As artificial intelligence continues its rapid integration into nearly every industry, higher education institutions are responding not just with updated curricula but with dedicated AI laboratories designed to immerse students and faculty in cutting-edge experimentation, research, and real-world applications. A close look at AI labs at four institutions—Pace University, Foothill College, Sacred Heart University, and Bryant University—offers a detailed snapshot of how these spaces are being built, who they serve, and why they’re transforming the academic experience.
Although anyone can access free generative AI tools like ChatGPT, colleges and universities aiming to lead in AI innovation are making significant investments in infrastructure, from high-performance computing to robotics. Surprisingly, this trend is not limited to R1 research institutions. Community colleges and smaller private universities are also launching AI labs—both physical and virtual—to broaden access to emerging technologies. Each lab is driven by a common goal: to merge interdisciplinary education with hands-on experimentation, collaborative research, and workforce readiness.
AI labs address a variety of institutional needs, from showcasing data science capabilities to serving the surrounding community. At Pace University, an associate dean described the lab as a central hub to consolidate, strengthen, and extend AI initiatives, combining education, research, and external partnerships. At Bryant University, the lab promotes the university’s data science and business programs while allowing students and faculty to explore AI’s role in business operations. Sacred Heart University’s AI lab leans into societal impact and student skill-building. Professor Bob McCloud says the lab teaches students how to identify reliable data, structure it properly, and apply it through AI workflows—a critical step in building ethical and effective AI tools. Meanwhile, Foothill College, part of the AI Incubator Network sponsored by the American Association of Community Colleges, Dell, and Intel, is helping close the digital divide by offering AI education at the community college level.
From sleek tech stations to advanced robotics, the setups vary, but all are built for exploration. Pace University offers access to high-performance computing with NVIDIA GPUs, three Alienware workstations, and a Robotics Lab featuring a humanoid robot, Clearpath mobile devices, and a Shadow Robot Hand. Ph.D. students use these tools for AI-driven experiments. Bryant University has five collaborative GPU workstations, robots including Pepper and NAOv6, vehicle robots, robotic arms, and movable workspaces. The lab is purpose-built for machine learning and robotics integration. Sacred Heart features 40 Alienware systems, 24 faculty/student workstations, object recognition tools, and eye-tracking tech—all powered by three dedicated servers. It’s designed for complex research and community-focused projects. Foothill College’s lab, while more modest, supports the “AI for Workforce” program and includes robotics for hands-on learning in engineering and coding.
Most AI labs are open to the entire campus community: students, faculty, and staff. Some institutions expand access to external groups for collaboration and exposure. Pace’s lab is also used by the student-run Google Developer Group and offers networking events with New York’s tech sector. At Sacred Heart, the esports team and athletics department have incorporated AI for performance analytics. Foothill College targets neurodivergent students through its Tools for Transition and Work program. Bryant’s lab attracts prospective students and corporate partners who may eventually recruit AI-savvy students.
These labs go far beyond theory, becoming launchpads for innovation and community projects. Foothill College supports neurodivergent learners building autonomous robots, hosts exhibitions and demos during campus events, and serves as a resource for youth from underserved organizations. Sacred Heart collaborated with local government to optimize a tree-planting program, conducted athlete data analysis using AI to study performance metrics, and used convolutional neural networks to detect fraud in art authentication. Pace launched an AI Internship Experience Program, where students built models to classify and generate visual content such as butterflies and Minecraft themes. It also offered a global online course focused on equity-centered AI design, taught by a global faculty team. Bryant data analytics students researched AAA travel data to predict trip cancellations, while the lab also hosts corporate partner projects, integrating students into real-world business analytics scenarios.
These AI labs aren’t just high-tech showpieces—they’re strategic investments in the future workforce. Students emerge with not only technical skills in machine learning, robotics, and data modeling, but also with soft skills like project management and data ethics. As Bob McCloud of Sacred Heart explains, “We teach students to define scope, select and structure reliable datasets, and apply those to real-world solutions.” The ability to not only code but to interpret and manage information effectively is what sets these programs apart.
With support from tech giants like Intel and Dell and demand from both students and employers, AI labs are poised to become a standard feature of the college experience, particularly as generative AI tools and robotics become more deeply embedded in everyday life. Universities that position themselves early with practical, interdisciplinary AI training will likely be the ones producing the most prepared graduates for tomorrow’s digital economy.
As AI continues to reshape industries and redefine digital literacy, higher education is rapidly evolving from passive instruction to hands-on, future-focused innovation. And on campuses across the country, AI labs are leading the charge.
