Our Approach

How we score AI readiness
in higher education

The Research Process

Independent, Evidence-Based Research

AIREDEX™ scores are the product of multi-layered research conducted by our team, assisted by advanced AI research tools. We draw on a wide range of publicly available information, including institutional announcements, academic program data, research publications, industry partnerships, and policy disclosures. This helps us build a comprehensive picture of each school's AI readiness.

We refresh our research on a regular basis to keep our scores relevant. This helps us track new mandates, partnerships, and progress that schools make on an ongoing basis. The best way to stay current on the schools you care about is to -- we will notify you when a school you are interested in makes progress, and when new schools are added to our ratings.

AIREDEX™ is an independent organization. We are not affiliated with, sponsored by, or endorsed by any college or university.

Scoring Framework

Four pillars of AI readiness

AIREDEX™ uses a proprietary system to evaluate the AI readiness of every college and university we score. This system measures four distinct aspects of each school's approach to AI, which we break into specific pillars, each described below. All four pillars are evaluated exclusively through the lens of the undergraduate experience.

01
Pillar 01
Institutional Commitment

Has institutional leadership made AI a stated priority? Where we find evidence of dedicated AI leadership roles, AI-specific strategic planning, meaningful resource allocation, and AI infrastructure embedded across the entirety of the school, we are able to evaluate the depth of that commitment -- and distinguish genuine investment from a short-term response to trends.

02
Pillar 02
Curriculum Integration

Curriculum is where AI readiness has its most direct impact on the undergraduate student. A school should be incorporating AI across disciplines, not just within computer science or engineering. We look for AI integration across majors including Business, Law, Public Policy, Humanities, and other fields -- because the AI revolution will reshape every profession, not just the ones that write code.

03
Pillar 03
Industry Partnerships

Many schools form partnerships with public and private tech companies to advance AI research, develop curriculum, and build shared infrastructure. When we find evidence of these relationships, it sends a strong signal that the institution is actively engaged with the industry -- which can pay real dividends for students in the form of internship pipelines, recruiting access, and exposure to real-world AI work before graduation.

04
Pillar 04
Research Depth & Access

A school's research output is one of the clearest indicators of how seriously it takes any academic discipline -- and AI is no exception. A school associated with cutting-edge AI research signals to the broader industry that AI is taken seriously there, which can reflect positively on its graduates. We also look for evidence that undergraduates have genuine access to that research environment.

A(I)ttitude™

Every institution has a position on AI, whether they have articulated it or not. Some are leaning in aggressively, integrating AI across academics, operations, and strategy, while others may be just starting to explore. Our proprietary A(I)ttitude™ designation synthesizes each school's attitude toward AI across multiple data points. It is not a scored pillar -- it is a qualitative label that distills a lot of analysis into a sentiment that is easy to understand at a glance.

Leading EdgeAI is central to the institution's identity and strategy
ProgressiveStrong forward momentum with meaningful AI investment
NeutralSome AI activity present but no clear institutional stance
CautiousLimited AI engagement; slow or hesitant adoption
ResistantEvidence of active resistance or institutional opposition to AI
Fair Comparison

We don't compare apples to oranges

Scoring a small liberal arts college against a major research university on the same absolute scale would be unfair, and misleading. A school with 1,800 undergraduates cannot be expected to have the same AI infrastructure as an institution with 50,000 students and a multi-million dollar research budget.

AIREDEX™ classifies each institution we evaluate into one of three cohorts based primarily on undergraduate enrollment size. Students considering a small college with a few thousand undergraduates should have different expectations for AI infrastructure and resources than students looking at a flagship research university enrolling 50,000. Every school is measured against peers of comparable scale, so that prospective students and applicants can better evaluate whether the school they are interested in is genuinely preparing them for a world where AI fluency will impact their career outcomes.

National University
Large research universities, typically 20,000+ undergraduates with major research infrastructure.
Regional University
Mid-size institutions, typically 10,000 to 20,000 undergraduates.
Small University
Smaller institutions, typically under 10,000 undergraduates.
Transparency

Showing Our Work

While our research process and algorithms are proprietary, we make a point of publishing our key findings directly on each school's profile, along with the sources that informed our analysis.

AIREDEX™ scores are based solely on publicly available information at the time of research. We make every effort to identify relevant developments, but cannot guarantee completeness. Scores may not reflect recent announcements, unpublished initiatives, or information not accessible through public sources.

Get In Touch

Questions About a Score?

If you represent a college or university and have questions about your AIREDEX™ score, or believe our research is missing key information, we welcome your outreach. We review all institutional inquiries.

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