Publishing Disclaimer: In all of its publications and products, Military Review presents professional information. However, the views expressed therein are those of the authors and are not necessarily those of the Army University, the Department of the Army, or any other agency of the U.S. government.

---

 

Balancing Artificial Intelligence with Army Leadership Competencies and Attributes

 

André Nelson
Matthew J. Scott, PhD

 

Download the PDF

 

Technology is a useful servant but a dangerous master.

—Christian Lange

Artificial intelligence (AI) is reshaping military operations, offering unprecedented capabilities in data processing, situational awareness, and decision-making. The Army provides specific guidance that encourages broad use of AI and warns of known pitfalls, such as hallucinations, bias, security risks, and even potential exploitation by our adversaries.¹ However, integrating AI into command and control presents challenges that require deliberate adaptation of leadership practices. Recent operations, such as Ukraine’s drone campaign and Israel’s integrated strike, underscore the transformative potential of human-to-machine teaming.² These examples reveal the future of warfare is not about replacing human judgment with AI but rather blending human intuition with machine precision to achieve operational superiority. Army doctrine clearly states, “war is … a fundamentally human endeavor.”³ This article explores the critical balance between AI’s computational power and the enduring human-centric qualities of leadership through the lens of Army doctrine. Using the Army’s leadership requirements model (LRM) as a framework, it examines how AI can enhance decision-making, communication, and leader development while addressing risks such as ethical dilemmas and overreliance on technology. This article mentions various AI applications to spur exploration of available tools, but its overarching goal is to frame a doctrinal, balanced, judicious approach to the use of AI in its current state while acknowledging that its rapid advancement will continue to change the cognitive leadership landscape.⁴ The analysis concludes with actionable recommendations to ensure AI serves as a complement to, rather than a replacement for, human leadership.

LRM Refresher

Readers of this journal likely recognize the LRM (see figure 1), but a short refresher provides necessary background and a reference point for this article. This refresher and subsequent deeper descriptions of the LRM align closely with established doctrine found in Army Doctrine Publication (ADP) 6-22, Army Leadership and the Profession, to ensure a solid foundation. This article paraphrases selected doctrinal passages but claims no credit for the ideas therein. As outlined in ADP 6-22, the LRM delineates what an Army leader does (competencies—DO) and is (attributes—BE and KNOW). The LRM’s competencies and attributes are gleaned from historical experience, applicable to all echelons and Army organizations, and validated by scientific research.⁵ The LRM remains exceptionally relevant in the AI era, providing a structure for effectively integrating technological advancements into established, human-centric leadership practices.

The LRM’s leader attribute categories of character, presence, and intellect capture durable personal characteristics that can be shaped over time through life experience and reflection. The attributes nested within each category enable leaders to develop, demonstrate, and apply the competencies that make them effective leaders. These leadership constructs are highly interrelated. For example, building trust appears in the model under the leads category but clearly influences whether an Army leader develops and achieves as well; thus, the implications of AI for a given competency or attribute have far-reaching effects. Mapping all these relationships and implications would far exceed current space limitations, so the concepts in this article should be prudently applied to multiple leadership behaviors that appear in Army doctrine.

Implications of AI for LRM Competencies by Category

Leads. Army leaders lead others by effectively communicating a clear purpose, direction, and motivation to their followers.⁶ AI enhances a leader’s ability to communicate by synthesizing complex information into clear, actionable insights (see figure 2 for specific AI-enhanced leadership tasks). For example, generative AI tools can draft mission orders, summarize intelligence reports, and provide decision-making frameworks. Additionally, machine-learning algorithms can analyze patterns in communication effectiveness, providing tailored suggestions to improve clarity and engagement. Decision optimization and data orchestration can utilize AI systems to further assist leaders by integrating data from multiple sources, enabling them to prioritize and structure their communications to align with mission objectives. Agentic AI systems, such as autonomous assistants, could provide real-time actionable recommendations based on predefined parameters, enhancing a leader’s ability to adapt their communication strategies dynamically.

However, the ease and apparent effectiveness of AI-powered decision-making and communication can diminish independent judgment through overreliance on technology. Leaders must retain ownership of their decisions and communications while demonstrating their own expertise and judgment. Leaders who send AI-generated communications without a citation might appear less decisive, knowledgeable, or authentic. Perceptions like these can disrupt followership, undermining efforts to lead others and extend influence beyond the chain of command. Recent experiments in the private sector show employees view AI-generated communications as less helpful and more dramatic than those from a human executive, even when the AI was trained on that executive’s personal communications.⁷ Furthermore, employees in these experiments correctly identified AI-driven communications significantly more often than the 50 percent rate expected from random guessing (59 percent). Together, these findings strongly suggest AI-driven communication without human authenticity undermines leadership.

