EAIMS v0.2.1 is now available, marking an important step in the evolution of the Enterprise AI Maturity Standard from an executable community standard toward a more reproducible and research-ready foundation.
This release establishes a stable Research Baseline for the first academic research based on EAIMS while improving the connection between the standard, its executable implementation, published books, and reproducibility materials.
What’s New in EAIMS v0.2.1?
EAIMS v0.2.1 builds on the executable foundation introduced in v0.2.0 with several research-focused improvements.
1. Stable Research Baseline
EAIMS v0.2.1 establishes an immutable baseline for research using the framework.
The first EAIMS research work is associated with:
EAIMS version: v0.2.1
Baseline commit: 6d1dbf1
Using a fixed baseline ensures that future changes to the EAIMS main branch do not alter the implementation or assumptions underlying previously reported research results.
2. Reproducible Research Materials
A dedicated research area has been introduced within the EAIMS repository.
The first package is available under:
research/paper-01/
It contains computational sensitivity-analysis code, generated results, and documentation required to examine and reproduce the computational experiments associated with the first EAIMS academic study.
The analysis evaluates computational behavior and classification stability. It should not be interpreted as establishing construct validity, predictive validity, inter-rater reliability, or broad organizational generalizability.
3. Clearer Evidence and Validation Boundaries
EAIMS v0.2.1 further clarifies the distinction between normative evidence requirements defined by the standard and validation performed by the executable implementation.
This distinction is important for maintaining transparency about what EAIMS specifies, what its software validates, and what requires independent organizational or empirical evidence.
4. Scoring Documentation Alignment
Scoring documentation has been aligned with the equal-weight reference implementation used in the v0.2 series.
This improves consistency between the written standard, executable implementation, and research materials.
5. Improved Citation and Version Metadata
Version and citation information has been strengthened across the repository.
Research based on EAIMS should reference a specific immutable release rather than the continuously evolving main branch.
For the first research baseline, that release is EAIMS v0.2.1.
EAIMS Publications
EAIMS now includes a dedicated Publications section connecting the open standard with its published books and research outputs.
English Edition
Enterprise AI Maturity Standard (EAIMS)
Author: Elias Naserkhaki
Free and openly available through Zenodo.
DOI: 10.5281/zenodo.21853733
https://zenodo.org/records/21853733
Persian Edition
استاندارد بلوغ هوش مصنوعی سازمانی (EAIMS)
Author: Elias Naserkhaki
The Persian edition is also freely and openly available through Zenodo.
DOI: 10.5281/zenodo.21863979
https://zenodo.org/records/21863979
Zenodo remains the authoritative archive for the published book files and their version history, while GitHub serves as the primary home for the open standard, executable implementation, and research reproducibility materials.
Supporting Academic Research
The first academic manuscript based on EAIMS is currently undergoing peer review.
Paper 01
EAIMS: An Evidence-Grounded and Executable Framework for Enterprise AI Maturity Assessment
The manuscript itself is not published in the GitHub repository while it is under journal review.
Instead, EAIMS provides the associated reproducibility materials and identifies the exact version of the standard used as its research baseline.
This separation allows the academic publication process and the open development of EAIMS to coexist while preserving research traceability.
From Executable Standard to Research-Ready Foundation
EAIMS v0.2.0 established an executable community draft.
EAIMS v0.2.1 strengthens that foundation by making research artifacts, version relationships, citation guidance, and reproducibility more explicit.
The direction remains unchanged:
Open. Vendor-neutral. Evidence-driven. Executable. Research-ready.
EAIMS will continue to evolve through practical implementation, research, critical review, and community contribution.
Explore EAIMS
Website:
https://eaims.org
GitHub repository:
https://github.com/eaims/EAIMS
Publications:
https://github.com/eaims/EAIMS/tree/main/publications
EAIMS welcomes technical reviews, research collaboration, implementation experience, critical feedback, and contributions from practitioners and researchers working on Enterprise AI maturity.
If you find the project useful, consider starring the GitHub repository and contributing to its continued development.