UGC Approved Journal no 63975(19)
New UGC Peer-Reviewed Rules

ISSN: 2349-5162 | ESTD Year : 2014
Volume 13 | Issue 9 | September 2026

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Volume 13 Issue 9
September-2026
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

7.95 impact factor calculated by Google scholar

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Published Paper ID:
JETIR2609015


Registration ID:
585706

Page Number

a132-a154

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Title

AI-Native Enterprise Architecture Framework

Abstract

Artificial Intelligence (AI) is fundamentally transforming enterprise architecture by evolving from a supporting technology into a foundational capability embedded across business processes, applications, enterprise data, decision-making, customer engagement, and digital operations. This research proposes the AI-Native Enterprise Architecture Framework (AINEAF), a comprehensive enterprise architecture framework integrating the SAP Enterprise Architecture Framework (SAP EAF), TOGAF®, SAP Business Technology Platform (SAP BTP), SAP AI Foundation, SAP AI Core, SAP AI Launchpad, SAP Business Data Cloud, SAP Datasphere, SAP Integration Suite, SAP HANA Cloud, SAP Analytics Cloud, Platform Engineering, DevSecOps, Responsible AI, and enterprise governance. Unlike conventional architectures that treat AI as an isolated application layer, the proposed framework positions AI as an architectural capability spanning business architecture, application architecture, enterprise data, integration, cloud platforms, security, operations, governance, and business value realization. The framework introduces an AI-native operating model that aligns enterprise strategy, business capabilities, enterprise data, AI lifecycle management, organizational readiness, governance, and continuous optimization. The proposed approach enables organizations to accelerate digital transformation, strengthen governance, increase AI adoption, improve business agility, modernize legacy architectures, enhance operational resilience, and establish sustainable intelligent enterprises.

Key Words

AI-Native Enterprise Architecture, Enterprise Architecture, Artificial Intelligence, SAP Business Technology Platform, SAP BTP, SAP Enterprise Architecture Framework, SAP EAF, TOGAF, Generative AI, Large Language Models, Agentic AI, Responsible AI, Platform Engineering, DevSecOps, Digital Transformation Co-Author section: I can see an email address entered in row 5 under Co-Authors. Since this is a single-author paper, delete that email and leave all co-author rows completely blank.

Cite This Article

"AI-Native Enterprise Architecture Framework", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.13, Issue 9, page no.a132-a154, September-2026, Available :http://www.jetir.org/papers/JETIR2609015.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"AI-Native Enterprise Architecture Framework", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.13, Issue 9, page no. ppa132-a154, September-2026, Available at : http://www.jetir.org/papers/JETIR2609015.pdf

Publication Details

Published Paper ID: JETIR2609015
Registration ID: 585706
Published In: Volume 13 | Issue 9 | Year September-2026
DOI (Digital Object Identifier):
Page No: a132-a154
Country: Bengalore, Karnataka, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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