Researchers warned that rapidly advancing AI agents could pose an “existential threat” to how grants are awarded, particularly where assessment models depend on human-centered verification, narrative-based review, and risk-screening processes. The concern is that assessment systems are not keeping pace with new agent capabilities that can generate documentation, automate workflows, and complicate evaluators’ ability to distinguish credible claims from mechanized outputs. The reporting frames the issue as an evaluation and compliance challenge, not just a technology adoption story. If reviewers cannot reliably interpret the provenance and substance of applicant materials, the grant ecosystem could face higher fraud risk, reduced reviewer confidence, and greater administrative burdens. The core institutional stake is integrity across the grant lifecycle—application, review, and monitoring. As agentic tools expand, higher education research offices and sponsored programs teams will likely need updated verification protocols and stronger controls around data sources, claims, and deliverables. The immediate policy implication is that funders and institutions may need faster redesign of assessment systems—potentially incorporating new technical signals and process safeguards—to preserve merit-based funding decisions.