Purdue and Google launch AI alliance with new undergraduate AI competency requirement

Purdue and Google partner to scale AI education, research, and workforce skills

Purdue University and Google Public Sector have formalized a multi-year partnership to speed up AI-enabled education, expand research, and grow the talent pipeline. Approved by Purdue's Board of Trustees, the collaboration spans a five-year commitment to the Google Partnership for Accelerated Research, an AI competency graduation requirement, TPU access for researchers, and a trusted tester program for Google DeepMind's co-scientist.

The plan also establishes a Google AI Hub inside Purdue's Hall of Data Science and AI, creating a visible anchor for joint work across campus.

• Five-year participation in Google's Partnership for Accelerated Research
• Collaboration on an AI competency graduation requirement for all undergrads on the main campus
• Access to Google Cloud Tensor Processing Units (TPUs) for research
• Trusted tester program for Google DeepMind's co-scientist
• Google AI Hub within Purdue's Hall of Data Science and AI

"This partnership with Google is a paradigm shift in academic-industry collaboration," Purdue President Mung Chiang said. "Beyond the basic type of agreements, this alliance offers comprehensive access and opportunities to the Purdue community that are rarely extended to academic institutions and places us in a very select category among top-tier research universities in the age of AI."

AI@Purdue: a campus-wide framework

The effort reinforces Purdue's AI@Purdue strategy across five areas: Learning with AI, Learning about AI, Researching AI, Using AI, and Partnering in AI. It's a whole-institution approach-teaching, research, operations, and external partnerships pulling in the same direction.

First major university to require AI competency for all undergrads

Approved by trustees on Dec. 12, Purdue will implement an "AI working competency" graduation requirement for all undergraduate students on the main campus. This is meant to move beyond theory and into practical fluency that shows up in labs, studios, and capstones.

"AI is a catalyst for scientific breakthroughs," said Karen Dahut, CEO of Google Public Sector. "By providing Purdue with Google Cloud's AI infrastructure and TPUs, we are empowering researchers to tackle global challenges with unprecedented speed. This collaboration helps ensure researchers, students and educators are using the most advanced AI, while preparing the next generation to lead an AI-driven workforce."

Infrastructure that accelerates research

With TPU access and participation in Google's accelerated research program, faculty and grad students can iterate faster on large models, multimodal work, and high-compute experiments. The trusted tester program for Google DeepMind's co-scientist signals early exposure to emerging tools, plus feedback loops that keep campus labs close to the frontier.

• Learn more about TPUs: Google Cloud TPU
• Explore research updates: Google DeepMind

"This extraordinary collaboration establishes a new benchmark for how leading research universities and innovative technology enterprises can advance scientific discovery in concert," said Dimitrios Peroulis, Purdue's senior vice president for partnerships and online. "Our students will learn from and work with technologies that represent the forefront of AI development, and they'll do so within an educational framework that emphasizes both innovation and responsible use."

What this means for educators and academic leaders

• Curriculum: Build AI fluency into general education plus discipline-specific use cases (e.g., AI for lab notebooks in biology, design critique in architecture, or code review in CS).
• Assessment: Require demonstrations of "working competency"-projects, portfolios, and scenario-based evaluations rather than quizzes alone.
• Faculty enablement: Offer short-format training, protected time for course redesign, and shared repositories of prompts, datasets, and policies.
• Responsible use: Bake in ethics, bias evaluation, and data governance across assignments-not as a one-off lecture.
• Research lift: Use TPU access and shared compute credits to unblock high-cost experiments and student-led research.

Implementation ideas for an AI competency requirement

• Define outcomes: data literacy, prompt fluency, model limitations, privacy, and domain-specific application.
• Modular approach: a short core module plus department-owned modules that match disciplinary needs.
• Capstones and clinics: partner with industry or campus units to ship real deliverables using AI responsibly.
• Quality bar: rubric-based reviews that check correctness, attribution, reproducibility, and ethical safeguards.

Operational steps to get your campus ready

• People: name a cross-functional AI steering group (academics, IT, legal, IRB, libraries, student affairs).
• Platforms: secure, auditable environments for model use; clear data classification and retention rules.
• Policy: course-level AI use statements; guidance on attribution, acceptable tools, and assessment integrity.
• Pilots: start with 3-5 courses per college; measure learning gains and workload impact; scale from there.

For departments moving now

• Audit syllabi for quick wins where AI can save time or deepen analysis.
• Create faculty "labs" to co-develop assignments and share artifacts.
• Stand up a student help desk or peer coaching for AI tools.
• Establish a review cadence to update guidelines each term.

Helpful training resources

• Browse AI upskilling paths by role: Complete AI Training - Courses by Job

The trustees' executive committee met in public session on Dec. 23 and holds authority to act for the full board between scheduled meetings. Expect more details as Purdue and Google progress from announcement to delivery and share what works across teaching and research.