Where does AI reduce labor—and where does review still matter?
This study measures repeatable workflow behavior, not AI hype. Responses are structured, pseudonymous, and analyzed in aggregate.
Before you participate.
Eligible population
People currently using AI in at least one repeatable professional, creator, publishing, or small-business workflow.
Publication threshold
At least 75 validated eligible responses before a benchmark can pass the minimum sample gate.
What we do not ask for
No name, email, phone, address, account ID, confidential employer/client data, prompts, or proprietary work product.
Known limitations
Recall bias, tool differences, task complexity, workflow maturity, and respondent experience can affect reported savings and reliability.
AI Workflow Adoption Benchmark v1 — canonical study record.
Study identifier
MINDSET-AIWA-2026-01
Status: Collecting
Protocol version: v1
Study design
Structured observational self-report. Responses are pseudonymous, fixed-choice and numeric, and analyzed in aggregate.
Population
People currently using AI in at least one repeatable professional, creator, publishing, or small-business workflow.
Publication gate
At least 75 validated eligible responses. Meeting the sample threshold alone does not publish a benchmark; methodology and limitation review remain required.
Controlling methodology: Editorial & Research Methodology. Program status: Research & Data Center. Citation guidance: Media & Citation Center.