because participants wanted more interaction with instructors.

Most participants were experienced professionals. While the first cohort included some early-career participants, many had more than a decade of experience in areas including capital markets, investment management, compliance, fraud detection and product development. The certificate is designed particularly for people who already understand their businesses but need a better framework for deciding where AI can – and cannot – add value.

That distinction becomes especially important during the program’s final portion, when participants develop potential AI use cases for their own work and practice making the case for those projects as if presenting to an investment committee or corporate board.

“You don’t want to say, ‘Let’s use AI for the sake of using AI,’” Averbukh said. “And you cannot say where you can even consider using AI without knowing what it is.”

Registration for the spring 2027 offering of AI in Finance is now open. Classes will meet live online on Tuesday and Thursday evenings from 7 p.m. to 9 p.m. beginning May 18, 2027. The final class will be held Thursday, June 24. An overview of the class as well as a link to enroll can be found on the eCornell website.