AI-Native Enterprise Application Design for Cross-Industry Engagement and Growth

Roshan Atulkumar Tathed

doi:10.36676/urr.v12.i1.1557

Authors

Roshan Atulkumar Tathed Harvard Business School Boston, USA

DOI:

https://doi.org/10.36676/urr.v12.i1.1557

Keywords:

AI-native applications, enterprise architecture, cross-industry collaboration, AI governance, human-AI interaction, scalability, interoperability, continuous learning, ethical AI, digital transformation

Abstract

The rapid advancement of artificial intelligence (AI) technologies has catalyzed a fundamental shift in enterprise application design, prompting a move towards AI-native systems where AI is embedded as a core architectural element rather than an auxiliary feature. This study explores the design principles, frameworks, and methodologies necessary to develop AI-native enterprise applications capable of fostering seamless cross-industry engagement and sustainable growth. By conducting a comprehensive literature review and multi-industry case studies, the research identifies key challenges related to scalability, interoperability, governance, and human-AI collaboration in current enterprise AI implementations. To address these challenges, a novel AI-native design framework is proposed, emphasizing modularity, continuous learning, explainability, and compliance.

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