We are living through a pivotal moment at the intersection of technology and work. Artificial intelligence is no longer a distant concept or a tool reserved for specialists, it has arrived in our inboxes, our administrative workflows, and our clinical environments with remarkable speed. For academic leaders and health professions educators, the central question is no longer whether to engage with AI, but how to engage with it wisely. The key question at this crossroads is whether we choose to merely use AI, or deploy it. This will have profound implications for how we lead, teach, and work.

Transactional vs. Transformative

AI is a technology driven by prompts, drawing on a language model leveraging vast amounts of information to understand and reply to questions or commands. It is enormously capable, and entirely reactive. It waits for you to tell it what to do.

Agentic AI is something different. An AI agent doesn’t simply respond to a single question; it reasons about a goal, develops a plan to achieve it, and takes sequential actions on your behalf until the task is complete. Think of it this way: standard AI answers a question; agentic AI manages a project.

Consider email. You could prompt a standard AI tool to draft a reply to a message, and it will. An agentic AI, by contrast, can review your entire inbox, identify high-priority threads, summarize extended conversations, draft replies in your preferred tone, and flag items requiring follow-up, all without being asked to do each step individually. Or consider research: rather than answering a single query, an agentic assistant can gather information from multiple sources, synthesize findings, identify key trends, and deliver a formatted research brief ready for decision-making.

Agentic AI provides a leap forward by not just answering a question, but by assimilating a wider set of inputs to assess a goal, create a plan, take action, and deliver a solution. For leaders managing complex, multi-layered responsibilities, that difference is transformational.

Building an Agent That Knows You

The real power of agentic AI emerges when the agent is tailored to your specific role, work style, and organizational context. This is not a technical undertaking reserved for IT professionals. It is a leadership skill that any administrator or educator can develop. But it requires deliberate thought before you begin building.

Start by examining your job profile honestly. What are your core deliverables? Which tasks are routine and repeatable—scheduling, document formatting, status updates—and which require genuine judgment and creative thought? The former are prime candidates for automation; the latter benefit from AI assistance but should remain under close human oversight.

Next, teach the agent your context. What tone do you use when writing to faculty versus students versus external partners? What are your institutional priorities? What constraints—regulatory, cultural, logistical—shape how work gets done in your environment? The more precisely you define these parameters, the more useful and accurate the agent becomes over time.

Finally, and critically, decide how much autonomy you are comfortable granting. Agentic AI works best when the problem is complex enough to warrant multi-step reasoning but bounded enough to guide the agent effectively. Build in regular checkpoints. Review outputs. Keep the human in the loop; not because the technology is untrustworthy, but because mistakes will arise, but more importantly, because professional accountability always rests with people, not platforms.

This iterative approach draws on principles that will be familiar to those in quality improvement: accelerate the flow of work, create continuous feedback loops, and convert individual learning into shared organizational knowledge. The goal is not to hand your work to a machine. It is to work more effectively, with more focus on the decisions that genuinely require your expertise.

AI in Health Professions Education: Opportunity and Obligation

For those of us in health professions education, the stakes are unusually high, and unusually compelling. Healthcare is one of the most rapidly expanding markets for AI application. Billing automation, document processing, and real-time diagnostic support are already in active deployment. In some radiology environments, AI-generated preliminary analyses are delivered to physicians before the patient has returned from the imaging suite. The integration is that fast, and that consequential.

This means our students and trainees are entering a clinical world that is already AI-enhanced. Educators and administrators preparing them carry a responsibility not just to teach about AI in the abstract, but to model informed, confident, and ethical engagement with these tools in their own practice. It’s the difference between awareness of a tool and active engagement with it.

At the same time, constraints are real. HIPAA compliance and data security create legitimate boundaries around AI deployment in healthcare settings, and not every tool appropriate for general administrative use is suitable for clinical contexts. Leaders must be equipped to ask the right questions: Has our organization established an AI use policy? What data are we feeding into these systems? Who is accountable when an AI-assisted output is wrong?

Riding the Wave

There is a natural tendency, when confronted with rapidly advancing technology, to frame the conversation around fear: around what AI will replace. That framing, while understandable, is not particularly useful for leaders. A more productive question is: What tasks would you prefer not to spend time on? What work, if automated thoughtfully, would free you to do the things that genuinely require your judgment, your relationships, and your humanity?

Academic leaders and health professions educators are currently facing this technological inflection point. The question is not whether the wave is coming; it is here. The question is whether we will engage with it deliberately and skillfully, or find ourselves overwhelmed by its pace.

Building a personal AI agent—one that knows your work, reflects your values, and operates within boundaries you have defined—is one of the most concrete steps a leader can take right now. It is not a surrender of professional judgment. It is an expression of it.

Author:

George Jones

Jones is Chair of the Board of Directors and Chair of the Technology Committee for the Dekalb Agricultural Technology & Environment Charter School in Stone Mountain, Georgia. Professionally, he is a Technical Architect Manager with 22 years of Enterprise Software Development and Delivery experience in driving the vision for digital platforms in complex IT environments.