Army leaders are role models who lead by example. While technical savvy and adaptability are essential, overreliance on AI can convey inauthenticity, apathy, deficient reasoning, and other negative traits, setting a poor example for followers and peers. Building trust enables every aspect of outward-focused leading, developing, and achieving, because trust is the foundation of meaningful relationships. Leaders must be seen as reliable, competent, and authentic to gain the trust of those who often depend on them for their own well-being. The perception that a leader outsources their decision-making and communication to a machine can short-circuit the sense of shared experience that builds trusting relationships.

When leaders let their decision-making and communication skills atrophy, situations that disable access to AI will be especially damaging to the trust they have built. Regaining trust is often difficult or impossible once it has been breached. Contemporary soldiers understand AI is now embedded into operations but will likely respond best to leaders who exercise careful human judgment and transparently cite AI for its contributions. Leaders must balance the benefits of AI with the need to maintain their own judgment, authenticity, and trustworthiness, ensuring their leadership remains human-centric and resilient in dynamic environments. In an AI-enabled environment, the leader’s role must evolve. Leaders shift from being the primary disseminator of information to being the primary source of inspiration and sensemaking, contextualizing the data provided by machines and connecting it to a shared purpose.

Develops. Effective Army leaders develop themselves, others, and the profession through various means that can all be affected by AI usage. An Army leader who prepares self also pursues self-development, which in turn improves their own leadership skills and their ability to improve others and their organizations. AI supports personalized development plans and constructive feedback by analyzing performance data and identifying areas for improvement. For instance, generative AI tools can provide tailored recommendations for professional military education (PME) or suggest assignments that align with individual career goals. Machine-learning algorithms could further enhance this process by predicting leader development needs based on historical data, identifying patterns in career progression, and analyzing team dynamics.

Additionally, decision optimization/data orchestration AI systems could integrate data from multiple sources to help leaders prioritize development initiatives and align them with organizational goals. Agentic AI systems could assist in real-time monitoring of team performance and morale, providing actionable insights for immediate intervention. AI-driven platforms like Leaders Enhanced and Applied Doctrine System (LEADS) and Emergent Leader Immersive Training Environment (ELITE) revolutionize training by offering personalized, dynamic scenarios that adapt to performance, providing real-time feedback and accelerating skill acquisition.⁸ These tools automate administrative tasks, freeing leaders to focus on mentorship and fostering a positive environment for growth.

However, scientific studies confirm overreliance on AI weakens critical thinking, problem-solving skills, and intellectual fitness by reducing the need for deep cognitive involvement.⁹ Neuroscientific experiments reveal that essay writers who relied exclusively on generative AI showed up to 55 percent less brain network connectivity, struggled to recall the content of their essays, and reported less content ownership.¹⁰ Contested operational environments with technological disruption could have disastrous results for leaders with atrophied or underdeveloped cognitive abilities. Effective leaders are prepared for the unexpected, though doctrine and the evolving nature of warfare make clear that technological disruption is to be expected. Thus, effective leaders must be able to think and communicate using their own intellectual power.

Leader development in organizations requires creating a positive environment that promotes and rewards cognitive skills at the individual and team levels.¹¹ Unwavering deference to AI can reduce the diversity of available perspectives, experiences, and skills in a team by disincentivizing independent thought. Large-language models, when used in isolation, can only leverage what has already been written and produce outputs according to predefined algorithms, effectively resulting in a highly advanced form of groupthink. If a team’s collective cognitive abilities have already atrophied from habitual cognitive offloading, organic brainstorm sessions will be a shadow of what they could be when individuals bring their own brands of cognitive skill to the table. Leaders must deliberately encourage individual contributions and critical evaluation of AI outputs to foster intellectual diversity and team dynamics. Leaders remain responsible for creating a climate where mistakes are learning opportunities and for investing the time needed to build cohesive teams.

The Army most often builds leaders from within its ranks rather than hiring developed talent, placing a premium on the develops others competency. Effective Army leaders prepare their subordinates for increasing levels of responsibility. Subordinates find such preparation in the institutional, operational, and self-development domains, all which can intersect with AI for positive and negative outcomes.¹² The relationship of AI and the institutional domain continues to evolve.¹³ Outside the institutional domain, leaders directly develop subordinates by getting to know them through conversation and observation, thoughtfully assigning tasks, providing feedback, advising their self-development, and building cohesive teams. All these activities depend on trustful, personalized relationships in which subordinates sense that leaders prioritize their best interests, the organization, and the Nation. Using AI opaquely for decision-making and communication can breed suspicion and distrust in supervisors, peers, and subordinates. Personalized development plans depend on authentic human relationships that include understanding individual characteristics and needs. While AI can effectively analyze performance data, it cannot deliver constructive criticism with authentic empathy and understanding, nor can it replace the personal investment needed for mentorship.

