What is a user journey?
The Harvard Chan AI Glossary
In our classes, we often pause to explain the ideas behind AI and the language used to describe it. These posts grew out of those conversations. They’re for anyone who would like to understand AI better, with no technical background assumed.
A user journey is a connected account of how a person moves from a recognizable need or trigger to a useful resolution. It describes what the person is trying to accomplish, what they do and what happens next. It is not simply a list of screens in an application.
Consider preparing an expense claim. The journey may begin when someone receives a receipt, continue through finding the relevant policy and entering details, and end when reimbursement is confirmed. Waiting for an approval or correcting an unreadable receipt belongs to the journey even if it happens outside the product.
Consider how a person gets oriented, decides, acts and then confirms, hands off or recovers. These are different moments. A person may understand a proposed action but still need to decide whether it is appropriate. After acting, they need to know whether it succeeded and what responsibility remains with them.
An ordinary path describes what happens when everything proceeds as expected. An exception is an important departure, such as a missing receipt. A recovery path describes how work continues after a problem. Including all three prevents design from concentrating only on the easiest demonstration.
In an AI application, the journey should distinguish generating a suggestion from accepting or carrying it out. If the assistant prepares an expense description, who checks it? If it submits the claim, how does the person know? If submission fails, is the draft preserved? These questions connect interface behavior with actual consequences.
A workflow is closely related but can emphasize the sequence of work across several people or systems. A user journey focuses on the experience and decisions of a particular person. Both perspectives are useful, and neither should erase the other. A process that is efficient for an administrator may create confusion for the employee using it.
The public dental-care example raised in class followed people beyond an initial visit into treatment and later follow-up. A journey for that service should include the patient’s decisions, difficulty arranging the next visit and what happens after a missed appointment—not just the screens staff use. A specialty-clinic referral has the same design question: does the person actually reach the next agreed stage of care? Confirming that a form was submitted is not the same as resolving the patient’s need.
If you would like to find out more about AI and improve your leadership skills, consider the AI in Health Care Certificate of Specialization from the Advanced Learning Academy at Harvard T.H. Chan School of Public Health. You can take an individual course or work toward the full certificate.
AI is a fast-moving field. This explanation reflects our class discussions and related material at the time of writing. Terminology, capabilities and tools may change.
For suggested additions or corrections, please email me at tpanch@hsph.harvard.edu.
Dr. Trishan Panch
Program Director, AI in Health Care
Harvard T.H. Chan School of Public Health — Advanced Learning Academy