Abstract
Drawing on the author’s observations as an instructor at the Sergeants Major Academy, this article examines how generative artificial intelligence (AI) appears to be creating an academic divide between students who effectively leverage AI tools and those who do not. It highlights the resulting challenges to fairness, critical thinking, and assessment integrity and explores how faculty are adapting to these changes. The article argues for a deliberate, long-term strategy to integrate AI ethically and effectively into professional military education.
Artificial Intelligence (AI) first emerged as a theoretical concept in the 1950s and has since evolved from a niche academic pursuit into a transformative force that has taken the world by storm. This technology, now woven into the fabric of modern society, presents a duality of progress and peril. On one hand, it has created unprecedented efficiencies, turning tasks that once consumed days into endeavors of mere hours or minutes. On the other hand, it has opened new avenues for individuals to gain personal, sometimes unearned, advantages. As the United States military officially authorizes the use of AI, its institutions of Professional Military Education (PME), such as the Sergeants Major Academy (SGM-A), find themselves at the epicenter of this paradigm shift. From the vantage point of an instructor, it is clear that the U.S. Army’s adoption of AI has directly and profoundly impacted the SGM-A. It also appears to be creating an academic divide between students who are adept at leveraging AI and those who are not. This chasm has forced the institution into a reactive posture, compelling it to begin the arduous process of adjusting its curriculum to ensure fairness while grappling with the broader, long-term implications of artificial intelligence in senior noncommissioned officer education. The observations presented in this article are drawn from my experience teaching resident-course students at the Sergeants Major Academy and from faculty discussions regarding student performance, assessment challenges, and the integration of generative AI into professional military education. They are offered as practitioner observations rather than the findings of a formal institutional study.
The Dawn of AI
The journey of artificial intelligence began in the mid-20th century, a period of burgeoning computational theory. Since its inception, society has eagerly taken advantage of AI’s expanding capabilities as it has grown and evolved into something far bigger and more integrated than its pioneers likely ever imagined. The contrast between the pre-AI and post-AI worlds is stark. Prior to the widespread availability of AI engines, a simple research project or the drafting of a complex document may have taken days of meticulous effort. Now, that same project can be completed in a fraction of the time, often in just a few hours or less. This acceleration of productivity is the hallmark of the paradigm shift we find ourselves in today.
AI creates profound efficiencies, allowing users to complete complex tasks in remarkably short periods. The core of this efficiency lies in the user’s ability to provide an AI system with specific, well-crafted instructions, which in turn generate a sophisticated product. This streamlined productivity allows a user to produce a greater volume of work in less time, often at a level of polish that might otherwise require considerably more time or expertise. The implications for academic work are staggering. A person who has little experience in the craft of writing essays but has cultivated experience with the use of an AI engine can now generate a detailed 2000-word essay in less than ten minutes. Conversely, a person who is a capable writer but has no experience with AI will likely take a few days to produce an essay of the same length and scope. It is this incredible potential for efficiency that eventually, and perhaps inevitably, led the U.S. Army to formally allow the use of AI within its formations.
The Military’s Green Light
As AI’s capabilities grew, its momentum became irresistible. The U.S. Army began its formal journey with AI in 2018, establishing an AI Task Force to explore the technology’s vast potential. This initial exploration laid the groundwork for a more comprehensive integration. Building on this foundation, a new pivotal moment arrived in late 2025 when the Department of War announced and officially approved the use of Generative AI and expanded access to generative AI capabilities across the department. The strategic impetus for this decision was to fundamentally improve the Army’s decision advantage, a critical component of modern warfare.
By the time the Army gave its official approval for this new category of AI, the underlying science had already been circulating for years in both popular and obscure societal circles. Consequently, organizations within the U.S. Army began using AI, often in an experimental capacity. Soldiers, always quick to adapt and innovate, took advantage of these new tools and began using them to create efficiencies in their daily tasks. Although the Department of the Army provided overarching guidance for the use of AI, this guidance was, by necessity, broad. It fell to individual military units and institutions to refine and apply this guidance to fit their specific applications and missions throughout the Army. One of the organizations most immediately and profoundly affected by this new science was the ecosystem of PME institutions, with the SGM-A at the forefront of this new and challenging frontier.
The Emerging Gap in the Ranks
The integration of AI into the academic environment of the SGM-A has not been seamless. Instead, it has created a clear and concerning divide, a tale of two very different types of students. On one side of this divide are those students who arrived at the Academy with a good practical understanding of how to use AI. On the other side are those who do not. The reasons for this disparity are varied. Some students have candidly mentioned that they have not needed to use AI in their previous jobs and therefore have little to no interest in learning how to use and apply it now. Others simply do not understand how this new science could help them in their academic or professional lives and, as a result, cannot see how to apply it effectively.
This emerging gap is not merely a matter of technical proficiency; it represents a fundamental imbalance in academic capability. Based on faculty discussions and classroom observations, this gap increasingly appeared to represent a significant academic disadvantage for some students. The most immediate and obvious area where this disadvantage manifested was in writing assignments. An instructor can readily observe the disparity: a student with a solid understanding of AI can produce a 2,000-word paper that is well-structured, grammatically correct, and comprehensive in a matter of minutes. Their peers who lack this skill must invest days of effort to achieve a similar result. This reality has forced a difficult and necessary conversation within the faculty and leadership of the Academy.