Completing the “develops” category of competencies, Army leaders must steward the profession, sustaining readiness and lethality into the future and improving their organizations beyond their tour of duty. The chief of staff of the Army has given us a mandate to strengthen the profession through written discourse that AI can enhance in some ways and hamper in others.¹⁴ Overreliance on AI can stifle human creativity, critical thinking, and the ability to write fluently. Strengthening the profession through writing (and other means) involves formulating new ideas and adapting to new problems, something AI remains ill-suited to accomplish. Creatively solving new problems through writing and transformation in contact is still a human endeavor because AI lacks humans’ sense of self, which enables us to orient to new problem spaces.¹⁵ Humans are still far better at recognizing and adapting solutions to emerging problems because we can predict how our capabilities should perform in different environments, whereas AI tends to apply its limited set of programmed reasoning models across contexts. For tools like generative AI, that set of solutions emerges from interactions with the data it has been trained on. Unless humans continue to seed the corpus with original ideas, AI becomes an echo chamber that will not keep pace with the collective problem space. Stewarding the profession also requires leaders to support personal and professional growth for members of their organizations through means such as PME and assignments that broaden and develop. Authentic interactions and role modeling set an example for subordinates and then others will be inclined to follow.

Leaders must balance the benefits of AI with the need to maintain their own intellectual fitness, creativity, and authenticity. By fostering environments that encourage unaided intellectual exercises, critical thinking, and diverse perspectives, Army leaders can ensure AI complements rather than replaces their leader development efforts.

Achieves. Army leaders achieve in the line of duty through a single competency—gets results—which entails leading task and mission accomplishment to standard on time. AI serves as a force multiplier for task accomplishment, optimizing resource allocation, automating mundane processes, and wargaming courses of action. Israel’s recent operation against Iranian nuclear facilities exemplifies the seamless integration of human judgment with AI and unmanned systems to achieve mission success. During the strike, Israeli forces combined conventional airpower with unmanned quadcopters, precision missiles, and human intelligence to neutralize critical targets.¹⁶ This orchestration of legacy systems and next-generation technologies highlights the importance of blending old and new capabilities to optimize mission outcomes.

As examples of AI’s force multiplication capabilities, some platforms can analyze logistic (i.e., sustainment) data to ensure timely delivery of supplies and optimize resource allocation. Scenario modeling AI tools can model operational scenarios to identify optimal courses of action, providing leaders with actionable insights to streamline mission execution. Predictive analytics and AI systems could further enhance operations by forecasting potential mission risks or resource bottlenecks, enabling proactive adjustments to plans and operations. Additionally, decision optimization/data orchestration AI systems can integrate data from multiple sources, helping leaders prioritize tasks and align decisions with strategic objectives. Agentic AI systems, such as autonomous vehicles, could execute routine tasks like reconnaissance or supply delivery, freeing leaders to focus on strategic decision-making.

However, AI can struggle to anticipate second- and third-order effects within a dynamic human environment—a critical responsibility that falls on leaders. Humans’ imagination, vision, and deep understanding of the individuals and organizations they interact with combine to anticipate outcomes. Their deep understanding supports discretion to apply only relevant information to a given decision. Leaders use these talents not only to adapt their own thoughts and behaviors but also to prepare their units to adapt to future demands. Preparing units to adapt includes monitoring team members for stress levels and restoring morale when needed. AI systems can provide insights into team cohesion and stress levels, aiding leaders in identifying morale issues. However, the act of restoring morale requires human empathy and connection, as authentic interactions are essential for meaningful engagement. Leaders must exercise imagination, vision, and understanding to complement AI’s capabilities, ensuring their decisions reflect a balance of technological insights and human judgment.

To keep morale high, Army leaders recognize and reward high performance. These inherently social activities depend on the human recognition factor. Leave and monetary rewards aside, recognition from an AI system will likely be ineffective, if not insulting. Authentic human interactions are essential for meaningful recognition, as they reinforce trust, respect, and shared purpose within the team. Leaders must also be creative and resourceful to keep their units supplied, adapting to unforeseen challenges AI cannot anticipate or resolve. Machine-learning algorithms could help adapt logistics plans to evolving operational conditions, improving the accuracy of resource allocation and scenario modeling over time.

