Starting in 2026, the CIC began funding the following interventions with the goal of removing barriers to AI education and pathways. Stay tuned for other interventions as we experiment and learn with our Partner Schools regarding proven approaches to making AI education available to all.
At most institutions, students do not take AI /ML courses until junior or senior year. The CIC funds departments to create an introductory AI and/or ML course (ideally with no/minimal prerequisites). Offered as early as the second or third semester, such a course exposes students to AI concepts well before upper-level electives, attracts non-majors, and serves as a low-barrier entry point.
While the ‘best’ time to introduce GenAI tools into the CS curriculum is still open to debate, many departments are working quickly to incorporate these tools as early as CS1 and to find ways to keep pace with the rapidly evolving landscape. Through a pilot initiative, the CIC has begun supporting departments to update their CS1 to include teaching programming with GenAI (often making GenAI literacy an explicit learning outcome) and to establish clear policies on appropriate GenAI that span all sections of a course.
Traditional math prerequisite chains — calculus series, linear algebra, and probability and statistics (most often taught by the math department) — often delay student access to AI and machine learning coursework. The CIC funds departments to develop an integrated “Math for AI” course that combines relevant math content students need while also introducing foundational machine learning concepts. This approach shortens the path to upper-level AI courses and gives departments the opportunity to show how math content directly connects to computing applications.
As departments expand their AI offerings, courses can end up covering the same material (especially foundational applied math concepts) more than once. The CIC supports schools to revisit and streamline their AI course sequence so that foundational topics are taught early on and just once, and so that faculty in the upper-level courses feel confident about building on that foundation rather than feeling the need to re-teach content.
As more and more departments launch and/or refine their graduate AI degrees, there is an opportunity to create pathways for students without undergraduate computing backgrounds to also be able to access these pathways. The CIC is working with a number of schools across the country to design and launch a discrete set of classes that present an onramp for any learn to a Master’s in AI. These work plans include curriculum development, tailored marketing and recruitment efforts and the expansion of student support services.