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¾Ã¾ÃÈÈ learn how AI is shaping the subject they are studying and how to use available tools appropriately within the course. They may use resources such as Gemini, NotebookLM or course-specific AI tutors to explore concepts, ask questions and strengthen their understanding while remaining responsible for their own thinking and work.

For example: An economics student might use a course AI tutor to practice concepts, ask follow-up questions and prepare for an exam.

AI becomes part of how students complete meaningful course work. Depending on the discipline, students may use tools such as Gemini, Claude, Google Colab, MindBridge or other professional platforms to conduct research, analyze data, troubleshoot code, test ideas or strengthen recommendations. ¾Ã¾ÃÈÈ also learn to evaluate the quality and limitations of what AI produces.

For example: A marketing team might use AI while analyzing data and developing recommendations for a real client project.

¾Ã¾ÃÈÈ move beyond using AI as a supporting tool and begin building with it. They may create AI-powered applications, agents, automated workflows, models or other solutions designed around real business problems using platforms and development tools appropriate to the course.

For example: A finance student might use Claude Code and other development tools to build and test an algorithmic trading strategy.

Courses include Auditing and Information Technology and Risk Control.

¾Ã¾ÃÈÈ use professional tools such as MindBridge to explore AI-assisted audit analysis and EY ARC modules to examine AI ethics and generative AI governance. They also work with tools such as NotebookLM and, in advanced coursework, may build AI agents, helping them understand both how AI can support accounting work and where professional judgment still matters.

Courses across the Business Analytics & AI curriculum incorporate data analysis, modeling and AI-enabled application development.

¾Ã¾ÃÈÈ work with Python, Google Colab and generative AI platforms to analyze data, build models and create AI-enabled applications. As they progress, they move beyond using AI for assistance and begin designing solutions that combine analytics, automation and business decision-making.

Courses include Econometrics, Principles of Economics and Intermediate Macroeconomic Theory.

¾Ã¾ÃÈÈ use Stata, custom AI tutors and generative AI tools to support coding, econometric analysis, research and economic modeling. They may use AI to work through journal articles, troubleshoot code or generate economic scenarios, while learning to verify sources, test assumptions and interpret results independently.

Courses include Data Analysis in Finance, Trading & Markets and Student Managed Portfolio.

¾Ã¾ÃÈÈ work with Claude Code, GitHub, VS Code and Rotman software to analyze financial data, build projects and test algorithmic trading strategies. They also use tools such as NotebookLM for equity research connected to real investment decisions, giving them experience with the kinds of analytical workflows increasingly used in finance.

Courses include Generative AI in Business, Data Mining for Managerial Decision Making, Legal & Ethical Environment of Business and Strategic Management.

¾Ã¾ÃÈÈ use ChatGPT, Gemini, Claude, Google Colab and AI agents to automate workflows, analyze data and explore strategic decisions. They also encounter custom AI-powered experiences, such as live negotiation simulations, that require them to respond to changing conditions and decide when AI can assist versus when human judgment needs to lead.

Courses include Marketing Analytics, Digital Marketing and Professional Selling.

¾Ã¾ÃÈÈ use AI in Google Ads and social media advertising simulations, client analytics projects and sales preparation. Tools such as ChatGPT, Apollo and Synthesia can support prospecting, campaign optimization and communication, while students remain responsible for evaluating the output and making the final strategic decisions.