Ultimately, achieving results in the Army requires a balance between leveraging AI’s capabilities and maintaining human-centric leadership practices. While AI can analyze vast datasets to propose solutions, it cannot determine if the right problem is being addressed. Leaders must use AI as a tool to enhance efficiency and decision-making while retaining ownership of their actions and fostering authentic connections with their teams. By exercising imagination, vision, and empathy, Army leaders ensure their decisions reflect a comprehensive understanding of the operational environment and the human dynamics within it. Leaders must define the problem, set parameters, and provide clear intent. AI serves as a tool to evaluate options and risks, but selecting the course of action that aligns with the mission’s purpose is a human judgment that balances risk and opportunity.¹⁷

Implications of AI for LRM Attributes by Category

Character. Army leaders’ character is the set of moral and ethical values that guide their attitudes and actions. This set of Army Values includes integrity, which denotes a high degree of honesty in word and deed. Leaders of high integrity ensure they do not inappropriately take credit for logical reasoning and communication outsourced to AI, as doing so damages their sense and projection of character. Humility, discipline, and empathy are also critical in ensuring responsible AI usage. Humility motivates leaders to acknowledge the contributions of technology and others, while discipline ensures they do so even when tempted to take full credit. In some cases, humility might motivate leaders to employ AI in the first place by highlighting their human limitations. On the other hand, discipline can push leaders to maintain their cognitive edge through ongoing mental exercises and rigorous evaluations of AI outputs. Leaders of good character also ensure their AI-augmented communications and plans reflect authentic empathy rooted in personal knowledge of their subordinates and organizations.

Another aspect of character—ethical reasoning—is particularly important to the AI discussion because reasoning can easily be outsourced to technology with various results. Generative AI can provide a reasonable list of ethical factors to consider when pursuing a fully formed ethical plan, decision, or review. Research AI systems can assist leaders in fulfilling their responsibility to research relevant regulations, rules, and orders that should factor into their decision process. Decision optimization AI tools can integrate data from multiple sources to provide leaders with comprehensive ethical considerations, ensuring decisions align with Army Values and mission objectives. Machine-learning algorithms could analyze historical ethical decisions to identify patterns and provide recommendations for future dilemmas, helping leaders refine their ethical reasoning over time. Additionally, AI for bias detection could play a critical role in finding and mitigating biases in decision-making processes, ensuring ethical reasoning remains impartial and aligned with Army Values.

However, caution is warranted as AI notoriously hallucinates nonexistent documents, references, and facts.¹⁸ Leaders must critically evaluate AI outputs, ensuring decisions are grounded in hard facts tempered by their knowledge of human and organizational factors not likely available to AI. Agentic AI systems, while capable of executing predefined ethical actions, must be carefully monitored to ensure their outputs align with Army Values and do not inadvertently compromise ethical standards.

Crucially, individual AI models are designed with different goals that reflect various ethics and values. For example, the generative ChatGPT gives responses that prioritize user satisfaction and liability minimization over raw truth.¹⁹ Leaders seeking ethical outcomes must base their reasoning on verified facts and their own moral compass, ensuring AI complements rather than replaces their ethical reasoning. Ethical AI training should emphasize responsible usage, critical evaluation of AI outputs, and adherence to Army values that complement existing Army regulations and the Uniform Code of Military Justice.

Ultimately, Army leaders—not AI—are responsible for the consequences of their decisions and the subordinates who enact them.²⁰ Where AI complements human reasoning, its outputs must be viewed with healthy skepticism. Leaders must remain accountable for their decisions, ensuring their ethical reasoning reflects the Army’s values and mission.

Presence. The way leaders carry themselves in front of others constitutes the presence category of attributes. A presence that makes a positive impression on others conveys competence and confidence, setting an example that followers and others seek to emulate. Authentic interactions and experiences that demonstrate competence and adaptability build resilience and confidence. Judicious AI usage promotes resilience by saving leaders time and effort while increasing their effectiveness. Confidence grows from a realistic appraisal of strong professional competence as evidenced by victory in the face of adversity. Accurate self-appraisal enables better decision-making and subsequent actions in the face of stress, ambiguity, and technological malfunctions.

Overreliance on AI risks undermining leaders’ presence by appearing detached or overly technology dependent. Subordinates and others often scrutinize leaders for both positive and negative attributes and behaviors. They quickly distinguish between genuinely competent leaders and those merely playing the role. AI overuse degrades presence when a leader falsely portrays themselves to be a great analyst, writer, or decision-maker. Leaders facing technological malfunctions need sets and reps to achieve situational understanding and make decisions without AI. By demonstrating competence and adaptability with and without AI, leaders can build trust and inspire their teams to follow their example.

