Exploring THE Synergy OF Ai AND Design Thinking IN Optimizing Knowledge Management Practices FOR Organizational Efficiency, Customer Satisfaction AND Risk Mitigation

Authors

  • Madhavi Chattarki
  • Sukanya Kundu

Abstract

The study looks at how artificial intelligence (AI), design thinking, and knowledge management practices work together in the IT field. The study uses data of 2283 people collected using questionnaires. The study uses different ways to analyze, including counting things up, finding connections between them, figuring out how they work together and breaking it down into parts.

The results show that using AI apps can help us, the impact of thinking about design and applying knowledge management all work together well. Study on regression show that design thinking, AI recovery and memory efficiency can predict how well practices of managing knowledge work. This is related to the entire process involved in dealing with all types of information. This study provides deep insight on how artificial intelligence, creative thinking and knowledge control are connected. The results are useful companies trying to improve their knowledge management practices in the constantly changing world of technology and new ideas. The study focuses on the IT business and understands its built-in limitations. But it sets up a basic starting point for future study in many areas and encourages looking into these connections with mixed-methods approaches. In the end, this shows how much artificial intelligence (AI) and design thinking affect creating good knowledge management plans. These results are important for planning smart actions and encouraging improvements in organizational creativity.

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Published

2024-02-13

How to Cite

Chattarki, M. ., & Kundu, S. . (2024). Exploring THE Synergy OF Ai AND Design Thinking IN Optimizing Knowledge Management Practices FOR Organizational Efficiency, Customer Satisfaction AND Risk Mitigation. Migration Letters, 21(S5), 42–60. Retrieved from https://migrationletters.com/index.php/ml/article/view/7672

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Section

Articles