How to Simplify Grant Processing Before Implementing AI

When people talk about modernizing grant management, the conversation often jumps too quickly to technology. Automation, artificial intelligence, assistants, smart validations. All of that can add a lot of value, but there's a crucial prerequisite you shouldn't skip: before implementing AI, you need to simplify the process.

Not because technology doesn't help, but because no system truly improves a procedure that is still burdened with unnecessary steps, unclear criteria, duplicated tasks, or poorly structured documentation. If the process is confusing, technology won't fix it on its own: more often than not it only accelerates the confusion.

That's why, in grants, the first useful transformation is usually much more basic and much more strategic at the same time. It consists of reviewing how work is done today—where time is lost, which tasks add friction, and what part of the effort is actually necessary.

Simplifying before implementing AI doesn't mean giving up on innovation. It means preparing the ground so any future improvement has a real impact.

The error of starting with the tool

In many modernization projects, the first question is “what solution do we need?” But in complex procedures like grant management, that isn't usually the best opening question.

A more useful question is: “which part of our current process is costing us the most time, consistency, or responsiveness?”

That shift in focus moves attention away from the tool and toward the problem. It also avoids one of the most common mistakes in any transformation: trying to apply technology to a process that hasn't been reviewed in sufficient detail.

If an organization isn't clear about where its bottlenecks are, which tasks are repeated, which incidents concentrate in each phase, or which steps could be simplified, any implementation risks becoming just an added layer rather than a real improvement.

What it really means to simplify

Simplifying is not just about cutting paperwork or removing steps at random. Done well, simplification makes the procedure clearer, more consistent, and easier to manage—without sacrificing safeguards.

In practice, that can mean several things:

• Redefining phases that currently overlap.

• Standardizing communications and documents.

• Unifying review criteria.

• Reducing redundant validations.

• Better organizing the information in the case file.

• Making bottlenecks more visible.

• Reviewing which data are requested, when they're requested, and what they are used for.

In other words, simplifying is not just “doing less.” It's removing unnecessary friction so important work stands out and repetitive work matters less.

Signs you should simplify before digitizing more

There are several clear signs that an organization needs to simplify first and automate later:

• The team still relies heavily on emails, folders, and manual checks.

• Templates exist, but each person customizes or recreates them.

• Case traceability doesn't clearly show the real status.

• Corrections (subsanaciones) take too long.

• Repetitive tasks keep being done from scratch over and over.

• People talk about implementing improvements, but there isn’t an accurate picture of the current process.

• Administrative burden is growing, but it's hard to explain exactly why.

In that context, introducing a new technological layer can create an initial feeling of progress without necessarily solving the underlying problem. If the procedure is already disordered, fragmented, or overcomplicated, that complexity just gets transferred.

Where to start simplifying

You don't need a massive review to start seeing improvements. Often it's enough to approach the process with a very practical, operational mindset.

1. Map the actual process

The first step is to understand how a case really moves through the system—not how it should move in theory, but how it moves in practice: which areas get involved, where delays occur, which validations are repeated, which information is consulted multiple times, and which tasks aren't formalized but are part of daily work.

That map usually reveals a significant gap between the formal procedure and the real one.

2. Identify recurring frictions

Once the flow is mapped, locate the points where most effort concentrates:

• Incomplete or inconsistent documentation.

• Manual review of attachments.

• Recurrent doubts about criteria.

• Rewriting the same communications repeatedly.

• Lack of clarity about the next step in the case.

• The need to redo checks that were already performed earlier.

You don't need to find twenty problems. Just identify the ones that repeat most and absorb the most time.

3. Standardize what currently depends too much on individual people

Many procedures run reasonably well thanks to team experience, but that doesn't mean they're well designed. Often it means people are compensating with effort and judgment for what the process doesn't resolve on its own.

That's why one of the most effective levers is standardization: review checklists, report structures, request templates, basic validation criteria, responses to frequent incidents, and case status definitions.

The less the quality of the procedure depends on individual memory, the more robust the system will be.

4. Measure the essentials

You don't need to build a perfect indicator system from day one. But you should start measuring a few basic variables: average time per phase, volume of corrections, most frequent incident reasons, points where the most delays occur, and the type of task that consumes the most capacity.

These metrics change the conversation completely. What used to be intuition becomes a basis for prioritizing.

5. Prioritize small but visible improvements

An effective review doesn't need to fix everything at once. In fact, it usually works better when it selects a few changes with clear impact: unifying templates, simplifying a particularly slow phase, reducing avoidable requirements, improving document structure, clarifying statuses and traceability.

When those first improvements are noticeable, the organization gains confidence to tackle more ambitious changes.

What good simplification prepares for

Here's the important part: simplification is not a minor preliminary step. It's what makes it possible for technology to be applied where it truly adds value.

Once the procedure is clearer, more organized, and better measured, it's much easier to detect which tasks make sense to support with targeted tools:

• Summarizing guidelines or calls for proposals.

• Assisting with preliminary review of documentation.

• Classifying submissions and attachments.

• Detecting inconsistencies.

• Helping draft communications.

• Quickly retrieving relevant information.

Without that prior work, AI risks being applied to poorly defined tasks, with unrealistic expectations or without a clear criterion for impact.

Simplifying is also a way of modernizing

Sometimes modernization is associated only with large projects, new platforms, or advanced automation. But many public organizations improve more by ordering their operations than by adding technology too early.

Simplifying a procedure is modernizing it. Because it reduces unnecessary burden, brings more consistency to the work, makes case status more visible, and frees up time for tasks that truly require technical judgment.

In grants, that has special value. It's not just about processing faster, but about managing better: with less friction, more clarity, and more capacity to focus effort on what really matters.

Before thinking about implementing AI in grants, ask a simpler question:

Is your procedure today clear enough, measured enough, and organized enough for a technological aid to deliver real value?

In many cases, the smartest improvement doesn't start with automation. It starts with simplification.

If you want to know how OptimGov Subvenciones can help simplify and improve grant management in your organization, you can learn more at:

optimtech.es/optimgov-subvenciones