California Community Colleges are embracing artificial intelligence across the system. From their annual Futures Summit on September 10 to targeted efforts to stop admissions fraud, the 116 colleges in the California Community Colleges system are positioning AI technologies at the center of operations and student services.
A driving factor in this push is the alarming rise in admissions fraud. According to the state chancellor’s office, more than 460,000 requests to the statewide online application system last year were fraudulent. That surge translated to roughly $7 million in losses in a single year, prompting leaders to act decisively.
Fraudsters have increasingly leveraged sophisticated tools and stolen personal data to submit fake applications, register for classes, and apply for financial aid. The impact is twofold: lost funds and fewer seats available to legitimate students. To counter this, the colleges have partnered with tech firms such as N2N, led by Kiran Kodithala, to apply AI and machine learning to fraud detection.
Before adopting AI, many colleges relied on labor-intensive, manual reviews and basic rule-based checks. These approaches proved insufficient against networks of coordinated fraudulent applications. N2N introduced a machine learning approach that examines large volumes of application data, identifies subtle patterns, and uncovers links across seemingly unrelated records.
As Sai Guptha Grandhi, a data scientist at N2N, explains: “Machine learning is particularly effective in detecting fraud because it can analyze vast amounts of data quickly and identify hidden patterns that manual review would miss. Traditional rule-based checks catch obvious red flags, but ML models can triangulate connections—shared phone numbers, addresses, or email structures—revealing networks of fraudulent activity.”
N2N’s model uses a triangulation strategy that cross-references multiple data points on applications. The system continuously learns from new inputs and feedback, improving detection over time. Partners reported a twofold increase in identifying fraudulent actors, and one deployment at West Valley-Mission Community College District showed a 92.3% effectiveness rate after redeployment. Similar performance and a 24-hour turnaround were reported at Santiago Community College, demonstrating both accuracy and speed.
Grandhi adds that the model improves through iteration: false negatives discovered by partners are fed back into the training set; new features such as phone number histories and geolocation data are added; and outdated predictors are removed. This collaborative refinement allows the system to scale across multiple institutions while strengthening statewide fraud defenses.
Kiran Kodithala highlights the accessibility of modern AI: “It took less than three years for AI to take off. For the first time, platforms allow people of any technical background to interact with intelligent systems without specialized training.” Kodithala points out that while AI has become user-friendly, many college administrative systems remain complex—student information systems, learning management systems, parking, housing, and other administrative platforms require countless logins and security profiles.
To bridge that gap, N2N developed integration tools and AI-driven products. Their Illuminate integration platform as a service connects disparate systems via APIs. Building on that work, they developed LightLeap AI, which converts institutional systems into AI agents that can answer student questions based on their individual profiles. Importantly, N2N’s approach keeps authoritative data in the original systems and queries it securely when needed, rather than centralizing all data with a vendor.
Kodithala credits collaboration with lead partners for accelerated progress. Ivy Tech Community College implemented an automated transcript ingestion flow that processes uploads and pushes results to Banner. Foothill-De Anza Community College District partnered on the initial AI fraud model development and helped fine-tune the system using historical data and operational expertise. West Valley-Mission built a student-facing chatbot, and Rancho Santiago Community College District joined efforts to combat financial aid fraud. California Virtual Campus is exploring plugins to help faculty identify areas for lesson improvement and compliance.
The shift to online learning during the COVID-19 pandemic, combined with major data breaches that exposed millions of records, created an environment where stolen identities could be used to apply to campuses and exploit financial aid systems. Fraudsters would register for classes, collect funds, and never attend, directly impacting college finances and access for genuine students.
Echoing the operational benefits, Jory Hadsell, Vice Chancellor and Chief Technology Officer at Foothill-De Anza, described the implementation: “We were spending significant staff time reviewing applications for fraud. After running historical data through the model, fine-tuning it with admissions and financial aid teams, the deployed system has reduced manual review time and delivered strong accuracy. No system is perfect, but we discovered twice the amount of fraud we expected. As more institutions adopt the model, it improves for everyone.”
Admissions fraud remains a national challenge, and the costs can be substantial. Yet California Community Colleges are actively reclaiming territory by applying AI-driven detection tools. Solutions from N2N and ongoing collaborations across districts are saving millions, freeing seats for genuine students, and strengthening institutional resilience. With continued iteration and broader adoption, these AI efforts aim to curb fraud more effectively statewide.
This article was shared from our partners at Educate AI Magazine.