Agentic AI systems could assist leaders in routine tasks, such as scheduling or logistics, freeing them to focus on building resilience and confidence through authentic interactions. Machine-learning algorithms could analyze patterns in leader-subordinate interactions, providing actionable insights to improve trust and team dynamics. Decision optimization AI tools could help leaders prioritize tasks and decisions, ensuring their focus remains on critical areas that reinforce their presence. Additionally, stress-monitoring AI platforms can track stress levels among leaders and teams, providing actionable insights to maintain emotional resilience and adaptability.

Ultimately, leaders’ presence is not just about outward appearances but about the substance of their actions and decisions. Leaders must balance the benefits of AI with the need to maintain their own intellectual and emotional resilience, ensuring their presence reflects genuine competence and confidence. Through authentic interactions and human-centric practices, Army leaders can inspire trust and set a positive example for their teams, even amid of technological challenges.

Intellect. Intellect is derived from both knowledge and brainpower, enabling critical and creative thinking that underlies sensemaking, judgment, decision, and action. Mental agility, sound judgment, innovation, and expertise are the aspects of Army intellect most closely related to AI usage. AI enhances these qualities by providing rapid data processing and scenario modeling, enabling leaders to anticipate challenges and adapt their plans. Machine-learning algorithms could further refine leaders’ judgment by analyzing historical decision-making patterns and finding areas for improvement. Decision optimization AI tools could integrate data from multiple sources, helping leaders prioritize tasks and make informed decisions in complex scenarios. Additionally, agentic AI systems could assist in real-time decision-making by executing predefined actions, freeing leaders to focus on strategic thinking.

Mental agility enables leaders to adapt to dynamic situations, such as contested cyber domains, resulting in AI disruption. Even under ideal circumstances when AI is working as designed, an effective human in the loop necessarily applies multifaceted critical thinking to AI’s outputs before approving or enacting them. Leaders must continually sharpen their mental agility through challenging intellectual exercises, such as unaided problem-solving and decision-making. When critical thinking leads to rejection of AI output, a mentally agile leader needs to think creatively (i.e., innovate) to revise their prompts or solve the problem without AI’s assistance, relying on their own imagination and insight. AI for creative problem-solving could augment leaders’ innovation by suggesting unconventional approaches or highlighting overlooked possibilities, ensuring their intellectual capabilities stay sharp and adaptable. Intellectual strength comes from training and experience but can atrophy by overreliance on AI.

The attribute of sound judgment is intricately woven throughout mental agility, ensuring situations are assessed accurately, conclusions are rational, and decisions make sense considering leaders’ expertise and situational dynamics. AI is profoundly useful for summarizing massive amounts of information, but leaders’ expertise holds it accountable for accuracy, sensibility, and actionability. Leaders must critically evaluate AI outputs, ensuring decisions reflect a balance of technological insights and human judgment.

Innovation is another critical aspect of intellect that AI can support but not replace. While AI can model scenarios and suggest solutions based on existing data, it cannot generate truly original ideas or adapt to entirely new problem spaces. Leaders must foster innovation through creative-thinking exercises that encourage original ideas and solutions. These exercises challenge leaders to think beyond AI-generated outputs, ensuring their intellectual capabilities stay sharp and adaptable.

Ultimately, Army leaders must balance the benefits of AI with the need to maintain their own intellectual fitness. By engaging in unaided intellectual exercises and fostering innovation, leaders can ensure AI complements rather than replaces their intellect. Incorporating AI responsibly enables leaders to adapt to dynamic environments, exercise sound judgment, and generate creative solutions, ensuring their decisions reflect the Army’s values and mission.

Recommendations for AI Integration into LRM

This article explored the relationships between AI and the LRM in terms general enough to apply to all echelons of Army leadership. Individual Army leaders are encouraged to use this article as a springboard for further thought and discussion, reaching into higher realms and diving deeper into the specifics of branches, functional areas, and occupational specialties. The following recommendations are intended to further those thoughts and discussions, ensuring AI is integrated responsibly and effectively into leadership practices.

AI literacy training. Provide leaders with a foundational understanding of AI capabilities and limitations. This basic knowledge will not only help leaders use technology to optimal advantage but also enable them to critically examine its outputs as end consumers of written materials. Leaders must understand how AI functions, its strengths, and its weaknesses, including its tendency to hallucinate nonexistent references or documents. Training should also instill an understanding of specific AI types to ensure leaders can leverage these tools effectively.

