Generative AI Lab

15.S04 SSIM Generative AI Lab: Action Learning Seminar on Generative AI, its Applications, and the Digital Economy

The rapid advancement of generative AI technologies is transforming business processes, decision-making, and innovation across industries. Organizations worldwide are grappling with the challenges and opportunities presented by these powerful new tools. We are at the forefront of a new era in artificial intelligence that offers unprecedented potential for both individuals and businesses.

The purpose of Generative AI Lab (GenAI-Lab) is to pair student teams with cutting-edge projects involving generative AI technologies as they apply to real-world business challenges and opportunities. The focus of these projects is on strategic implementation and practical application, emphasizing how generative AI can drive innovation and solve complex business problems.

Key objectives of the course include:

1. Providing students with hands-on experience in applying generative AI tools to solve real business challenges.
2. Developing strategic thinking skills in identifying and leveraging generative AI opportunities within organizations.
3. Fostering an understanding of the current capabilities, limitations, and ethical considerations of generative AI technologies.
4. Equipping students with the skills to effectively communicate the value and impact of generative AI solutions to business stakeholders.
5. Exposing students to a variety of industries and use cases for generative AI, broadening their perspective on its potential applications.

Interested in hosting a project?

Please contact Tim Valicenti at tvalicen@mit.edu for more information.

Applying generative AI to real business challenges

In this full-term course, teams of MIT Sloan students will take on semester-long corporate projects related to generative AI. Projects will include: 

• developing AI prototypes
• writing strategy memos on the implications of generative AI developments
• analyzing and assessing deployments of generative AI systems 
• developing AI usage policies for a marketplace business
• value-chain analysis and investment memo for VC firm making AI investments 

Generative AI Lab (GenAI-Lab) will leverage industry connections of MIT Sloan research centers (including the Initiative on the Digital Economy, Center for Information Systems Research, and Center for Collective Intelligence) as well as faculty connections to technology companies/investors to create a diverse set of projects from a variety of companies and industries. We will use some class time to discuss a rotating team's issues in depth and technical aspects of business implementations of generative AI, with the rest of class time used for consultation with mentors and rolling office hours. In addition, we will offer lectures and readings drawing on frameworks and material developed in 15.S68 Generative AI for Managers. These include ways of thinking about value creation, risks and benefits, competitive strategy, and job redesign.  

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.