UT Austin and the University of Maryland Smith School both now offer STEM master’s programs that put artificial intelligence near the center of the degree. Their structures, costs and admissions expectations are different enough to compare carefully.
| Factor | UT Austin | Maryland Smith |
|---|---|---|
| Degree | MS Business Technology & AI | MS Information Systems & AI |
| Length | 36 credits; 10 months | 30 credits; 3 semesters full-time |
| STEM | Yes | Yes |
| AI Exposure | Very High | Very High |
| Published tuition | $55,600 Texas resident; $59,700 nonresident | $1,631/credit Maryland resident; $2,072.50/credit nonresident/international, plus fees |
| Admissions preparation | Programming and database experience required | No business degree required; quantitative preparation is useful |
| Career evidence | Class of 2025 average starting salary: $110,360 | Class of 2025: 75.1% of job seekers accepted an offer by three months; reported salary average $95,321, with a low salary-response rate |
How the AI emphasis differs
UT Austin emphasizes AI foundations, machine learning, generative AI, data/cloud engineering, advanced programming and a required company capstone. Maryland integrates AI into information systems through AI-augmented Python and databases, Harnessing AI for Business, predictive analytics, cloud study and an industry practicum; its online curriculum also includes agentic AI.
Career-data caution
The two schools publish different types of outcomes. UT Austin reports a Class of 2025 average starting salary. Maryland publishes a detailed employment report with offer acceptance and salary data, but the salary portion has a relatively low response rate. MSITM.com treats these as useful evidence rather than directly comparable scorecards.
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UT Austin profile → | Maryland Smith profile →
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Comparison based on program data reviewed/verified by MSITM.com in September 2026.