AI in the Grant Lifecycle: Review of Current Tools and Use Cases

This report examines how artificial intelligence is transforming the grant development lifecycle, a process that has long been criticized for being time-intensive, inequitable, and administratively burdensome. We highlight how emerging tools—from large language models and retrieval-augmented systems to reviewer simulators and compliance checkers—are reshaping proposal writing, feedback, and submission. The goal is to assess both opportunities and risks, and to outline how institutions and investigators can responsibly integrate these tools to achieve this goal.Current state. AI tools already provide support across all stages of grant preparation. They assist with brainstorming and literature discovery, drafting aims and research strategy, embedding citations, simulating peer review, and managing formatting and compliance. These applications help reduce repetitive work, improve clarity, and expand access to structured feedback, particularly for early-career and underresourced researchers.Future outlook. The next wave of AI integration will shift from stand-alone applications to adaptive, collaborative systems. Agentic co-pilots will manage multi-step tasks within unified workflows; federated learning infrastructures will allow institutions to fine-tune models on their own data securely; and personalized AI companions will adapt to individual writing styles, funding histories, and strategic goals. Together, these advances point toward a new grant ecosystem defined not only by efficiency but also by greater equity, creativity, and institutional alignment.