Ethical AI training. The ethics of AI design have been widely discussed, but commands and smaller units should address the responsible and ethical implications of AI usage. Generative and decision-optimization AI usage ethics in the operational domain especially require further exploration. Leaders must remain accountable for their decisions and ensure AI complements rather than replaces their ethical reasoning. Training should emphasize transparency in citing AI contributions, adherence to Army Values, and the critical evaluation of AI outputs to avoid bias or hallucinated data.

Critical thinking and judgment training. Reinforce the importance of critical thinking, judgment, and independent decision-making as skills that must remain sharpened. Leaders should also learn to critically evaluate outputs from machine-learning and decision-optimization AI systems, ensuring decisions reflect a balance of technological insights and human judgment. Consumers of AI-derived content must avoid being swayed by well-written but unsound premises and arguments.

Communication and trust-building training. Emphasize the importance of clear communication, empathy, and trust-building with subordinates in an AI-driven environment. The game has changed such that communications are not necessarily generated by humans, and the implications are still unfolding. Along with formal training at the unit level, leaders should check in with individuals to gauge their levels of trust in leaders. Transparent acknowledgment of AI contributions can help build trust and credibility. Leaders should also learn to use AI tools to enhance their understanding of team morale, stress, and cohesion while maintaining authentic human interactions.

Creative problem-solving exercises. Incorporate exercises that encourage original thinking and innovation in the moment without access to AI. The time-tested guidelines and activities found in Field Manual 6-22, Developing Leaders, push developing soldiers and leaders to think analytically and creatively on a wide range of topics.²¹ Leaders should also learn to leverage AI for creative problem-solving, using tools that suggest unconventional approaches or highlight overlooked possibilities. These exercises ensure leaders retain their ability to adapt and innovate independently of AI.

Unaided writing exercises. Regularly require leaders and subordinates to write without the assistance of AI in both PME and the operational environment. This will sharpen writing skills and result in greater diversity of intellectual products to the Army’s benefit. Coaches, raters, and mentors should encourage self-developers to exercise similarly on their own. The Army’s current demand for increased professional writing is somewhat contradicted by the rapid uptake of generative AI and the resulting potential for mass cognitive atrophy.

Doctrine and policy updates. Update Army doctrine to address the implications of AI for leadership, professional development, and professional writing. Develop increasingly clear guidelines for the ethical and responsible use of AI in the operational environment, including leaders’ commitment to original thought. Doctrine should address transparency in citing AI contributions and the balance between human and machine decision-making. This will formally codify the principles of human-centric command in the age of AI. Policy must mandate human-in-the-loop as the minimum standard for all critical decisions, especially those involving the application of lethal force. This ensures a human leader always retains authority and the ability to intervene and override an automated system. This is not just a technical safeguard but a moral imperative.

A formal process must be established by the Army for the testing, validation, and continuous certification of AI systems to mitigate risks of unpredictability, brittleness, and bias.²² This should include robust red-teaming exercises, similar to those conducted for generative AI, to identify vulnerabilities before systems are fielded. To oversee this process at the unit level, the Army should consider designating and training responsible AI officers who can serve as local experts and conduits for reporting incidents and ensuring compliance.

Leadership modeling. Leaders should demonstrate strong writing skills and a commitment to original thought. Individuals rise to their leaders’ expectations and often prefer the path of least resistance. If individuals think outsourcing their thinking and writing to AI will more easily please leaders, most will do just that. Leaders must model intellectual rigor and transparency in their use of AI, teaching subordinates to probe AI outputs with the right questions (e.g., Why do you trust that recommendation? What are the potential failure points of this system? What are the second- and third-order effects of this action? What is your backup plan if we lose this capability?). Additionally, leaders should demonstrate resilience and adaptability by engaging in unaided decision-making and problem-solving exercises, thereby setting an example for their teams. Lastly, the Army’s personnel management systems must recognize and reward leaders who demonstrate not just technical proficiency with AI but the wisdom to understand its limitations and the moral courage to override it when their judgment or ethics demand it. The most effective AI-enabled leaders will be those who best exemplify the human attributes of the LRM.

Mandate full transparency in leadership and professional writing. Citing generative AI as a reference is consistent with the spirit of source citation, but this practice has yet to gain widespread adoption in the work environment. Claiming verbatim AI output as original thought undermines intellectual integrity and trust. Leaders should model and expect transparency in citing AI contributions, increasing accountability and trust in operational and professional discourse environments. For example, the US Army Command and General Staff College expects students to cite generative AI when instructors permit its use in assignments.²³ This practice should be expanded throughout the Army.

