Strategic Management of Novel Distributed AIML Techniques for Next Generation Technology and Business - A Holistic Study Focusing on Frameworks for Business Growth and Optimization

Authors

  • Kausik Chakrabarti

Abstract

Infusion of novel Artificial Intelligence and Machine Learning (AIML) algorithms and tools in technology and business platforms herald a transformative evolution in how businesses reinvent themselves to a more cognitive, autonomous structure - toppling the evolutionary process of technology and process change management through siloed views by incumbent technology leaders and shifting the complete ecosystem to a marketplace economy, with alliance and ecosystem formation at the center to derive significant values for each other. This thesis thus aims to deep-dive into some novel AIML technologies and key real-time platform technologies to research the value propositions through adoption of strategic business frameworks aiding the decision-making process for technology and business transformation through the formation of a converged yet dynamic partnership ecosystem. The results and outcomes of the research study and learnings are expected to be strategically and tactically helpful for businesses adopting AIML in their core businesses, helping to adapt and construct effective v
evaluation methodology to navigate through the highly dynamic technology and business landscape that need strategic partnerships and alliances to derive meaningful values.

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Published

2025-04-17

How to Cite

Chakrabarti, K. (2025). Strategic Management of Novel Distributed AIML Techniques for Next Generation Technology and Business - A Holistic Study Focusing on Frameworks for Business Growth and Optimization. Global Journal of Business and Integral Security. Retrieved from https://www.gbis.ch/index.php/gbis/article/view/790