Academics

Minor in AI in Business

This minor is offered by the Department of Information Technology and Operations Management.


Why Minor in AI in Business?

Artificial Intelligence (AI) is reshaping the future of business. From transforming business models and streamlining operations to enhancing customer experiences and supporting strategic decision-making, AI has become a critical driver of innovation and competitive advantage across industries. As organizations increasingly integrate AI into their operations, they are seeking business professionals who can combine strong business knowledge with the ability to strategically apply AI to solve real-world challenges and create organizational value.

The growing importance of AI skills is reflected in the World Economic Forum’s Future of Jobs Report 2025, which identifies AI and big data as the fastest-growing skill areas for the 2025–2030 period, surpassing demand for competencies such as cybersecurity, technological literacy, leadership, and analytical thinking. This global trend underscores the rapid shift toward intelligent automation, data-driven decision-making, and AI-enabled business transformation, creating unprecedented career opportunities for graduates with expertise at the intersection of business and AI.

The AI for Business Minor is designed to prepare students for this evolving business landscape by equipping them with the knowledge and practical skills needed to integrate AI into core business functions, including finance, marketing, operations, strategic management, and decision support. Unlike programs that focus primarily on the technical development of AI algorithms, this minor emphasizes the strategic application of AI in business contexts, enabling students to leverage AI technologies to improve decision-making, automate business processes, generate customer insights, and foster innovation in products, services, and business models.

Students will also develop an understanding of responsible AI adoption, ethical governance, and effective collaboration with technical teams, preparing them to lead AI-driven initiatives while ensuring that AI technologies are implemented responsibly and sustainably. By combining business expertise with AI literacy and practical applications, graduates of the minor will be well positioned to lead digital transformation efforts and contribute to organizations that increasingly rely on intelligent technologies to achieve long-term success.

Target Audience

The minor is open to undergraduate students majoring in:

No prior programming background is required. The curriculum follows a progressive, applied learning approach suitable for business students.

Learning Outcomes

Upon completion of the minor, students will be able to:

1. Explain core AI concepts and their applications in business contexts.

2. Use AI and analytics tools to generate insights and support decision-making.

3. Analyze and evaluate AI-enabled business process transformation initiatives.

4. Apply principles of responsible and ethical AI use in organizational settings.

5. Communicate AI-based recommendations effectively to technical and non-technical stakeholders.

Minor Course Requirements

To obtain a Minor in AI in Business, students must complete a minimum of 18 credits, distributed as follows:

Core Requirements (9 credits)

Course 

Title

Credits

BDA214 AI for Business 3
BDA401 Applied Machine Learning for Business 3
BDA215 Responsible & Ethical AI in Organizations 3

Elective Courses (9 credits)
Students may select up to 9 credits from the courses in the student’s discipline related to AI.

I.  ITOM Electives

Course

Title

Credits

BDA312 AI-Driven Process Automation 3
ITM402 AI-enabled Business Intelligence 3
BDA403 NLP & Conversational AI in Business 3
ITM398B AI-enabled Web Design and Development 3

II. Business Electives

Course

Title

Credits

FIN401M Seminar: Finance Frontiers: Innovations in Machine Learning and Blockchain 3  
MGT450Q Artificial Intelligence and the Future of Management 3  
MKT330  Artificial Intelligence in Marketing 3  
ACC214 Managerial Accounting and AI Decision Support 3  

III. School of Arts and Sciences – Bioinformatics Electives

Course

Title

Credits

BIF515 Machine Learning 3

IV. School of Arts and Sciences – Computer Science Electives

Course

Title

Credits

CSC462 Fundamentals of Deep Learning 3
CSC463 Introduction to Data Science 3
 

V. School of Engineering- Computer Engineering Electives

Course

Title

Credits

COE546 Machine Learning 3
COE547 Deep Learning 3
COE548 Large Language Models 3
 

VI. School of Engineering- Industrial Engineering Electives

Course

Title

Credits

INE599P Data Analytics using R Language 3

VII. School of Engineering- Mechanical Engineering Electives

Course

Title

Credits

MEE532 Advanced Manufacturing and AI 3