Where AI Actually Helps in Open Calls (and Where It Doesn’t)

For small arts organizations, open calls can be both essential and overwhelming.

They’re one of the primary ways new artists enter a program. They expand networks, bring in new ideas, and create access points. But they also generate a very specific kind of labor—one that is rarely visible and almost always underestimated.

Hours are spent:

• renaming files
• cross-checking information
• answering the same applicant questions
• reformatting data for jurors
• trying to make sense of submissions that technically meet requirements but are difficult to navigate

Most of this work has nothing to do with evaluating art. And for many artist-run spaces or mid-size nonprofits, it’s handled by one or two people, often alongside everything else.

So when AI enters the conversation, the question shouldm't be “Can this replace curators?” Rather “Can this reduce the amount of time we spend managing information?”

The answer is yes. Here are some specific ways.

Where Open Calls Actually Break Down

Submission platforms like Submittable or CaFÉ provide structure, but they don’t necessarily create clarity.

Anyone who has worked across multiple calls—whether as an organizer, artist, or juror—has seen the same patterns:

• File names that don’t match artist names
• Artwork titles that don’t align with uploaded images
• Inconsistent formatting across applications
• Clean interfaces that become messy once data is exported
• Jury processes that require building new systems outside the platform

Even when applications are “complete,” they often require additional labor to make them usable.

A common moment: exporting a CSV file after selections and realizing that before you can share anything, everything needs to be cleaned, renamed, or reorganized.

This is the work that accumulates. Not reviewing the submissions, but preparing them to be reviewed, shared, or archived.

Where AI Actually Helps

AI can mimic interpretation, but it’s not equipped to make meaningful curatorial judgments. It is, however, very good at pattern recognition, standardization, and repetition. That makes it useful in places where time is lost to inconsistency.

1. Cleaning and Structuring Data

After an open call, you often end up with:

• a spreadsheet of selected artists
• a folder of images
• a mismatch between how those two things are labeled

AI can help reconcile that.

For example:

• Renaming files so they follow a consistent structure
• Matching artwork titles to image files
• Standardizing capitalization, punctuation, and formatting across datasets

This is the kind of task that is tedious, error-prone, and necessary. It’s also where AI can save hours.

2. Catching What Slips Through

Most submission platforms ensure that required fields are filled. They don’t ensure that submissions are clean or consistent.

AI can help flag:

• duplicate submissions
• image files that don’t meet stated requirements
• inconsistencies across entries (e.g., mismatched titles or missing metadata)

Think of it less as automation and more as a second pass to catch what the system doesn’t.

3. Editing Call Materials (Not Writing Them)

For small organizations, calls for entry are often written quickly and reused across cycles.

Over time, they accumulate:

• unclear instructions
• missing details
• inconsistencies between sections

AI is useful here as an editor, not a writer. AI is good at:

• tightening language
• identifying gaps in information
• helping restructure FAQs based on real applicant questions

This is especially valuable when you don’t have time to step back and revise your own writing.

4. Reducing Repetitive Communication

Every open call generates the same patterns of communication:

• “Can I submit this type of work?”
• “Did my application go through?”
• “When will decisions be announced?”

AI can help draft:

• response templates
• clearer FAQ sections
• updated guidance based on recurring questions

Individually, these are small interventions. Collectively, they reduce the volume of back-and-forth that happens during a call.

Where AI Does Not Help

AI should not be used to evaluate or select work. It fundamentally doesn't understand what’s being asked. Art evaluation is not pattern matching. It’s contextual, subjective, and shaped by curatorial intent.

Using AI to:

• rank submissions
• assess quality
• filter artists

introduces more problems than it solves—especially around bias and transparency.

There’s also a difference between processing information and interpreting it.

AI can assist with the first. It should not be responsible for the second.

A Note on Transparency

Organizations don’t need to disclose every instance of automation.

But there is a meaningful distinction:

• If AI is helping organize files or standardize data → no disclosure needed
• If AI is shaping language, analysis, or interpretation → transparency matters

Framing AI as an administrative assistant rather than a decision-maker helps maintain trust with applicants.

The Real Issue Isn’t AI—It’s Workflow

Most open call systems aren’t broken because they lack advanced technology. They’re difficult because they were never designed as complete workflows.

Instead, they’re a combination of:

• a submission platform
• spreadsheets
• email threads
• shared folders
• ad hoc fixes

AI doesn’t fix that. But it can make a well-designed system more efficient. The more structured your process is, the more useful these tools become.

The less structured it is, the more confusion it amplifies.

How to Start Without Overcomplicating It

You don’t need to redesign your entire system to see benefits.

Start with one friction point:

• Are you renaming files manually after every call?
• Are you answering the same five questions repeatedly?
• Are you cleaning up data before sending it to jurors?

Then test a small intervention:

• Use AI to standardize file naming
• Refine your call language and FAQs
• Clean and format your data before sharing it

The goal isn’t efficiency for its own sake. It’s to reduce the amount of time spent managing information so more time can be spent reviewing work.

A Better Use of Time

Open calls are not just opportunities. They are systems that shape how time, attention, and care are distributed.

For small organizations, the challenge is rarely a lack of vision. It’s the accumulation of administrative work that pulls focus away from the work itself.

Used thoughtfully, AI can help reduce that friction. Not by changing how decisions are made, but by making the surrounding processes more consistent, usable, and manageable.

The result is simple: more time and attention on artists and their work.

Strata Studio works with arts organizations to design open call workflows that are more consistent, more usable, and less administratively heavy by using practical tools that support existing systems rather than replacing them.