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:
- The minor is open to undergraduate students across all majors, programs, and schools at LAU
- Other disciplines interested in Business and seeking future-ready digital skills
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 | |