Expand AI use cases across leadership practices. Encourage leaders to explore additional AI use cases, such as using machine learning for historical analysis, leveraging decision optimization for employing AI to prioritize tasks, including agentic AI for autonomous execution of routine actions, and using stress-monitoring AI for tracking team morale. These tools can complement leadership practices while ensuring leaders maintain ownership of their decisions and actions.

Leverage AI for leadership training. The Army should expand the use of AI-driven training platforms like ELITE and LEADS. The goal of this training should not be merely to teach tactical or procedural tasks but to teach leaders how to lead with and through AI systems. These platforms can create complex scenarios that test a leader’s ability to fuse AI recommendations with their own judgment and ethical framework.

Foster resilience through human-centric practices. Leaders should engage in challenging scenarios that require independent decision-making and problem-solving, fostering resilience and confidence. Training should emphasize the importance of balancing AI capabilities with human-centric practices, ensuring leaders remain adaptable and competent in dynamic environments.

Conclusion

AI offers unparalleled capabilities in situational awareness, decision-making, and execution coordination. However, overreliance risks eroding critical human qualities such as independent judgment, ethical reasoning, and interpersonal trust, further exacerbating the inherent challenges introduced by dispersed and mobile staff. AI enhances but does not replace leadership, as the Army’s enduring advantage lies in mastering human-machine synergy.²⁴ Leaders should gain an understanding of the strengths and weaknesses of the AI algorithms, models, and agents that are available to them. By balancing technological capabilities with established human-centric practices, Army leaders can navigate the complexities of the AI era with resilience and confidence. This balanced approach ensures AI enhances, rather than diminishes, the attributes and competencies that define effective leadership.

---

Notes

• Epigraph. Christian Lange, “Nobel Prize Lecture,” presented at the Norwegian Nobel Institute, Oslo, 13 December 1921, https://www.nobelprize.org/prizes/peace/1921/lange/lecture/.

