Artificial intelligence (AI) is rapidly becoming part of everyday life for students, clinicians, and educators. Tools that summarize articles, draft discussion posts, generate outlines, and assist with writing can make graduate school feel more manageable. Used thoughtfully, AI can increase efficiency and reduce administrative burden. It can help students organize ideas, review concepts, and manage heavy workloads. At the same time, the rise of AI introduces an important question for counseling education. If emerging therapists rely heavily on AI to complete assignments without deeply engaging with the material themselves, what happens when they sit down to take a national licensing exam or enter clinical practice where critical thinking cannot be outsourced? This is not a question of whether AI should exist in education. It is a question of how it is used and how it may influence the way therapists learn.
Licensing Exams Require More Than Information Recall
National counseling licensing exams, such as the NCE or NCMHCE are designed to assess more than memorized definitions. They measure clinical reasoning. Candidates must interpret scenarios, prioritize ethical decision-making, identify appropriate interventions, and recognize subtle differences between treatment approaches. Success on these exams depends heavily on pattern recognition and critical thinking. Those skills are developed through repeated exposure to concepts, discussion, reading, writing, and reflection over time. When students actively process material themselves, the brain builds connections that support recall and reasoning under pressure. If AI consistently performs the thinking portion of academic work, those neural connections may not develop in the same way.
For most of human history, knowledge has developed through repetition and immersion. Students read material multiple times, discussed ideas with peers, wrote reflections, practiced applying concepts, and gradually built understanding through repeated exposure. This process is sometimes slow and effortful, but it strengthens learning. Cognitive psychology consistently shows that repetition, retrieval practice, and active engagement help information move from short-term memory into long-term understanding. Writing, explaining, and debating ideas deepen comprehension. In many ways, graduate education mirrors this pattern intentionally.
The Difference Between Productivity and Substitution
AI can be a powerful productivity tool when it supports learning rather than replacing it.
Examples of productive AI use include:
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Summarizing lengthy readings to preview key ideas
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Generating practice questions for exam preparation
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Helping organize notes or study guides
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Brainstorming topics before writing an assignment
In these cases, the student remains the primary thinker. Problems arise when AI becomes a substitute for engagement. If discussion posts, reflection papers, or assignments are generated largely by AI with minimal personal processing, the student may appear academically successful while missing the deeper cognitive work required for clinical practice and exam success. Learning requires participation. Productivity tools should not replace that participation.
How AI Is Changing the Learning Process
AI changes the traditional pattern of learning because it can compress or bypass the steps that historically created understanding. Instead of reading an entire chapter, a student might review a summary. Instead of writing a reflection, a student might ask AI to generate one. Instead of wrestling with a concept, they might receive a simplified explanation instantly. While this saves time, it may reduce the cognitive struggle that often produces deeper learning. Struggle is not always a sign of inefficiency. Sometimes it is a necessary part of mastery. Counseling is not a profession built on scripts. In real sessions, therapists must assess safety risks, recognize patterns in client narratives, evaluate competing hypotheses, and make ethical decisions in real time. These processes require mental flexibility and analytical thinking. Graduate assignments are designed to help develop these skills. Writing a treatment plan, discussing a case conceptualization, or analyzing an ethical dilemma forces the student to slow down and reason through complex situations. The process itself builds clinical thinking. If that process is skipped, the skill development may be weakened. Critical thinking supports client safety, ethical practice, and effective treatment planning. Additionally, without this development, emerging therapists may have challenges with taking the national exams. This does not mean AI will inevitably weaken education. It means the profession must think carefully about how these tools are integrated into training, especially for current and new graduates who have yet to take the national licensing exams.
Finding a Responsible Balance
The goal should not be to eliminate AI from graduate education. AI is likely to remain part of modern professional life. Instead, emerging therapists should learn to use it in ways that support rather than replace intellectual engagement.
Responsible use may include:
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Using AI to clarify confusing concepts after attempting to learn them independently
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Creating study guides that you then actively review and test yourself on
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Generating practice exam scenarios and working through them without assistance
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Comparing AI summaries to original readings to check understanding
The key question is simple. Is AI helping you learn, or helping you avoid learning?
Students carry responsibility for their own learning, but training programs, faculty, and clinical supervisors also play an important role. Educators may need to rethink assignments, emphasize applied reasoning, and openly discuss the strengths and limitations of AI in academic work. Supervisors may also notice whether emerging clinicians demonstrate strong conceptual thinking or rely heavily on external guidance. The counseling profession has always adapted to changes in technology and society. AI is simply the latest development that requires thoughtful integration.
Final Thoughts
Artificial intelligence can be an incredibly helpful tool. It can improve efficiency, reduce administrative stress, and provide access to information quickly. Used responsibly, it may even enhance learning. But becoming a therapist requires more than access to information. It requires deep engagement with ideas, repeated exposure to complex material, and the development of strong critical thinking skills. Licensing exams will still expect candidates to think independently. Clients will expect therapists to reason ethically and clinically in real time. AI may assist the learning process, but it cannot replace the experience of truly immersing yourself in the work. The future of counseling will likely include AI. The challenge for emerging therapists is making sure it becomes a support for learning rather than a substitute for it.
Author: Dr. Steven Glasser, PhD.
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