MS in Business Analytics & Artificial Intelligence

The Master of Science in Business Analytics & Artificial Intelligence at American University's Kogod School of Business prepares students to use data, analytics, and artificial intelligence to solve business challenges and support strategic decision-making. The program combines technical skills with business knowledge, helping students understand not only how to analyze data but also how to turn insights into practical recommendations.

Designed for students from a range of academic and professional backgrounds, the program does not require a prior coding background for admission. Students develop skills in predictive modeling, machine learning, data visualization, natural language processing, and ethical AI practices while learning to apply these tools across business functions.

The degree comprises 33 credit hours and generally takes around two years, with flexible study options that include in-person, online, and hybrid formats, as well as full-time and part-time pathways. A hands-on practicum in Washington, DC, gives students the opportunity to work with real-world data and address business challenges.

Curriculum Structure

The curriculum combines analytics foundations, quantitative methods, business intelligence, AI applications, and practical projects. Students work with tools such as Python, R, SQL, and Tableau while learning to communicate analytical findings effectively to business stakeholders.

Initial Stage: Core Business and Analytics Foundations

Students begin by developing a foundation in quantitative analysis, business technology, data management, and organizational decision-making. Core courses include:

• Applied Managerial Statistics: Develops quantitative skills for interpreting data and supporting business decisions.

• Managing the Digital Organization: Explores how technology influences organizational processes, strategy, and business operations.

• Database and Big Data: Introduces database systems and the management of large datasets.

These courses help students build the analytical and business knowledge needed to understand complex organizational problems and work confidently with data.

Middle Stage: Analytics Foundations and Predictive Modeling

Students progress to courses that focus on turning data into useful business intelligence and forward-looking insights. Key courses include:

• Business Insights through Analytics: Develops the ability to interpret analytical results and use them to inform business decisions.

• Predictive Analytics: Builds skills in using data and analytical methods to identify patterns and forecast potential outcomes.

• Business Intelligence: Explores methods for organizing, analyzing, and presenting information to support organizational planning.

Students also develop practical capabilities in data manipulation, visualization, machine learning, and AI-supported analysis. Coursework uses real-world datasets to help connect technical concepts with business applications.

Advanced Stage: Specialization and Applied Experience

Students can tailor their studies through electives and areas of focus such as sustainability, marketing, finance, forensic accounting, and data science. They can also work with an academic adviser to develop a specialization aligned with their professional goals.

The Business Analytics & AI Practicum Project is a central part of the program. Students apply analytical techniques to real-world data and business problems, strengthening their ability to evaluate evidence, develop solutions, and present recommendations. The practicum also provides opportunities to build professional connections in Washington, DC.

Course availability and specific requirements may vary by delivery format, so students should consult the official program requirements for their intended study option.

Focus Areas

The program offers elective pathways that allow students to connect their analytics and AI skills with particular industries or business functions.

• Finance: Apply analytics and AI to financial analysis, forecasting, investment decisions, and risk assessment.

• Marketing: Use data to understand customer behavior, evaluate campaign performance, and improve marketing strategy.

• Sustainability: Explore how analytical methods can support sustainability planning, resource management, and evidence-based organizational decisions.

• Forensic Accounting: Develop skills relevant to financial data analysis, fraud detection, and identifying unusual patterns in financial activity.

• Data Science: Build further expertise in data analysis, predictive modeling, and technical approaches to extracting insights from complex datasets.

Students can also consult an adviser about creating a customized specialization. Across these options, the program emphasizes applying analytics and AI to real business needs rather than treating technology as an isolated subject.

Learning Outcomes

By completing the MS in Business Analytics & Artificial Intelligence, students can develop the ability to:

• Collect, organize, interpret, and analyze data to support business decisions.

• Apply quantitative methods, predictive analytics, and machine learning to business problems.

• Use tools such as Python, R, SQL, and Tableau for data analysis and visualization.

• Understand AI applications, including natural language processing, and consider the ethical implications of using AI.

• Translate complex analytical findings into clear recommendations for business leaders and other stakeholders.

• Apply analytical knowledge through practical projects involving real-world datasets and business challenges.

• Connect technical insights with organizational strategy, operations, finance, marketing, and other business functions.

These capabilities are designed to help graduates bridge the gap between technical analysis and business decision-making.

Professional Alignment (Accreditation)

The MS in Business Analytics & AI is a STEM-designated program, reflecting its emphasis on quantitative analysis, computing tools, data modeling, and technology-driven business problem-solving. STEM designation can be particularly relevant to eligible international students in the United States because it may support an application for an extension of Optional Practical Training, subject to applicable immigration requirements and individual eligibility.

The program combines technical training with business strategy and practical experience. This interdisciplinary approach is relevant to employers seeking professionals who can understand analytical methods and communicate their business implications.

Students should distinguish STEM designation from professional accreditation or certification: it does not itself confer a separate professional license or guarantee employment or work authorization.

Reputation and Employability

American University's Kogod School of Business emphasizes applied learning, industry engagement, and the integration of AI into business education. Its MS in Business Analytics & AI includes a practical project using real-world data, with opportunities to build professional connections in Washington, DC. The university also highlights its Institute for Applied Artificial Intelligence and initiatives designed to connect students with emerging developments in AI.

The program's flexibility and business-focused curriculum make it relevant to students seeking to advance within their current field or transition into analytics-oriented work. Potential career paths include:

• AI Product Manager

• AI Transformation Manager

• Business Analytics Consultant

• Business Intelligence Analyst

• Financial Analyst

• Marketing Analyst

• Intelligence Analyst

• Supply Chain Manager

• Data Analyst

• Analytics-focused strategy or operations professional

The university's program page reports that 94% of graduates are working or pursuing further education within six months of graduation and cites an average salary increase of more than 35%. These are university-reported program outcomes, not guarantees for individual students; results can vary with prior experience, career goals, location, and employer requirements.

For students who want to combine business knowledge with practical AI and analytics skills, this degree offers a flexible route toward work in a range of data-driven industries.