Which parts of the grant writing process has AI been most helpful for?

Often in proposals when space allows, we do look to add research studies to underscore how a program can impact the constituents served.

And AI can be a great source for targeting that research and pulling studies that are specific to that program and what the organization is looking to do in terms of impact.

It helps us find the right research faster.

It can also help us summarize data more efficiently, such as survey outcomes when an organization will review it but does not have time to look through it thoroughly.

They can take the survey outcomes and produce a summary of that data more efficiently.

It can also help organizations that are developing a pilot program consider outputs and outcomes.

Do they sound generic or interchangeable when AI is overused?