Executive Summary
This benchmark will evaluate planning intelligence maturity — where models live, how planners govern recommendations, and how execution feedback closes the loop.
The study is in preparation. No benchmark scores are published until methodology and participant criteria are finalized.
Key Research Themes
- Explainability requirements for planner trust
- Spreadsheet-side AI versus platform-native intelligence
- Replanning governance and exception workflows
- Executive evaluation criteria for AI planning investments
Benchmark Matrix
Planned exhibit: AI planning maturity matrix. No chart or benchmark data has been published.
Proposed methodology
Benchmark dimensions will be published before data collection begins. Participating organizations will be anonymized.
The study prioritizes operational governance over algorithmic novelty.
Executive Recommendations
- Require explainable trade-offs before scaling optimization
- Measure override rate and replan frequency alongside model metrics
- Embed planning intelligence in the operating system, not adjacent tools
This research is in preparation. The page contains the proposed scope, not completed findings or a published methodology.
