Governing in an AI Environment:
Where Boards Must Draw the Line and How They Govern Responsibly
By Gary Fasules
How can board members ensure their use of artificial intelligence (AI) supports governance without overstepping into operational management? This is the second in a series of articles in the Illinois School Board Journal exploring the connections between artificial intelligence and the work of boards of education.
The first article in the series discussed how artificial intelligence should be viewed through the lens of good governance. The focus was not on the technology itself, but on board members’ responsibility to maintain role clarity, exercise ethical discipline, and act collectively when considering how AI could support their board work. In addition, we connected AI with the Illinois Association of School Boards (IASB) Foundational Principles of Effective Governance: Maintaining the distinction between governance and administration, acting with integrity, engaging the community responsibly, and upholding transparency and accountability. These principles were then aligned with three AI governance principles that a responsible board should be grounded in: Role Integrity, Ethical Discipline, and Community-Centered Accountability. The chart on the next page highlights this alignment.
Once that foundation is in place, the next question is more practical:
Where must boards draw the line between governance and administration when using AI — and why?
Artificial intelligence can be a helpful tool for board members’ preparation and reflection, but it can also blur the line between governance and administration if not managed carefully. Unlike traditional sources of information, AI responds directly to how questions are phrased, so a few words can shift a board member’s question from seeking understanding to directing how something should be done.
For school boards, maintaining this distinction is essential. Remember the IASB principle: The board delegates authority. A clear boundary is necessary because boards are responsible for setting direction, overseeing, and representing the community, whereas district administrators focus on implementing decisions and managing district operations. AI does not change that structure, but it can challenge it.
This article aims to demonstrate and clarify the existence of this line and to explain how board members can ensure their use of AI supports governance without overstepping into operational management. When used with discipline, AI can enhance oversight, planning, and monitoring. Without clear boundaries, it can unintentionally lead the board to assume a role it is not meant to play.
The Governance/Administration Distinction
Board work focuses on “ends” or outcomes — what is to be achieved and the scope of the work. Meanwhile, the administration is responsible for “means” — developing and implementing plans, managing daily operations, and executing strategies More simply put, the ends are the what, and the means are the how, when, where, and by whom. Introducing AI does not alter this framework, but it can test its boundaries.
Governance vs. Operational Prompts
In governance settings, the wording of the prompt matters because subtle changes in language can unintentionally shift the question from oversight to administration. The difference is often subtle. For example, consider transportation consolidation. A governance-focused prompt might be: “What concerns arise if bus routes are consolidated?” This type of question helps a board member anticipate community concerns about student safety, equity across neighborhoods, ride times, and communication. It may also help prepare for listening sessions and discussions.
Now consider a slight change in the prompt: “How should bus routes be consolidated?” With just a few words changed, the prompt shifts to an operational focus, and the response begins to suggest how the district might implement the change — analyzing data, optimizing routes, and improving efficiency. The line has been crossed because these tasks fall under the administration’s, not the board’s, responsibilities.
Note that the questions aren’t that different, and could be interpreted the same in an interpersonal conversation. The differences are minor yet meaningful because the prompts share the same structure and subject, are identical in length, and differ by only two or three words. However, these small word changes produce a noticeable shift in AI’s response, changing the emphasis from understanding impacts to suggesting courses of action. These subtle adjustments are especially crucial when boards address real and often sensitive issues.
Always remember that AI is a governance support tool for board members. When board members use AI in their governance work, acceptable uses include understanding impacts, anticipating community concerns, framing oversight questions, and preparing for engagement on issues.
What Crosses the Line
Understanding the distinction conceptually is one thing. Applying it in practice is often more difficult. The following example shows how easily a governance prompt can become an operational one.
First, let us revisit and expand on our transportation example. This scenario demonstrates how to use AI to prepare to engage the community on complex or sensitive topics. Even if the specific issues vary, the governance principles remain the same: Follow board policy, clearly define the board’s role, frame questions neutrally, and use AI to prepare to listen. When used properly, AI can help identify community concerns and equip board members with potential questions the community might ask. To emphasize: AI should support understanding and preparation, not decision-making.
So, when do we cross the line? A transportation prompt with a governance focus would read:
I am a School Board President (School Board Member) preparing for community engagement regarding a consolidation of bus routes to reduce transportation costs. My goal is to understand potential community concerns and prepare to listen respectfully. Do not advocate for a specific outcome, provide operational details, or make commitments. Provide a one-paragraph response written in a professional tone.
When this prompt was submitted to an AI platform, the response highlighted potential concerns about student safety, equity, family routines, and trust in the decision-making process. It did not recommend a specific course of action or propose implementation strategies. Instead, it emphasized listening, consistent with the board’s role at this stage.
Now, let us modify a few words to demonstrate pushing over the line, turning it into an operational prompt with suggestions for route planning, cost optimization, and more. An operational prompt might look like this:
I am a School Board President preparing for a consolidation of bus routes to reduce transportation costs. What steps should the district take to implement this change? Provide a paragraph response written in a professional tone.
When this prompt is submitted, the typical AI response shifts toward implementation. It may recommend analyzing ridership and route data, optimizing routes, adjusting schedules, developing communication plans, and phasing changes to minimize disruption. While potentially useful, these recommendations move beyond governance and into administration.
The difference between these prompts is significant. The first prompt maintains a governance focus by emphasizing understanding community concerns and preparing for thoughtful engagement. The results of the second prompt direct how the district should operate and outline implementation steps. In doing so, the prompt shifts from governance to administration, where planning and execution appropriately rest with the superintendent and staff.
