James Francis
Chief AI Officer · AwardSpring
Executive Forum · Recorded Tuesday, September 29, 2026
AI Under Human Review
An AwardSpring Executive Forum. AI that drafts, briefs, and prepares, and people who decide what actually gets sent.
Recorded September 29, 2026 · 45 minutes, heavy on Q&A
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James Francis
Chief AI Officer, AwardSpring
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Alex Stepien
CEO, AwardSpring
The recording
Watch the full session
The conversation and the Q&A, as it happened.
About this session
AI vendors are starting to promise agents that reach out to your donors and students for you. We think that's exactly backwards. In this Executive Forum, AwardSpring's leadership makes the case for the opposite design: AI that drafts, briefs, and prepares, and people who decide what actually gets sent. It was an informal fireside conversation with clients, colleagues and partners in higher education about where AI helps in scholarship and donor work today, how SpringIQ keeps a human quality check on every output, and the questions this industry moment raises.
What we covered
From "should we?" to "how do we do this?"
A year ago most campuses treated AI as a threat to the learning model. The academic side and the administrative side are now converging on one institutional view, and the leaders getting furthest are rethinking how the institution runs, not just rolling out licenses and stopping there.
Data is the bottleneck
Without access to real data across the student information system, scholarship management and finance tools, an institution captures only a fraction of what AI can do. The panel's advice: make data unification a top-three cabinet priority.
Meet Jordan
Think of AI as a new hire who graduated top of the class with no context, no system access and no knowledge of your environment. Jordan gives generic answers until you hand over specific data, context and tools. Implementation is the work of giving Jordan what the job needs.
Decompose the role
Break a job into its skills and sort each one: uniquely human (building relationships, navigating ambiguous situations, donor and student conversations) or automatable (CRM updates, meeting notes, data entry). Automate the second list. Train and reward the first. You cannot electrify a steam-powered line and call it progress; the workflow itself has to change.
AI under human review
AI handles the first 80 percent of a task: drafts, triage, reporting. People keep the craft and the final call. A two- or three-person foundation office cannot read thousands of recipient thank-you notes by hand, so AwardSpring's donor experience product is the first line of review at scale, and the office decides how much autonomy the agent gets. Trust is built the way software teams build it: deterministic tests, agent-to-agent review, continuous validation, and spot checks with a clear view of the blast radius when something is wrong.
No single right answer
Different institutions, comfort levels and workflows need different calibrations. AwardSpring's goal is to let every customer set the dial and keep a finger on the scale.
Related
From AI Summer School
In July, 40 higher education leaders across financial aid, enrollment and advancement joined five AI Summer School sessions. The biggest unlock was connecting AwardSpring's MCP to ChatGPT, Claude or Copilot and running custom reports in seconds, free of the limits of pre-built software reporting.
Who this is for
Leaders at colleges, universities, and scholarship foundations working out what AI should and should not do in scholarship and donor work. If your team is somewhere between curious and skeptical, this session was built for you, and the Q&A is the point.
Panelists
Alex Stepien
CEO · AwardSpring
Keep AI under human review.
See how SpringIQ keeps a person's sign-off on every output that moves.
