International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
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A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
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Volume 8 Issue 3
May-June 2026
Indexing Partners
Ai Driven Business Model-innovations and Transformation
| Author(s) | Dr. Nathasha A B, Ms. Farshana Jasmin K |
|---|---|
| Country | India |
| Abstract | Recent years have witnessed a surge in research on artificial intelligence (AI)-driven business model innovation (BMI), demonstrating the profound impact of AI across industries. This study explores how generative AI and advanced analytics are reshaping core business model components: value proposition, operational processes, customer interaction, and monetization mechanisms. By analyzing adaptation patterns in startups and established companies, the research identifies AI-induced opportunities for hyper-personalization, predictive analytics, resource optimization, and automation of cognitive tasks. Through case studies from sectors such as finance, retail, healthcare, and manufacturing, the study highlights how AI systems—from autonomous decision-making tools to machine learning-driven process optimizations—enable organizations to redefine traditional value creation models, achieve higher productivity, and unlock new sources of competitive advantage. The transformation demands not only technological innovation, but also strategic vision, cultural change toward data-driven experimentation, and robust ethical frameworks to ensure transparency and fairness. In conclusion, effective integration of AI technologies into key processes positions organizations to capitalize on new market opportunities and gain significant competitive advantages in the digital era |
| Keywords | Artificial Intelligence, Business Model Innovation, Digital Transformation, Data-Driven Strategy, Organizational Change |
| Field | Business Administration |
| Published In | Volume 7, Issue 6, November-December 2025 |
| Published On | 2025-11-19 |
| DOI | https://doi.org/10.36948/ijfmr.2025.v07i06.60902 |
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E-ISSN 2582-2160
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