Marquette Launches AI in Business Major for Fall 2026

The College of Business Administration at Marquette University has announced a new standalone major in Artificial Intelligence in Business (AIBU), launching in Fall 2026. The program aims to bridge the gap between technical AI literacy and strategic business leadership while embedding ethical stewardship into the curriculum.

According to the official program page, the AIBU major prepares students to use AI tools effectively and ethically in today's dynamic business landscape. Students will gain hands-on experience using AI tools, including GenAI and Agentic AI, while exploring their real-world applications in business.

Dr. Yasamin Hadavi, assistant professor of information systems and analytics at Marquette, served as a core contributor to the program's creation. In a Q&A published by Marquette Today, Hadavi explained that the primary catalyst for this major was the growing disparity between rapid technological advancement and the available talent pool. As organizations pivot toward AI in pursuit of competitive advantage, the demand for "AI-fluent" candidates has reached a critical threshold.

The curriculum focuses on four distinct competency areas. First, students master generative intelligence and prompt engineering — the art and science of crafting high-precision inputs to elicit optimal outputs from Large Language Models (LLMs). This skill transforms AI from a simple search tool into a sophisticated co-pilot for business problem-solving.

Second, students gain hands-on experience with applied machine learning and model governance by working with diverse datasets to deploy and evaluate supervised machine learning algorithms. The curriculum focuses on Model Evaluation and Data Quality Assessment, teaching students to identify the specific conditions under which AI provides a competitive advantage versus when it might introduce risk.

Third, the major empowers students to develop functional business applications using Low-Code/No-Code environments. By exploring "Vibe Coding" — using natural language and intuitive design to guide code generation — students learn how technical logic is applied through modern, AI-assisted development workflows. (Honestly, calling it "vibe coding" feels like marketing trying to make coding sound less intimidating.)

Fourth, a core competency of the Marquette graduate is ethical AI leadership. Students learn to evaluate the transparency, fairness, and bias of data and algorithms, ensuring they can lead AI initiatives that are socially responsible and aligned with organizational values.

Mark Barratt, chair and associate professor in the Department of Supply Chain and Systems Intelligence, noted that the AIBU major meets a growing need in industry. The program will prepare professionals to enter the workforce with a deep understanding of AI and firsthand experience using these tools to create lasting value for companies.

The program's structure is designed to complement all existing majors in the College of Business Administration. Its flexible structure allows students to seamlessly declare it as an additional major, building in-demand future-ready skills and pairing AI expertise with core interests in existing business disciplines. Students are encouraged to speak with advisers about the AIBU major and explore possible credit overlap with current major courses.

Dr. Terence Ow, WIPFLI Fellow in AI, emphasized that it is not enough to use AI effectively. More importantly, this major will prepare students to use AI tools ethically. Graduates will enter the industry ready to harness the power of AI in their workflows and decision-making processes while upholding ethical standards each step of the way.

The AIBU major ensures students don't just ask, "Can we build this?" but rather "Should we build this, and how does it serve the common good?" This focus on responsible AI use prepares graduates to lead with integrity. In an era where algorithms can influence everything from hiring biases to credit scores, the world doesn't just need smart employees — it needs wise leaders.

Graduates will be prepared for success through strategic decision-making, model governance and a balanced perspective. They are trained to maximize the competitive advantages of AI (such as predictive analytics and operational efficiency) while remaining aware of its limitations (such as hallucinations, data drift and "garbage-in, garbage-out" risks).

Marquette's AIBU major is a distinctive program that balances technical proficiency with the ethical framework required of modern business leaders. While many institutions are just beginning to integrate AI, Marquette has established it as a dedicated, standalone major within the College of Business Administration — one of the first of its kind in the nation.

Hadavi's advice to students considering this major is to hold a flexible mindset and get comfortable with ambiguity. This major is for those who are eager to "unlearn" old methods and embrace a state of constant evolution. You aren't just learning a subject; you are learning how to learn at the speed of technology.

This program is not designed to teach you how to offload your workload to an algorithm. It is designed to empower you to use AI with awareness and responsibility. The most successful students will be those who use AI to amplify their own creativity and analytical depth, rather than using it as a substitute for critical thought.

There is a common saying in the industry: "AI won't replace you, but a person using AI will." If you rely solely on the output of the tool, you become replaceable. This major gives you the "under-the-hood" knowledge — the understanding of algorithms, data quality and ethics — that makes you indispensable.

Whether employers actually value this blend of ethics and technical skills over pure coding ability remains to be seen. For now, Marquette is betting that being the moral compass in the room will pay dividends — or at least keep graduates from building something they'll regret later.

Artūras Malašauskas is an AI Systems Integrator with 20+ years of production-grade web engineering experience. He has designed, shipped, and scaled enterprise Python/PHP systems for logistics, SaaS, and public-sector clients. For the past year, he has focused exclusively on AI integrations: deploying open-source LLMs, building generative media pipelines (image, audio, video), and engineering multi-agent workflows for real production environments. His standard: reproducibility, security, cost-efficient inference—no vaporware. He documents and evaluates emerging AI tooling, separating verified capabilities from marketing noise. Technical editor at: muza-ai.eu, ai-verslas.lt, ai-naujinos.lt Connect on LinkedIn