Trends from Six Cycles of the Tools Competition
Meg Benner, Kristyn Manoukian, Joon Suh Choi, Kumar Garg
Each year, the Tools Competition reviews hundreds of proposals from teams building the next generation of learning tools. These submissions offer a unique view into how ed tech teams are responding to rapid advances in AI, and what that shift means for the field.
“Building Better AI for Learning,” a new report from the Tools Competition, looks across six years of competition data to understand what this shift means for the field. Drawing on winning teams and hundreds of proposals, the report explores how AI is being integrated into educational learning platforms and what early standards are emerging for tools that aim to be credible, useful, and responsible.
Across the strongest proposals, a clear picture is beginning to emerge. Strong AI-enabled learning tools are grounded in real instructional contexts, tested against meaningful performance expectations, shaped by the needs of specific users, and designed with trust and responsibility in mind from the start.
For developers, researchers, funders, and educators, the report offers a practical view of where AI-enabled learning tools are headed and what it will take for them to earn trust in real education settings.
Download the full report below to explore the trends, examples, and insights shaping the next phase of AI-enabled learning tools.
Explore the Data
Interested in more trends analysis? Check out the Tools Competition Submissions Dataset, a longitudinal record of all 7,147 submissions to the Tools Competition, spanning six funding cycles from 2021 to 2026, and carrying program metadata such as funding track, prize tier, geography, and target audience, and proposal tags.
To preserve competitor confidentiality, identifying fields such as proposal name, organization, and tool summary are included only for the 171 prize winners. Non-winning submissions are limited to metadata and tags.
The dataset is designed to support broader field learning, including analysis of emerging areas of interest, shifts in technology use, and patterns in the audiences, geographies, and focus areas represented across education innovation proposals.