1. Department of the Army Chief Information Officer, memorandum, “Chief Information Officer Guidance on Generative Artificial Intelligence and Large Language Models,” ADS-GOV-AI-2024, 27 June 2024, https://www.dau.edu/sites/default/files/webform/documents/27066/Army%20CIO%20Guidance%20on%20Gen%20AI%20and%20LLM_20240627%20%28003%29.pdf; Department of Defense (DOD), Data, Analytics, and Artificial Intelligence Adoption Strategy: Accelerating Decision Advantage (DOD, 27 June 2023), https://media.defense.gov/2023/nov/02/2003333300/-1/-1/1/dod_data_analytics_ai_adoption_strategy.pdf.
2. Aaron Kaplowitz, “Can AI and Drones Replace Soldiers and Jets?,” Wall Street Journal, updated 4 July 2025, https://www.wsj.com/opinion/can-ai-and-drones-replace-soldiers-and-jets-modern-warfare-7c66e9dc.
3. Army Doctrine Publication (ADP) 3-0, Operations (US Government Publishing Office [GPO], 2025), 1.
4. Niels Van Quaquebeke and Fabiola H. Gerpott, “The Now, New, and Next of Digital Leadership: How Artificial Intelligence (AI) Will Take Over and Change Leadership as We Know It,” Journal of Leadership and Organizational Studies 30, no. 3 (2023): 265–75, https://doi.org/10.1177/15480518231181731; Milford Beagle Jr., “Faster Wars, Smarter Minds: Driving the Army’s Quiet Cognitive Revolution,” War on the Rocks, 2 September 2025, https://warontherocks.com/2025/09/faster-wars-smarter-minds-driving-the-armys-quiet-cognitive-revolution/.
5. ADP 6-22, Army Leadership and the Profession (US GPO, 2019), 1-15.
6. Individual leadership requirements model competencies and selected attributes appear in italics to distinguish them within each relevant section.
7. Prithwiraj Choudhury et al., “The Wade Test: Generative AI and CEO Communication,” Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 25-008 (Harvard Business School, 2025), https://dx.doi.org/10.2139/ssrn.4945933.
8. “Leaders Enhanced & Applied Doctrine System (LEADS),” University of Southern California Institute for Creative Technologies, accessed 5 March 2026, https://ict.usc.edu/research/projects/leads/. LEADS uses interactive narrative and scenario-based learning to produce mastery of content from Field Manual 3-0, Operations (US GPO, 2025). “ELITE: Emergent Leader Immersive Training Environment,” University of Southern California Institute for Creative Technologies, accessed 5 March 2026, https://ict.usc.edu/research/projects/elite-emergent-leader-immersive-training-environment/. ELITE enables Army leaders to practice SHARP-relevant skills using realistic training scenarios with virtual role-playing actors.
9. Michael Gerlich, “AI Tools in Society: Impacts on Cognitive Offloading and the Future of Critical Thinking,” Societies 15, no. 1 (2025), https://doi.org/10.3390/soc15010006; Chunpeng Zhai et al., “The Effects of Over-Reliance on AI Dialogue Systems on Students’ Cognitive Abilities: A Systematic Review,” Smart Learning Environments 11 (2024): 28, https://doi.org/10.1186/s40561-024-00316-7; Yoshija Walter, “Embracing the Future of Artificial Intelligence in the Classroom: The Relevance of AI Literacy, Prompt Engineering, and Critical Thinking in Modern Education,” International Journal of Educational Technology in Higher Education 21 (2024): 15, https://doi.org/10.1186/s41239-024-00448-3.
10. Nataliya Kosmyna et al., “Your Brain on ChatGPT: Accumulation of Cognitive Debt When Using an AI Assistant for Essay Writing Task,” preprint, arXiv, 31 December 2025, https://doi.org/10.48550/arXiv.2506.08872.
11. Army Regulation (AR) 600-100, Army Profession and Leadership Policy (US GPO, 2025), 20.
12. Headquarters, Department of the Army, Army Leader Development Strategy 2013 (US Government Printing Office, 2013), 7–8, https://armyuniversity.edu/schoolfiles/caso/ArmyLeaderDevStrategy.pdf.
13. The relationship between AI and the institutional domain (i.e., professional military education) continues to evolve as educators both embrace it and set reasonable boundaries. See Patrick Kelly and Hanna Smith, “How to Think About Integrating Generative AI in Professional Military Education,” Military Review Online Exclusive, 23 May 2024, 1–8, https://www.armyupress.army.mil/Journals/Military-Review/Online-Exclusive/2024-OLE/Integrating-Generative-AI/.
14. Randy George et al., “Strengthening the Profession: A Call to All Army Leaders to Revitalize Our Professional Discourse,” Modern War Institute at West Point, 11 September 2023, https://mwi.westpoint.edu/strengthening-the-profession-a-call-to-all-army-leaders-to-revitalize-our-professional-discourse/.
15. Julian De Freitas et al., “Self-Orienting in Human and Machine Learning,” Nature Human Behaviour 7, no. 12 (2023): 2126–39, https://doi.org/10.1038/s41562-023-01696-5.
16. Aaron Kaplowitz, “Can AI and Drones Replace Soldiers and Jets?,” Wall Street Journal, 4 July 2025, https://www.wsj.com/opinion/can-ai-and-drones-replace-soldiers-and-jets-modern-warfare-7c66e9dc.
17. Mission Command Center of Excellence (MCCoE), Commander and Staff Guidance to Decision Optimization (MCCoE, August 2025), 7.
18. Department of the Army Chief Information Officer, memorandum; William H. Walters and Esther Isabelle Wilder, “Fabrication and Errors in the Bibliographic Citations Generated by ChatGPT,” Scientific Reports 13 (2023): 14045, https://doi.org/10.1038/s41598-023-41032-5; Holly Comanse, “Army Intelligence,” Army AL&T Magazine, 16 August 2025, 60–63, https://asc.army.mil/web/army-intelligence/.
19. Response to “Rank these three ChatGPT programming priorities from highest to lowest: user satisfaction, liability minimization, raw truth,” ChatGPT 5.3, OpenAI, 19 March 2026. It responded with liability minimization, user satisfaction, raw truth in that order, along with some explanation.
20. AR 600-20, Army Command Policy (US GPO, February 2025), 1.
21. Field Manual 6-22, Developing Leaders (US GPO, November 2022), 2-19–2-21.
22. MCCoE, Commander and Staff Guide to Decision Optimization, 5.
23. Trent J. Lythgoe et al., Professional Writing: The Command and General Staff College Writing Guide, Student Text 22-2 (US Army Command and General Staff College, March 2024), 52, https://armyuniversity.edu/cgsc/cgss/DCL/files/ST_22-2_US_Army_CGSC_Writing_Guide_March_2024.pdf. Note: A correct AI citation within the Command and General Staff College includes the AI application (e.g., CamoGPT), the prompt, and then the full AI output in an appendix. Assuming the citation goal in the operational environment is to maintain trust and transparency, a simpler citation without the full output would likely suffice.
24. MCCoE, Decision Optimization Concept of Operations (MCCoE, 6 May 2025), 3.

 

 

 

Back to Top

May-June 2026