September 22, 2026 at 12:00 PM ET
Impact of Integrating AI into Award Management
Pre-award and post-award management as a Research Administrator.
Research administration is document-heavy, deadline-driven, and highly regulated. Every proposal and every award depends on reading sponsor and institutional requirements correctly, usually under time pressure and across several disconnected systems. Most offices still handle that work transactionally: searching for opportunities by hand, reviewing documents one at a time, reacting to budget and compliance problems as they surface, and tracking deadlines through email and spreadsheets.
This session makes the case for a different model. Patience Ezeike lays out a practical, institutional framework for using AI across the full grant lifecycle, from funding discovery and proposal preparation through award setup, post-award monitoring, and closeout. The goal is not automation for its own sake. It is to move research administrators away from manual compliance checks and toward proactive, predictive support, while keeping people accountable for every final decision. AI identifies, summarizes, drafts, compares, and alerts; authorized professionals still approve the compliance, financial, and institutional calls. The throughline of the whole talk is simple: AI should augment professional judgment, not replace it.
What you'll learn
- How AI maps to the full research administration lifecycle, from funding search and proposal intake through award review, post-award monitoring, and closeout, so you can see where it fits your own workflow.
- Pre-award use cases you can apply now: matching research interests to funding opportunities, running a proposal readiness check, drafting budgets and budget justifications from the solicitation, and reading FOAs and required documents, including the prompts that make each one work.
- Post-award use cases: summarizing Notice of Award terms, forecasting burn rate and remaining balances, flagging compliance and reporting gaps, monitoring subawards, and producing a closeout exception list.
- A secure, auditable architecture and a human-in-the-loop governance model, covering approved-tools-only rules, role-based access, source-grounded responses, audit logs, and alignment with OMB Uniform Guidance, NSF PAPPG, and NIH GPS.
- A phased implementation roadmap that starts with low-risk, high-ROI tasks before moving to decision support and, eventually, intelligent automation.
Meet the speaker
Patience Ezeike is a Senior Research Proposal and Contract Analyst at The University of Alabama, where she works across both pre-award and post-award research administration, from proposal development, budgets, and contract analysis through award setup and compliance.
She brings a practitioner's view of where AI genuinely helps in day-to-day grants work and where a human has to stay in the loop. In this session she shares an institutional framework, real prompt examples, and an implementation roadmap that research offices can adapt to their own tools and policies.