New online learning experience aims to create adaptable, AI-fluent professionals
By Carolyn Tiernan
The paradox of AI education is hard to ignore: investments are going into skill-specific development, certificates, and credentials, believing they’ll translate directly into jobs. Yet, in a field that evolves so rapidly, the AI tools taught today risk being obsolete tomorrow. The key to preparing AI-ready students and professionals lies in teaching the underlying AI theories, concepts, and problem-solving approaches.
To help meet this moment, MIT Open Learning is piloting Universal AI, a new online learning experience spanning the foundations and real-world applications of artificial intelligence. Taught by MIT faculty and experts, the offering is designed to be accessible to those without a strong technical background. Specific topics covered include four key types of AI (predictive, prescriptive, multimodal, and generative); core technologies like Python, data analytics, machine learning, deep learning, LLMs, and ethics; plus domain-specific applications of artificial intelligence in action. The experience is structured into short modules designed to be updated quickly and easily as AI technology evolves.
“At Open Learning we have an ambitious goal to educate 1 billion learners in 10 years, and I strongly believe that artificial intelligence is a technology that everybody needs a baseline understanding of,” says Dimitris Bertsimas, vice provost for open learning. “I developed the idea of Universal AI several years ago and tested the concept with two diverse audiences — Greek students of all backgrounds and employees at Hartford HealthCare — with very encouraging results. Building Universal AI into the learning experience it is today, delivered on MIT Learn, is one of the reasons I was excited to join Open Learning as vice provost last year.”
The pilot program of Universal AI launched this week with a wide-ranging group of international universities, hospitals, companies, and two-year colleges. These participants will help shape the final educational offering by providing feedback on the content and learning experience. MIT Sloan is also running a special seminar this semester where students can experience the Universal AI pilot and provide feedback.
“MIT is most known for the thinkers it graduates into the world that go on to solve problems and impact the world in unique ways,” says Megan Mitchell, senior director of Universal Learning at MIT Open Learning. “With Universal AI we aim to adapt this teaching philosophy for a global audience, educating adaptable, AI-fluent professionals that are prepared to succeed in a rapidly evolving technological landscape. The variety of organizations participating in our pilot will help to validate that our offering meets this need.”
An AI learning experience universal in breadth and access
Universal AI is structured into asynchronous, self-paced modules, including foundational modules that teach AI fluency and vertical modules that teach domain-specific applications of AI. There are 10 vertical modules currently in development at Open Learning spanning fields like healthcare, supply chain, business, and sustainability, with more proposed by other MIT faculty. The learning experience is augmented with generative AI tutors that were developed by MIT engineers and researchers, and is delivered on Open Learning’s learning platform, MIT Learn.
A small cohort of employees in the Hartford HealthCare system, ranging from analysts to surgeons, participated in an abbreviated pilot earlier this summer to provide early feedback on the first modules of the Universal AI Foundational Series. They are also participating in the current pilot program.
“Hartford HealthCare is committed to providing colleagues at all levels with leading-edge professional development and training opportunities, particularly in transformative technologies like AI,” says Regina Moriarty, director of operations at Hartford HealthCare. “Universal AI is valuable to our organization because it gives colleagues at all levels a shared language and understanding of the potentials and pitfalls of AI.”
The first of several Universal Learning offerings
Universal AI is the first offering in a new collection of curricula from Open Learning called Universal Learning, which is designed to meet a growing need of students and professionals that take a unique and cross-disciplinary approach to problems. Today’s global issues — like climate change, artificial intelligence, and global health — are increasingly multifaceted, and therefore demand innovative, integrated approaches and solutions. Universal Learning offerings will be similarly cross-disciplinary, covering climate, energy, biology, healthcare, manufacturing, in addition to AI. Universal Climate is currently in development, headed by Christopher Rabe, program lead and education program director for the MIT Climate Project. Additionally, development of Universal Biology will kick off in 2026 and be led by Ron Vale, who is joining Open Learning and the Department of Biology in December.
Open Learning’s vision for scaling Universal Learning to millions of learners will be driven by the AI systems developed for the MIT Learn that enable personalized learning at scale. MIT Learn is the institute’s hub for non-degree learning opportunities, with over 12,700 educational resources available. Learners can use the “AskTIM” chatbot to support selecting the right course for them, evaluating syllabi based on desired learning outcomes, reinforcing key concepts with flashcards and video summaries, and getting help with homework and quizzes. Open Learning is actively working on additional AI systems that will enable holistic assessments, translations, and more.
Open Learning anticipates launching Universal AI to the public in early 2026. Organizations looking to get involved with Universal AI or Universal Learning can find out more here.
New online learning experience aims to create adaptable, AI-fluent professionals was originally published in MIT Open Learning on Medium, where people are continuing the conversation by highlighting and responding to this story.