The master of science in artificial intelligence for business at the George Washington University School of Business is a school-wide, cross-departmental program that prepares graduates to deliver AI responsibly in organizational settings. The program equips students to design, deploy, and govern AI-enabled systems that create business value while meeting expectations for reliability, accountability, and responsible innovation. The 30-credit curriculum combines rigorous technical preparation in programming, statistical foundations for AI, and modern AI methods with applied implementation skills, business integration, and AI ethics and governance.
Students complete a shared 12-credit core and then specialize through one of three tracks, each culminating in a track-specific 3-credit capstone focused on end-to-end delivery. A sequenced AI pathway builds from responsible AI and governance to foundational AI capability and generative AI systems with business applications, reinforced through hands-on labs, cross-disciplinary electives contributed by participating departments, and practitioner engagement. Graduates are prepared for roles at the intersection of technology and management, including AI product and strategy, analytics and AI leadership, and responsible AI governance, with the ability to translate state-of-the-art methods into scalable, implementable solutions.
To be considered complete, the below must be included in the online application:
Completed Online Application: The fee will be waived for applicants who already possess an undergraduate or graduate degree from GW. The online application accepts electronic payment.
Current Résumé: Uploaded through the online application system.
One Letter of Recommendation: From professional and/or academic references.
Statement of Career Objective: In no more than 500 words, describe how the MSAIB program fits into your professional life and your career objectives.
Additional Application Requirements
Transcripts: All admitted students will be required to submit official, sealed academic transcripts with proof of their bachelor’s degree. There is no need to submit transcripts at the time when you first apply; you may do so after admission. Once admitted, please submit transcripts from all of the colleges and/or universities you have attended where you received 15 credits or more, whether or not a degree program was completed or the credits appear as transfer credits on another transcript.
International applicants should upload the English-language version of their transcripts or a copy of a credentialed evaluation. For a list of acceptable foreign credential evaluation services, please visit nacs.org.
International Applicants: Applicants who have not completed their entire degree in a country in which English is the principal language must submit one of the following: an official TOEFL score of at least 100 (internet-based test), an official IELTS score of 7.0 with no individual band score below 6.0, or a PTE Academic Score of at least 68. Test date must be within the past two years. TOEFL code: 5246 Department code: 02
Financial Certification Form along with supporting documentation indicating that you have adequate funding for tuition and living expenses for the duration of the MSAIB program. The form is required from students requesting a visa and only after receiving an admission offer.
Copies of all current or recently issued visa or I-20 documentation. (To expedite processing, you should submit an application that is otherwise complete and forward the copies of visa or I-20 documentation when they become available).
The following requirements must be fulfilled: 30 credits, including 12 credits in required core courses and 18 credits in required and elective courses in one selected track.
| Code | Title | Credits |
|---|---|---|
| Core courses | ||
| DNSC 6311 | Stochastic Foundation: Probability Models | |
| DNSC 6312 | Statistics for Analytics I | |
| ISTM 6200 | Python Program Database Applications | |
| ISTM 6227 | Course ISTM 6227 Not Found | |
| Track requirement | ||
| Students select and complete all required and elective course requirements for one of the following tracks: | ||
| AI systems management track | ||
| Required | ||
| ISTM 6202 | Relational Databases | |
| ISTM 6209 | Web and Social Analytics | |
| ISTM 6214 | Foundations of Artificial Intelligence | |
| ISTM 6218 | Business Applications of Artificial Intelligence | |
| ISTM 6210 | Integrated Information Systems Capstone | |
| Elective | ||
| One course selected from the following: | ||
| ISTM 6213 | Cloud Applications | |
| ISTM 6217 | Internet of Things Management | |
| ISTM 6222 | Digital Business Strategy | |
| ISTM 6290 | Special Topics | |
| AI analytics track | ||
| Required | ||
| DNSC 6306 | Decision and Risk Analytics | |
| DNSC 6307 | Optimization I | |
| DNSC 6308 | Optimization II | |
| DNSC 6313 | Statistics for Analytics II | |
| DNSC 6314 | Machine Learning I | |
| DNSC 6315 | Machine Learning II | |
| DNSC 6317 | Business Analytics Practicum | |
| Electives | ||
| 6 credits in courses selected from the following or other GWSB courses approved by the advisor. | ||
| DNSC 6280 | Supply Chain Analytics | |
| DNSC 6305 | Data Management for Analytics | |
| DNSC 6319 | Time Series Forecasting for Analytics | |
| DNSC 6320 | Pricing and Revenue Management | |
| DNSC 6321 | Social Network Analytics | |
| DNSC 6323 | Visualization for Analytics | |
| DNSC 6325 | Business Process Simulation | |
| DNSC 6327 | Sports Analytics | |
| DNSC 6331 | Customer Analytics | |
| Other possible electives include courses from the AI systems track (above) and other GWSB courses such as ACCY 6521 Data Analytics for Accounting, FINA 6290 AI in Finance, IBUS 6101 Big Data for International Business, MKTG 6258 AI Applications in Marketing, MKTG 6262 Digital Marketing Analytics, and MKTG 6263 Marketing Decision Analytics. | ||
| AI business track | ||
| Required | ||
| ACCY 6521 | Data Analytics for Accounting | |
| FINA 6290 | Special Topics | |
| IBUS 6101 | Big Data for International Business | |
| MKTG 6262 | Digital Marketing Analytics | |
| MKTG 6263 | Marketing Decision Analytics | |
| MKTG 6264 | Artificial Intelligence and Machine Learning for Marketing Automation | |
| ISTM 6210 | Integrated Information Systems Capstone | |
| Electives | ||
| 6 credits in approved GWSB coursework selected in consultation with the advisor. | ||