Generative AI Lab

GenAI-Lab at a glance

  • Term

    Spring

  • Units

    12

  • Eligible students

    All MIT students - priority given to graduate students with programming experience or MBAs who were former DS/SWE roles

  • Prerequisites

    No official prerequisite courses. WebLab over IAP recommended, at least one analytics or hands-on coding course encouraged for students wishing to participate in a project that involves leveraging the OpenAI, Claude, or Gemini APIs

     

  • Bid/Application

    Application

  • Host organization profile

    We accept a diverse range of hosts from large cap firms, startups (Series A or later), government, education, and nonprofits

  • Sample sectors

    Biopharma, cybersecurity, finance, government/nonprofit, healthcare, logistics, media, startups, tech, etc.

  • Sample projects

    Browser-use agents, multi-modal systems, LLMs for marketing content, LLMs for customer on onboarding, LLMs for simulated environments, LLMs for financial analytics, LLMs for social good, etc.

The class

Students will work in teams to develop practical, low-code solutions and strategic roadmaps for sponsor companies. While coding skills are not required, students are expected to become proficient in using various low-code generative AI tools and platforms. The course will culminate in the creation and demonstration of a proof-of-concept or prototype that showcases the potential impact of generative AI for the host company.

By the end of this course, students will be well-prepared to lead generative AI initiatives, bridging the gap between technical capabilities and business strategy in this rapidly evolving field.

The primary criterion for projects is to provide a learning experience for the students. In addition, the projects should be of high relevance and interest to a particular organization and senior managers and professionals in it.

Project teams of three to four students are expected to work independently of regular class meetings. Host organizations will cover costs of travel and lodging, if any (as approved independently by the host organization). Each project team will have an MIT- associated faculty or research mentor to provide guidance and assistance and a link to outside project hosts on an as-needed basis.

Several optional skills-based sessions will be available during the semester, where students will have the opportunity to learn more about relevant analytic techniques and address issues they are confronting during the course of project work (details forthcoming). Attendance is strongly encouraged.

Required sessions

  • February 2026

    Pitch Day

  • May 2026

    Final presentations