Refers to a planning and risk assessment exercise in which a group imagines that a project, initiative, policy, or strategy has failed in the future and then works backward to identify what may have caused the failure. Unlike a traditional “postmortem,” which analyzes problems after something has gone wrong, a premortem is conducted before implementation begins. The goal is to identify hidden risks, flawed assumptions, unintended consequences, operational weaknesses, or overlooked challenges early enough to improve decision-making and reduce the likelihood of failure. The approach is especially valuable in periods of rapid change and uncertainty because it encourages people to think critically about vulnerabilities that may otherwise be ignored during optimistic planning processes. The growing use of premortems reflects a broader shift toward proactive planning approaches designed to help organizations prepare for uncertainty, complexity, and rapid technological change.

Premortems are increasingly used in strategic planning, project management, higher education transformation initiatives, technology implementation, AI governance and deployment, public policy, healthcare, business innovation, cybersecurity and risk management, and organizational change efforts

A typical premortem exercise asks participants to imagine: “It is two years from now, and this initiative failed. What happened?” Participants then identify possible causes such as unrealistic timelines, lack of stakeholder support, poor communication, insufficient training, ethical concerns, financial problems, technology limitations, data quality issues, regulatory barriers, and unintended impacts on workers or learners

Premortems are increasingly being used in discussions about artificial intelligence as organizations try to anticipate risks before deploying AI systems at scale. Examples:

• A college implementing AI advising systems may conduct a premortem to identify possible student privacy concerns, inaccurate recommendations, or unequal impacts on different student populations.
• A employer adopting AI hiring tools may use a premortem to examine risks related to bias, transparency, workforce resistance, or legal compliance.
• A government agency may conduct an AI premortem to explore cybersecurity vulnerabilities, misinformation risks, or public trust issues before launching an AI-enabled service.

Some organizations use AI tools during premortem exercises themselves. In these cases, AI systems help generate possible failure scenarios, identify overlooked risks, simulate stakeholder reactions, summarize patterns from prior project failures, or support scenario-planning activities. However, human judgment remains important because AI-generated risks may be incomplete, inaccurate, or lack organizational context.