How one university used AI to build trust in financial scenario planning

Higher education finance leaders face a dual challenge: building realistic financial plans and helping the rest of the institution understand what those plans mean for future decisions.

The New Jersey Institute of Technology (NJIT) recently addressed this challenge as part of its multi-year financial planning work. NJIT’s finance team needed a clearer way to help leaders understand a complex deficit reduction strategy, test possible budget actions, and build confidence in the path forward.

To support that work, Lisa Easton, NJIT’s Assistant Vice President for Strategic Budget Planning, built an AI-enabled financial simulator in Gemini AI Studio. The simulator allowed leaders to review different budget scenarios, turn planning levers on or off, and see how those choices affected NJIT’s multi-year financial outlook. It was a clearer, more interactive way to support the financial conversations leaders already needed to have.

For chief business officers (CBOs) and cabinet leaders, NJIT’s example shows one practical application of AI in finance as leaders begin exploring where the technology can support planning and decision-making. The example also underscores that financial planning is not only about producing a more sophisticated forecast; it is about helping leaders across campus understand current financial risks, align around shared realities, and evaluate how different choices could affect both their units and the institution as a whole.

Rethinking financial planning on your campus? Save your seat for EAB’s upcoming webinars on adaptive planning models and how to align stakeholders on financial decision-making.

The challenge: Moving leaders from spreadsheets to shared understanding

NJIT’s finance team worked through a multi-year financial sustainability plan that required cabinet leaders and senior budget owners across campus to understand both the institution’s baseline financial picture and the effect of potential revenue and expense actions.

NJIT needed a way to help these leaders answer practical questions:

• What does the university’s financial outlook look like currently, before any new revenue or expense actions are applied?
• What changes if the university takes one budget action but not another?
• How would each potential action affect the university’s multi-year financial outlook?

The goal was not to let users freely change the underlying financial model or its inputs. The aim was to give stakeholders a clearer way to explore the impact of defined budget scenarios, while keeping the core assumptions defined by finance and cabinet leadership.

The solution: An AI-enabled scenario planning simulator

NJIT built the simulator in Gemini AI Studio using a stable base model of operating revenues and expenses. That stable baseline was important because it gave senior leaders a common view of NJIT’s financial outlook and helped keep budget planning conversations focused on which actions to consider, rather than debating the underlying numbers.

From there, the simulator allowed users to review and select from a set of budget scenarios. Leaders could turn scenarios on or off and see the impact of those choices in the model. Some scenarios used fixed values, while others included editable fields that allowed users to test a limited range of finance-approved inputs.

The simulator organized the planning process across five tabs:

Together, these views demonstrated how selected adjustments affected institutional finances across multiple years. Just as important, the simulation tool included guardrails. Leaders could explore defined budget scenarios, but only within limits set by finance, which helped prevent unrealistic or incompatible results.

View of simulator’s main dashboard

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NJIT’s simulator gave leaders a shared view of the financial baseline and the multi-year impact of selected planning scenarios. Specific financial details have been redacted.

View of scenario configuration tab

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The scenario configuration view allowed leaders to select defined revenue and expense levers while keeping core assumptions controlled by finance. Specific tactics and financial details have been redacted.

Why it worked: Clear scenarios, visible impact, and improved trust

NJIT’s simulator did more than make the financial model interactive. It helped senior leaders outside the finance office understand which revenue and expense actions were being considered, how those actions could change NJIT’s multi-year financial outlook, and which options might need to be prioritized or held in reserve.

Three features helped make the simulator useful for budget planning conversations:

These features matter because they help shift budget planning meetings from explanation to discussion, giving senior leaders more time to focus on which revenue enhancements or cost-containment actions are most realistic.

Improved trust was one of the most meaningful outcomes of NJIT’s work. The simulator helped make the model more transparent by showing which revenue enhancement or cost-containment actions were driving changes in the university’s financial outlook.

What other finance leaders can learn from NJIT’s approach

NJIT’s example offers several practical lessons for CBOs and cabinet leaders exploring AI-enabled financial planning.

1. Start with the decision, not the technology

NJIT did not begin with a broad goal to “use AI.” The financial simulator was built to solve a specific planning problem: helping stakeholders understand budget scenarios and their impact on a multi-year financial plan. AI is most useful when it’s designed to solve a specific problem.

2. Build from a stable baseline

Before leaders can compare budget options, they need agreement on the institution’s current financial outlook and the assumptions behind it.

3. Use financial scenarios to prepare for action

Financial scenario planning should help leaders examine tradeoffs and build readiness for change, while also clarifying how the institution might respond if financial conditions shift.

NJIT’s broader deficit reduction planning included identifying financial risks to monitor, trigger points that would require further review, and additional revenue enhancement or cost-containment actions that could be held in reserve. By connecting each scenario to a possible leadership response, NJIT’s planning process helped leaders move from understanding the financial outlook to preparing for specific next steps.

To support that work, NJIT organized potential responses into a tiered action framework that distinguished between actions to take now, expectations for units to manage toward, and contingency options to hold in reserve if initial efforts fell short.

AI can make financial planning more actionable

AI can make financial planning easier to understand and use, but it does not replace finance leaders’ judgment or resolve the hard tradeoffs behind a financial sustainability plan. Those decisions still require human review, clear governance, and accountability.

NJIT’s example shows how, with the right guardrails, AI can strengthen the financial planning process in a practical and focused way. For CBOs, that may be one of the most promising near-term uses of AI in financial planning: not replacing the underlying multi-year financial model, but making the model’s assumptions, scenarios, and projected impacts easier to understand, discuss, and act on.

Molly Bell

Associate Director

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Paul Gunther

Principal Strategic Leader, Office of the President

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