This brings into sharp focus the pros and cons of AI integration within the unique context of the SGM-A. The primary “pro” is undeniable: efficiency. In a demanding academic environment where students are balancing a heavy course load, the ability to rapidly research, outline, and draft assignments is a powerful advantage. This mirrors the very reason the Army adopted AI in the first place to enhance performance and streamline operations. Furthermore, exposing future Sergeants Major to AI is essential for future readiness. These leaders will be returning to an Army that is increasingly reliant on AI for everything from logistics to intelligence analysis. Familiarity with AI is no longer a luxury; it is a core competency.
However, the “cons” are equally, if not more, compelling. The most significant is the creation of an academic divide, as already discussed. This is not a meritocratic gap based on intellect or effort, but a technological one that threatens the very foundation of fair and equitable assessment. Secondly, there is a profound risk of atrophying critical thinking skills. The SGM-A’s mission is to develop adaptive leaders who can think critically and communicate effectively. If students become overly reliant on AI to generate their thoughts and prose, they may not develop the foundational intellectual skills required of a senior NCO. An AI can produce a well-written paper, but it cannot replicate the cognitive process of wrestling with complex ideas, synthesizing disparate information, and forming a coherent, original argument. Finally, the use of AI presents a significant challenge to the integrity of assessment. How can an instructor accurately gauge a student’s true understanding of a topic if their written work is largely the product of an algorithm?
The Faculty’s Dilemma
The faculty of the SGM-A finds itself in a difficult position. They have noticed the style and quality of writing produced by AI do not necessarily match the verbal articulation or other, less formal types of writing from the same students. This discrepancy is often the first indicator that a student is relying heavily on AI. Faced with this dilemma, the SGM-A acted. The most immediate and decisive of these actions has been a shift in assessment methodology. In some courses and instructional settings, faculty have increasingly incorporated oral assessments, presentations, graded discussions, and oral boards to better evaluate student understanding.
This shift is a direct attempt to close the academic gap and level the playing field. It is far more difficult for a student to rely on AI in a dynamic, real-time oral examination. This method forces students to demonstrate their own knowledge, to articulate their thoughts in their own words, and to engage in the kind of critical, on-the-spot thinking that is essential for a senior leader. While this is an effective stopgap measure, it also represents a significant pedagogical shift that requires instructors to develop new skills in oral assessment and to restructure their courses accordingly.
The challenge, however, extends beyond simply changing assessment methods. The faculty itself is a microcosm of the student body, with some instructors who are comfortable with AI and others who are not. To effectively guide students in the ethical and practical use of AI, the faculty must first become proficient themselves. The Academy faces the dual challenge of educating its students while simultaneously educating its educators.
A conscious and planned strategy for AI at the Sergeants Major Academy needs to start with formal, institutional instruction. Academy leadership should clearly define when and how students may use AI for research, drafting, and staff work, as well as when its use is prohibited. These instructions must define AI as an instrument that can help, but cannot replace, human judgment and efforts.
The second component of this strategy is persistent instructor training. Instructors must have organized chances to experiment with artificial intelligence systems, have access to illustrations of effective classroom implementation, and discuss moral dilemmas that they may face. Constant workshops, exchanges among colleagues, and time dedicated to revising teaching materials would enable instructors to go from random reactions to a more assured and logical process. When instructors grasp the opportunities and restrictions of AI technology, they are able to strongly demonstrate positive practices and to create tasks that reward real thinking rather than only correct prompt formation.
A third element is intentional student education on AI as a leadership competency. Rather than allowing AI proficiency to remain an informal advantage for a few, the Academy should provide all students with basic training on how to use AI for brainstorming, research, and planning, as well as how to challenge its output, identify errors, and recognize bias. Short, targeted modules embedded in existing courses can normalize AI as part of the professional toolkit, while emphasizing that it is the Sergeant Major, not the software, who remains responsible for the decisions that follow.
A fourth component of this strategy should focus on assessment. Future assessment models should combine AI-permitted and AI-restricted evaluations. Some assignments should allow students to use AI and be graded on their ability to evaluate, refine, and improve AI-generated outputs. Other assignments should require students to demonstrate their own writing, speaking, and problem-solving abilities without AI assistance. A balanced approach would allow the Academy to develop AI-literate leaders while still preserving core leadership and critical-thinking competencies.
Conclusion
The Sergeants Major Academy is in the midst of a profound and unavoidable transformation. The integration of AI is not a passing trend; it is a permanent feature of the modern world and the modern military. While initial adaptations by faculty, including increased reliance on oral assessments in some learning environments, represent a necessary first step, they are not a long-term solution. The path forward must be a proactive one. The SGM-A must develop a clear and comprehensive strategy for AI integration that includes robust training for both students and faculty, a curriculum that teaches the ethical and effective use of AI as a tool for critical thought rather than a replacement for it, and a new philosophy of assessment that can accurately measure a student’s knowledge and abilities in this new era. The goal cannot be to simply close the gap between those who use AI and those who do not; it must be to ensure that every graduate of the Sergeants Major Academy is a master of their craft, capable of leveraging the power of technology without ever losing the essential human qualities of leadership, critical thinking, and intellectual integrity.
