Artificial Intelligence (AI) has become an integral part of the educational landscape, prompting educators to seek ways for students to utilize these tools effectively while avoiding pitfalls like dependency or superficial engagement. One promising framework for discussing AI’s role in education is to conceptualize it as a team composed of three distinct roles: the Tasker, the Draftsmith, and the Facilitator. This model encourages students to take responsibility for how they engage with AI, ensuring its use enhances their learning rather than detracting from it. Drawing from recent scholarly work, such as the insights from Dell’Acqua et al. (2025), this approach provides a structured lens through which to analyze and guide students’ interactions with AI.
Understanding the AI Teammates
The Tasker
The Tasker is focused on streamlining repetitive or procedural tasks such as organizing calendars, formatting citations, or cleaning datasets. These tasks can often be tedious yet essential, and by leveraging AI, students can redirect their time towards deeper cognitive engagement. Tools such as Robotic Process Automation (RPA) systems, embedded AI features like Copilot in Microsoft Word, or Claude in Excel and Google Sheets serve this purpose. Farri & Rosani (2025) emphasize the importance of using AI to alleviate the burden of procedural chores, thereby enabling students to engage more meaningfully with complex thinking and learning processes.
However, students must recognize that AI-generated outputs are not infallible. It is crucial for them to establish acceptable levels of risk for each task and to validate AI-generated results accordingly. The validation requirements will vary based on factors such as the importance of accuracy and the student’s familiarity with the AI tool in question. Setting up a Tasker effectively requires investing time to ensure its reliability before relying on it for independent operation.
The Draftsmith
The Draftsmith plays a different role by assisting in the creation and refinement of content. For instance, it can identify passive voice in student writing, generate outlines for presentations, and develop study aids like multiple-choice or essay questions. I have found that my engineering students effectively utilize a tailored prompt library to convert their clients’ needs into actionable project requirements. Bussgang (2025) highlights how simple interactions with the Draftsmith can significantly boost productivity without sacrificing educational value.
Despite the benefits, it is essential that the final product reflects the student’s unique voice. I often remind my students that developing their writing style is a foundational skill that can take years to cultivate. This is especially relevant in professional settings where most communication occurs via email. Many students, however, do not realize that improper use of the Draftsmith can lead to increased cognitive load, as they must provide extensive context for meaningful output (Purohit, 2025). Relying too heavily on AI for initial drafts can also hinder learning, as writing is a critical process for deepening understanding and committing knowledge to long-term memory.
The Facilitator
In contrast to the Draftsmith, the Facilitator functions as a cognitive partner. By engaging AI in this role, students can ask it to challenge their arguments, propose counterpoints, or explore different perspectives. This interaction is beneficial when preparing for presentations or testing design ideas. Utilizing AI in this capacity encourages reflective thinking, which is vital for deep learning (Solis, 2024; Harbridge, 2025).
Maximizing the value of AI as a Facilitator requires students to invest significant time and focus. Meaningful dialogue with AI is only achieved when students ask thoughtful questions and provide adequate context. They should also be prepared to rephrase prompts or even switch models if the AI is not offering useful feedback. Teaching students the importance of attentive engagement will significantly enhance their learning outcomes.
Implications for Teaching Methods
Introducing these roles to students can lead to improved decision-making regarding AI use in their academic assignments. Here are several effective strategies I have implemented:
- Design assignments that engage different roles. For instance, instruct students to start with AI as a Tasker to gather and organize research, transition to the Draftsmith for refining syntax, and finally employ the Facilitator to critically evaluate their arguments before submission.
- Clarify AI’s strengths and limitations. It is imperative to communicate that while AI can assist with structure and ideation, it cannot substitute for critical thinking, revision, or the development of a unique writing voice.
- Promote transparency in AI use. Emphasizing a culture of Total AI Transparency encourages students to disclose their use of AI in assignments, thereby fostering trust and accountability.
Concluding Thoughts
In navigating the complex relationship between students and AI, it is essential to steer them away from either complete avoidance or excessive dependence. By delineating the roles of Tasker, Draftsmith, and Facilitator, educators can clarify expectations and foster a more deliberate approach to AI use. This empowers students to become proficient in leveraging AI as a constructive partner in their educational journey.
Illysa Izenberg serves as an Associate Teaching Professor at the Center for Leadership Education within the Whiting School of Engineering at The Johns Hopkins University. With a robust teaching background in management and business ethics, she has been recognized for her excellence in teaching through multiple awards.
References
Bussgang, J. (2025, May 20). 3 small steps to 10x your productivity with AI this week. The Experimentation Machine. https://experimentationmachine.com/p/10x-this-week
Duffy, A. (2025, April 11). Your CEO just said ‘Use AI or else.’ Here’s what to do next. Every. https://every.to/p/your-ceo-just-said-use-ai-or-else-here-s-what-to-do-next
Farri, E., & Rosani, G. (2025). HBR guide to generative AI for managers. Harvard Business Review Press.
Gross, A. (2025). AI Crash Course [Online course]. SectionAI. https://www.sectionschool.com/courses/ai-crash-course-workshop
Harbridge, R. (2025). AI for Team Leaders [Online course]. SectionAI.
Harvard Business Publishing. (2025). Help your team harness generative AI (Lesson 1). In Leading with generative AI [Online course]. Harvard ManageMentor.
Purohit, R. (Host). (2025, June 18). The man inside the minds of the people building AGI [Audio podcast episode]. In AI & I. Every.
Solis, B. (2024, November). Train your brain to work creatively with Gen AI. Harvard Business School Publishing.
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