Navigating Academic Adaptation in an AI-Enabled World: Understanding the Stages of Grief
Stage 1: Denial
Stage 2: Anger
Stage 3: Bargaining
Stage 4: Depression
Stage 5: Acceptance
Embracing Change for a Future in Higher Education
Navigating the Transition: Academics in an AI-Enabled World
As we step further into an AI-enabled world, academics are at a crossroads, faced with the choice to embrace generative artificial intelligence (GenAI) or resist it. This shift brings mixed emotions, particularly for those who fondly remember the “good old days” of traditional assessments, the art of academic writing, and the gradual development of independent thinking. Alongside those nostalgic feelings, deeper existential concerns about identity, professional value, and the potential for automation loom large.
In navigating this complex transition, managing responses to GenAI extends beyond technical or pedagogical changes. Emotional responses play a critical role, echoing Elisabeth Kübler-Ross’ five stages of grief: denial, anger, bargaining, depression, and acceptance. Here’s how these stages manifest in academia and ways to guide colleagues through them.
Stage 1: Denial
Denial acts as a defense mechanism, cushioning the impact of change. Many academics initially refuse to accept GenAI’s relevance, questioning whether it truly has a place in their practices despite its growing adoption among students.
What could help: Start with low-stakes conversations among teaching teams or within academic groups. Focus on how students utilize GenAI for tasks like idea generation or article summarization. Sharing examples of adjusted assessment briefs or guided GenAI exercises can spark curiosity rather than fear.
Stage 2: Anger
Once denial fades, feelings of frustration and anger often emerge. Academics may direct these emotions toward AI companies or feel threatened about job security and a loss of authority.
What could help: Acknowledge these emotions as legitimate. Create spaces for open dialogue about assessment integrity and workload concerns. Organizing challenges for redesigning assessments can channel frustrations into productive outcomes.
Stage 3: Bargaining
At this stage, academics seek to negotiate and find compromises. Integrating GenAI tools into current practices is a common approach, but bolder actions may be necessary.
What could help: Support experimentation with GenAI while addressing its limitations openly. Facilitate discussions among colleagues about specific concerns such as assessment integrity, and encourage shared learning across departments. This is an opportune time to co-design guiding principles that reflect collective insights.
Stage 4: Depression
A sense of loss marks this stage as the traditional education system evolves. Institutional support may exist but can often appear fragmented and driven by individuals rather than holistic strategies.
What could help: Peer support is crucial during this phase. Establishing small communities of practice and scheduling training can significantly bolster morale. Aim for continuous progress rather than striving for unattainable perfection.
Stage 5: Acceptance
In this final stage, individuals come to terms with the reality of the situation and begin to forge pathways forward. Acceptance doesn’t equate to complete confidence; often, it is a quiet recognition that genuine transformation is challenging.
What could help: Shift the focus from short-term compliance to long-term adaptation. Investing in staff development, redesigning curricula with AI considerations, and creating shared policies for responsible use are essential steps. Acceptance serves as a foundation for thoughtful and ethical engagement moving forward.
Conclusion
The journey toward adapting to GenAI is not linear; revisiting earlier stages or bypassing them entirely is common. This framework underscores the importance of proactive engagement, collaboration, and supportive leadership. Ultimately, the goal is to shift from mere acceptance to long-term adaptation, fostering innovation that prepares students for an AI-enabled future.
Michael Mehmet is an Associate Professor in Marketing at the University of Wollongong School of Business, Australia. Rushana Khusainova is a Senior Lecturer in Marketing at the University of Bristol Business School, United Kingdom.
Navigating this transition is crucial as we look to the future of education, preparing not just ourselves but also the next generation of thinkers and leaders.