Applied AI Integration

Overview

The Applied AI Integration (A²I²) process is MSOE’s approach to incorporating essential applied artificial intelligence topics into our curriculum. Led by the MSOE faculty and aligned with MSOE’s hands-on mission, the A²I² process supports authentic incorporation of AI topics across disciplines - from engineering and computing to business and nursing. Its goals are straightforward: give students practical experience with AI tools, strengthen their ability to reason about AI results, and ensure they understand the ethical and societal context in which AI operates. Courses and academic programs that meet MSOE’s A²I² content guidelines are formally recognized in the MSOE academic catalog. This catalog recognition provides clear evidence of MSOE’s commitment to applied AI integration and can guide students in their selection of courses and programs.

Why A²I² Matters

AI technology now influences how problems are framed, analyzed, and solved in nearly every field. Applied AI integration prepares students to use these technologies responsibly and effectively, not as a novelty, but as an integral part of their professional practice. This initiative helps students develop adaptable skills by combining technical knowledge with judgment, stewardship, and domain-specific application. This prepares them to contribute to their employers and society upon graduation and to continue learning as AI technology evolves.

 The A²I² Framework

At the heart of A²I² process is a flexible framework that balances theory with practical application. It assures both depth and breadth in topical coverage and emphasizes the need for responsible AI use. Students learn how AI works, how to use it, how to judge its output, and how to steward data and technologies responsibly. The framework defines four essential A²I² dimensions:

• Foundational Knowledge: Understand how common AI technologies work, including their design, capabilities, and/or limitations.
• Practical Application: Apply existing and emerging AI technologies to solve the complexchallenges of today and tomorrow.
• Critical Evaluation: Critically evaluate the selection, use, and output of AI technologies, by assessing their accuracy, effectiveness, and limitations.
• Social Responsibility: Manage data and AI systems responsibly with respect to privacy, protection of proprietary information, ethical considerations, best practices, regulatory context, and consideration of potential societal effects.

These dimensions can be adapted to suit the needs of the full range of academic disciplines taught at MSOE. For example, Foundational Knowledge will be different for computer science than for nursing or business. In particular, Practical Application content will be shaped by the problems and tools applicable to each field of study.

 Defining Meaningful Coverage

The A²I² process provides clear yet flexible definitions to distinguish the level of applied AI integration within particular courses:

• Substantial Coverage denotes a specific, deliberate, and significant integration of topics related to a particular framework dimension into a course. Indicators may include two or more dimension-related course learning outcomes, discussion of the dimension topics in the official catalog description, and/or dedicating one week or more of course time to the dimension.
• Sufficient Coverage is less intensive than substantial coverage but still meaningful. For example, a single dimension-related course outcome, a brief mention a dimension-related topic in the course catalog description, and/or at least a day of course time dedicated to the dimension.
• The term touchpoint refers to either substantial or sufficient coverage of topics related to any single framework dimension.

Recognition and Catalog Tags

Courses and programs that meet the A2I2 content requirement are recognized with specific wording, tags, in their MSOE catalog entries. These are:

• Course Tags: This course meets or exceeds MSOE’s Applied AI Integration guidelines for substantial or sufficient coverage of one or more specific A²I²dimensions. For example, “This course meets or exceeds the MSOE Applied AI Integration guidelines for substantial coverage of Practical Application and sufficient coverage of Foundational Knowledge and Critical Evaluation.”
• Program Tags: The [program name] program meets or exceeds MSOE’s Applied AI Integration guidelines.

These tags permit students and other stakeholders to easily identify where and how applied AI topics are integrated in particular courses and programs across MSOE’s curriculum.

Requirements for Tagging

To receive catalog recognition, the following touchpoint and coverage metrics must be met:

• A²I² Certified Course: Substantial or sufficient coverage of one or more framework dimensions.
• A²I²Certified Undergraduate Program: a) Eight documented touchpoints, one for each framework dimension in the first two years and one for each dimension in the last two years, and b) substantial coverage of one framework dimension in the first two years and one framework dimension in the last two years.

Programs may, and typically do, exceed these minimum requirements.

Distribution of dimension coverage across multiple required courses is encouraged to reinforce learning over time and ensure applied AI exposure for all students, including transfer students.

How the A²I² Process Supports Students and MSOE’s Mission

The A²I² process is intentionally faculty-driven and adaptable. It supports course-level integration of applied AI topics that align with course topics and program needs. Some examples include analyzing algorithmic assumptions in a statistics course, applying AI tools in a senior design project, and addressing data privacy and intellectual property in a professional practice course. At the program level, mapping touchpoints across required courses ensures comprehensive coverage and coherent progression from introductory to advanced experiences, particularly in undergraduate programs.

The A²I² process is MSOE’s practical, student-focused approach to applied AI. By recognizing courses and programs that meet clear standards across Foundational Knowledge, Practical Application, Critical Evaluation, and Social Responsibility, MSOE affirms its mission and equips graduates to lead responsibly in an AI-enabled world.