AICoP: How SPS Is Embedding AI School-Wide
The AI Community of Practice welcomed the School of Professional Studies for a session on what coordinated, school-wide AI adoption actually looks like in practice. Mark Ritzmann, Mandeep Brahmbhatt, and Michael Fleming walked attendees through how SPS has woven AI into its academic programs, administrative operations, and faculty development — and unveiled a new SPS AI Lab designed to consolidate the work into a single home.
The throughline of the session wasn't a tool or a feature. It was an argument: that adoption sticks when leadership, academic technology, and administration push in the same direction, and when the work is grounded in experience rather than theory.
Culture First, Then Tools
Mark opened with a point he returned to throughout the hour: SPS's progress is downstream of top-down support from Dean Troy Eggers and the senior associate deans. He described a recent all-admin meeting that turned into an impromptu show-and-tell — every person stood up to share how they were using AI in their work. One example stuck out: the facilities team had used AI to generate renderings for a 60th Street office redesign, complete with links to purchase the furniture in the images.
That cultural foundation, Mark argued, is what makes the rest of the strategy work. SPS's three-part overarching goal — teaching AI to students, teaching with AI to support faculty, and using AI to improve operational efficiency — has spawned working groups, communities of practice, and what Mark wryly called "a committee to manage the committees." Enthusiasm at SPS isn't a problem the team is trying to solve. It's the raw material they're trying to channel.
A Structured Pathway for Faculty
Michael Fleming, Senior Director of Online Support and Academic Technology, presented SPS's three-level model for faculty AI adoption: literacy, then tool proficiency, then pedagogical integration. The school built an asynchronous AI Teaching & Learning Resource Guide — adapted from Stanford's literacy framework, covering functional, ethical, rhetorical, and pedagogical dimensions — so any faculty member can build a foundation before touching the tools.
From there, faculty can attend a new Practical AI Tools Training, launched this spring and now part of the standard ed-tech program every semester. It covers the three centrally available tools: CU-CHAT, Gemini, and NotebookLM. Notably, the team frames features like Gemini Gems in tool-agnostic terms — "anatomy of a Gem" rather than Google-specific terminology — preparing faculty and students for skills that transfer across platforms.
Two in-person Faculty AI Summits, led by Karen McFadden and Eric Nelson, brought full-time and adjunct faculty together for use-case roundtables, collaborative work time, and a memorable live demonstration where an instructional designer interrogated an AI rubric generator Gem in real time — a pointed illustration of why human-in-the-loop matters.
Experiential Training for Staff
On the administrative side, Mandeep Brahmbhatt, Director of Information Systems, described a six-part lunch-and-learn series that has become the best-attended programming in SPS history. The series progresses from data classifications and privacy to advanced use cases and a staff-led show-and-tell, with data analytics planned next.
Mandeep emphasized that training only goes so far before people need to put their fingers on a keyboard. SPS leans heavily on low-stakes group exercises — including one memorable scenario asking teams to draft a press release, signage, and parent communications for "violent aggressive squirrels attacking students on campus." The format works precisely because it's silly enough to lower the stakes for hesitant adopters.
The SPS AI Lab
The session closed with the announcement of the SPS AI Lab, funded by senior leadership and built on five pillars: thought leadership white papers (5–7 pages, topic-specific — AI in finance, healthcare, legal), applied research focused on workplace AI skills, corporate partnerships tied into the school's 19 master's capstones, a software sandbox giving students and alumni access to industry tools through academic licenses, and a centralized asset library. The site, ai.sps.columbia.edu, is targeted to launch in the coming weeks.
Breaking Down the Walls
The Q&A surfaced a familiar Columbia challenge: decentralization. Victoria Mulaney Brown, Director of Academic Integrity, noted that SPS's model is exactly the kind of comprehensive support faculty across the university need. Pariksit confirmed that CUIT is developing a centralized AI literacy program that will draw directly from SPS's work rather than duplicate it — a sign that the islands of excellence are starting to connect.
Takeaway
SPS offers a working answer to a question every school at Columbia is trying to solve. The faculty pathway, the admin series, and the new AI Lab aren't separate programs — they're connected infrastructure, designed around experiential learning, responsible use, and existing governance frameworks rather than parallel ones. As CUIT moves toward centralized literacy resources, the SPS approach is a strong reference point for how to turn enthusiasm into durable practice.
Also announced during the session: Columbia has signed its contract with Anthropic and is doing a soft launch of Claude for web and API. Claude for web is $300 per user per year. The API — which includes Claude Code — is billed separately as pay-as-you-go at Anthropic's token rates, with a hard budget cap that shuts off access when the limit is reached. Access is available to faculty, researchers, and administrators (not students), and Claude is currently approved for sensitive and confidential data — but not HIPAA, as the BAA is still in progress. Requests go to [email protected] with a chart string.
For questions, contact: [email protected]. For training and consult inquiries: [email protected].