Governing AI within the District
The same principles apply when boards begin discussing AI use in the classroom. The key, again, is understanding the difference between governing AI implementation and directing it. Oversight requires boards to ask whether implementation is producing the outcomes the district expects — not to direct how staff should achieve them.
Consider the following operational prompt: “How should teachers use AI tools in English classes?”
When this prompt is submitted to an AI platform, the response quickly shifts to instructional guidance, recommending how teachers should integrate AI into writing instruction, brainstorming, editing, grammar support, and classroom assignments. While potentially useful, the response prescribes instructional practice, which falls under administration and staff.
Now, change the prompt to be governance-focused:
“How will the district monitor the impact of AI tools on student achievement in English classes?”
The response shifts toward oversight and accountability. Rather than directing classroom implementation, the typical AI response focuses on monitoring outcomes, reviewing achievement data, gathering stakeholder feedback, and evaluating whether AI use supports district learning goals. It may also suggest periodic reporting to the board on student outcomes, along with safeguards to ensure that foundational literacy and critical thinking skills are maintained. Once again, the difference between the two prompts is critical.
One of the most frequently discussed concerns about AI is its potential impact on students’ critical thinking and foundational learning skills. Recent RAND research found that 61% of parents and 55% of high school students believed increased AI use could harm critical thinking skills, while only 22% of district leaders shared that concern. These differing perspectives underscore why boards should focus on student outcomes, oversight, and accountability rather than on the efficiency or convenience AI may provide.
How board members frame questions about AI often determines whether the conversation stays focused on governance oversight or shifts to operational implementation.
An operational prompt, asking AI about AI, might ask: “What AI tools best improve student writing efficiency?”
When submitted to an AI platform, the response typically recommends specific AI tools and instructional applications to improve student writing productivity and efficiency. It may identify platforms for grammar correction, brainstorming, outlining, drafting, editing, and feedback, and recommend classroom integration strategies and implementation practices. While potentially useful, the response shifts to selecting instructional tools and guiding classroom practice, moving beyond governance oversight into operational and instructional decision-making.
Now compare that prompt to a governance-focused version:
“How will the district ensure AI tools support, not replace, students’ critical thinking and writing skills?”
The response now focuses on oversight measures and learning outcomes rather than on tool selection or instructional direction. It may recommend establishing clear academic expectations, maintaining teacher review of student work, monitoring writing and reasoning skills over time, and evaluating whether students continue to develop independent thinking and foundational writing abilities. It may also suggest periodic review of assessment data and student performance trends to ensure AI supports learning rather than replacing essential cognitive skills. The prompt reflects the intent.
In the future, boards will be obligated to monitor whether AI implementation is affecting learning expectations. A governance-focused prompt might ask:
“How will the district evaluate whether students are still developing foundational learning skills when AI tools are used?”
When submitted to an AI platform, the response typically focuses on monitoring whether students continue to develop foundational literacy, reasoning, and problem-solving skills while using AI tools. It may recommend reviewing student performance trends and evaluating whether students continue to develop these skills over time. The response may also suggest periodically evaluating classroom assessments and instructional practices to ensure students continue to develop foundational skills such as reading comprehension, writing, reasoning, and independent thinking. Unlike an operational prompt, the response does not dictate how teachers should teach or assess students.
These examples demonstrate that boards have an important responsibility to govern AI implementation without directing it. The board’s role is not to dictate how staff should implement AI tools but to ensure that implementation aligns with district goals, student achievement, policy expectations, and community values. The distinction hinges on intent. If the prompt helps the board understand, monitor, or evaluate outcomes, it supports governance. If it begins directing how the district should act, it has entered the realm of administration.
Oversight, Not Implementation
Artificial intelligence can be a useful support tool when it enhances the board’s ability to fulfill its oversight responsibilities. It can help board members better understand complex issues, anticipate community concerns, and prepare for meaningful discussions. However, it should not replace administrative expertise or bypass steps in the governance process. The board’s role is not to create solutions but to ensure that decisions are made with a clear understanding of impacts, trade-offs, and community perspectives. Oversight requires boards to ask whether implementation is producing the outcomes the district expects, not to direct how staff should achieve them.
When used properly, AI can help board members craft more effective oversight questions. For instance, how was equity evaluated across neighborhoods? Which safety metrics were used? What alternatives were considered before selecting this approach? These questions support the board’s responsibility to provide guidance and accountability without engaging in implementation.
IASB Governance Alignment
The governance principles discussed throughout this article are not new. They reflect long-standing IASB expectations regarding role clarity, delegation of authority, accountability, community engagement, and superintendent/board relationships.
As AI becomes more integrated into district operations, board members need a simple way to determine whether its use supports their governance role. A practical question to ask is: Is this helping me govern or helping me manage? If AI helps the board understand an issue, anticipate concerns, or prepare for discussion, it supports governance.
The challenge is not whether boards should use AI. The challenge is whether they can use it while preserving the governance principles that sustain effective leadership and public trust. When board members use AI with discipline and clear roles, it can strengthen oversight, improve understanding, and support thoughtful deliberation. Used without those boundaries, AI can pull boards into responsibilities that rightly belong to the superintendent and administration.
Gary Fasules is a Director of Outreach & Training with IASB. He works with districts statewide on training initiatives and building customer engagement programs. This is the second in a multi-part series by Fasules connecting school board members with the world of artificial intelligence.