What challenges did Arizona State University face before AI implementation?

Improve student support in math. Better target enrollment outreach. Process large volumes of student interaction data securely and within compliance.

What was the impact of the AI solution?

Students using Archie increased correct math answers by 6%. The enrollment propensity model was 4x more accurate than naive random guessing. Marketing campaigns using the model increased registrations by 52% compared with traditional lead scores.

Source

GCPEvidence: Medium50/100

Arizona State University builds Gemini-powered math support chatbot and AI enrollment propensity model on Google Cloud

Use case typeStudent supportUpdated Jun 13, 2026

Arizona State University (ASU) uses Google Cloud to support student learning and outreach. ASU Prep’s Archie chatbot uses Gemini to help middle and high school students solve math problems in real time by identifying errors, providing hints, and explaining problems. ASU EdPlus built an AI-powered platform that ingests enrollment and student success center audio, transcribes it, extracts insights, and combines it with web behavior data to predict enrollment likelihood.

Organization: Arizona State University
Industry: Education
Location: United States
Published: June 2026

Reported outcomes

quantified impactQuality & accuracy

+6%quantified impact+52%quantified impact

Strategic outcomes

New product / capabilityBuilt an AI math support chatbotBetter decisions & insightBuilt an enrollment propensity modelCustomer experience & trustImproved student math support

Catalog median for quality & accuracy deployments: +41% across 63 reported metrics. Compare benchmarks →

Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Quantified impact: 6% increase

Google Cloud Customer StoryJun 6, 2026Customer storyInferred claimMedium evidence strength

Students using Archie increased correct math answers by 6%.

Normalized claim

Quantified impact: 4 x increase

Google Cloud Customer StoryJun 6, 2026Customer storyInferred claimMedium evidence strength

The enrollment propensity model was 4x more accurate than naive random guessing.

Normalized claim

Quantified impact: 52% increase

Google Cloud Customer StoryJun 6, 2026Customer storyInferred claimMedium evidence strength

Marketing campaigns using the model increased registrations by 52% compared with traditional lead scores.

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: Arizona State University
Provider: GCP
Maturity: Unknown
Linked source: Google Cloud Customer Story

No explicit deployment-stage evidence found.

Customer identity supportedSource describes one deploymentMaturity evidence evaluated

Primary read

Use case focus

Showing 3 of 5

1Student support chatbot
2Enrollment propensity modeling
3Predictive analytics

Improve student support in math.
Better target enrollment outreach.
Process large volumes of student interaction data securely and within compliance.

Gemini powers the Archie math support chatbot with hint and error feedback.
BigQuery is used to ingest and analyze large volumes of structured and unstructured data.
ASU EdPlus built an AI-powered platform that converts audio recordings to text and uses a propensity model to predict enrollment likelihood from web behavior data.

Technologies

Gemini BigQuery Google Cloud Machine Learning

Students using Archie increased correct math answers by 6%.
The enrollment propensity model was 4x more accurate than naive random guessing.
Marketing campaigns using the model increased registrations by 52% compared with traditional lead scores.

Sources & evidence1

Evidence: Medium50/100Evidence strength