A Balanced Enterprise Architecture Framework for AI Adoption

Abstract

Artificial intelligence is increasingly central to enterprise transformation, yet many organizations still approach adoption through disconnected pilots, vendor-driven experimentation, or narrow technology programs. This paper presents a balanced enterprise architecture framework for AI adoption that integrates business, technology, developer experience, and user experience perspectives with explicit security and ethical AI considerations. Governance and operating model provide the control and coordination needed to scale AI safely, responsibly, and sustainably. The paper introduces a TOGAF-style capability map and a practical execution toolkit covering readiness assessment, use case prioritization, governance gates, reference implementation assets, stakeholder conflict resolution, phased roadmap delivery, threat modeling, data protection, ethical impact assessment, bias review, accountability, and incident response. The proposed framework helps enterprises translate AI ambition into structured, governable, secure, and value-oriented implementation. It argues that enterprise AI maturity should be measured not only by the number of models deployed, but also by the alignment among business capability, technical readiness, engineering enablement, security assurance, responsible governance, and trustworthy human outcomes.

Keywords

AI adoption · enterprise architecture · AI governance · business capability mapping · responsible AI · secure AI implementation · digital transformation

Suggested Citation

Chokhawala, B. (2026). A Balanced Enterprise Architecture Framework for AI Adoption. 44th International RAIS Conference on Social Sciences and Humanities. https://doi.org/10.5281/zenodo.22801627

BibTeX

@inproceedings{chokhawala2026balancedenterprisearchitecture,
  author    = {Chokhawala, Bhagyeshkumar},
  title     = {A Balanced Enterprise Architecture Framework for AI Adoption},
  booktitle = {44th International RAIS Conference on Social Sciences and Humanities},
  year      = {2026},
  doi       = {10.5281/zenodo.22801627},
  url       = {https://doi.org/10.5281/zenodo.22801627}
}