After a decade of meteoric growth, computer science education in the United States has hit a sudden, jarring inflection point. For years, the narrative in higher education was defined by an insatiable hunger for coding skills, with enrollment numbers swelling at institutions across the country. However, the latest data reveals a stark reversal: undergraduate enrollment in computer and information sciences at four-year institutions has dipped by 8.4 percent this year.
As the tech industry grapples with the transformative, and often disruptive, power of artificial intelligence, students and educators alike are reassessing the value of the traditional degree. In New York City, the City University of New York (CUNY)—the nation’s largest urban public university system—finds itself at the epicenter of this shift, struggling to balance a legacy of explosive growth with a new, harsher reality of a cooling entry-level tech job market.
A Decade of Growth, A Year of Contraction
The current decline at CUNY is particularly striking given the institution’s trajectory over the last ten years. Between 2014 and 2024, while overall university enrollment across the system faced headwinds, computer science enrollment surged by a staggering 146 percent. It became a primary engine of social mobility for thousands of first-generation and low-income students.
However, a recent report from the Center for an Urban Future (CUF) reveals that this momentum has stalled. Data provided by the university system indicates that enrollment in computer science programs plummeted 15 percent between 2024 and 2025, falling from 10,330 to 8,819 students. This contraction occurs against a backdrop of increasing total enrollment at CUNY, suggesting that students are intentionally pivoting away from a field that, until recently, was viewed as a guaranteed ticket to a high-paying career.
The cooling of interest is not occurring in a vacuum. Since 2022, entry-level tech jobs in New York City have declined by 49 percent. This contraction in hiring, coupled with "AI anxiety"—the fear that emerging technologies may automate entry-level programming roles—has cast a long shadow over the classroom, forcing administrators to ask: What does a computer science education need to look like to remain relevant in an AI-first economy?
The Capacity Crisis: A Structural Bottleneck
Behind the enrollment figures lies a more systemic issue: an instructional capacity crisis. Eli Dvorkin, editorial and policy director at the Center for an Urban Future, argues that CUNY’s decade of rapid expansion was not met with a commensurate investment in faculty.
"Just a few years ago, a computer science degree alone could take a student pretty far," Dvorkin noted. "But in today’s much tougher entry-level job market, students need more applied skills, exposure to AI in context, real-world projects, industry connections, and faculty who have the insights to help them connect to careers and enough time to mentor them."
The CUF report, which draws on more than 75 interviews and an exhaustive analysis of CUNY’s budgetary and course data, paints a grim picture of student-to-faculty ratios. While student demand skyrocketed for ten years, the number of full-time computer science faculty at four-year CUNY institutions grew by only 21 percent. Worse, community college campuses saw a 22 percent decline in full-time CS faculty.
At Queens College, the strain has become acute, with the student-to-faculty ratio ballooning from 16-to-1 to 40-to-1. At Hunter College, Ping Ji, the chair of the computer science department, estimates the ratio is now closer to 50-to-1—far exceeding the university system’s internal target of 14-to-1 for STEM fields.
The Student Experience: Lost in the Lecture Hall
The human cost of these ratios is felt most keenly by students, who often find themselves navigating massive introductory courses with little to no personal guidance. Oluebube Onwuamaegbu, a 2025 Hunter College graduate now working as a software engineer at Amazon, recalls her introductory Python course, which hosted nearly 800 students.
"There were a lot of us. I wasn’t impressed," Onwuamaegbu said. "There’s not really much asking questions to your professor because a billion other people have their hands raised. And then on top of that, I’m really shy, so I’m not trying to ask a question in case it comes off dumb."
The pedagogical limitations are profound. Faculty are often reduced to delivering lectures through headsets to cavernous rooms, a far cry from the mentorship-heavy environment required to master complex programming paradigms. Furthermore, the curriculum has struggled to keep pace with industry standards. Onwuamaegbu noted that her coursework heavily emphasized C++, a language she rarely encounters in her professional role. "In any of the interviews I’ve done, I have never had someone prefer C++," she remarked.
This disconnect is underscored by the data: across four of the colleges analyzed in the report, only 19 of the 79 full-time computer science faculty members possessed prior industry experience. Without professors who have walked the halls of modern tech companies, bridging the gap between theoretical computer science and applied, market-ready skills becomes an uphill battle.
Institutional Roadblocks: Why Hiring Is Stalled
Why hasn’t CUNY simply hired more faculty to meet the demand? The Center for an Urban Future identifies several bureaucratic and economic barriers that have left the university system, in Dvorkin’s words, "trying to recruit computer science professors with one hand tied behind its back."
The primary culprit is compensation. Between 2015 and 2025, CUNY consistently advertised the lowest median annual salary—approximately $79,000—for computer science faculty among comparable institutions in New York City. In a field where private-sector compensation is astronomical and research universities offer significant start-up packages, CUNY struggles to compete.
Beyond salary, the hiring process is notoriously sluggish. Researchers documented multiple instances where promising candidates withdrew from consideration because the university’s internal approval processes dragged on for months, missing the peak hiring season. Furthermore, resources are distributed unevenly; some new hires receive as little as $20,000 to establish research labs, a pittance in a field that requires high-end computing power and specialized equipment.
A Path Toward Adaptation: Official Responses
Despite these hurdles, CUNY leadership maintains that they are actively working to reform the system. Aankit Patel, university dean for technology and computer and information science, points to several high-level initiatives designed to bridge the gap.
The university has recently secured a $75 million gift from the Simons Foundation, the largest donation in the school’s history, specifically earmarked for research computing, artificial intelligence, and the hiring of up to 25 new faculty members. Additionally, the launch of the "CUNY Tech Futures" program and the establishment of the CUNY AI Lab signal a move toward more integrated, hands-on learning.
"We are working closely with our city partners to respond to the moment and hopefully create a curriculum that’s meaningful to students as they try to figure out how to navigate the changing job market," Patel stated.
For students like Mohamed Elmonoufy, a graduate of the New York City College of Technology, these programs have already provided a lifeline. Despite working full-time as a taxi driver throughout his studies, Elmonoufy utilized the flexibility of CUNY’s scheduling to land an internship and eventually secure a role as an AI trainee at Openigloo. His story highlights the potential of the system when it successfully aligns its academic offerings with professional pathways.
Implications: The Future of Urban Tech Education
The path forward, according to the Center for an Urban Future, requires more than just stop-gap funding. The report calls for an overhaul of the funding formula to reflect the true cost of computer science education, which involves expensive lab maintenance and specialized faculty retention.
The recommendations are clear:
- Accelerate Faculty Hiring: Streamlining administrative approvals is non-negotiable if CUNY is to remain competitive with the private sector and other universities.
- Dedicated Investment Fund: A specific, ring-fenced fund for CS faculty salaries and research start-up packages would alleviate the current recruiting crisis.
- Industry-Academic Partnerships: Expanding the "Practitioners-in-Residence" model to ensure that classrooms are staffed by professionals who understand current industry tools, such as generative AI and cloud infrastructure.
The stakes are high. For many of New York’s low-income, first-generation students, CUNY is the primary gateway to the middle class. If the university cannot evolve to meet the shifting demands of the tech sector, that gateway may narrow, leaving thousands of talented, motivated students behind.
As Professor Ping Ji noted, the faculty at CUNY are often doing the work of two or three people, fueled by a dedication to their students that transcends their limited resources. Quoting a Chinese proverb—"What the cow eats is grass; what it produces is milk"—Ji captures the essence of the CUNY mission. The faculty are making the most of what they have, but for the sake of the students, the system must eventually provide more than just grass. The future of New York’s workforce depends on it.
