Bora Upendra Rao
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Bora Upendra Rao has a total of 7 co-authors. Here are the top co-authors by number of shared publications:
- Madhur Taneja
Centre of Research Impact and Outcome, Chitkara University, Rajpura- 140417, Punjab, India
1 shared publication - Malcolm Homavazir
Department of ISME, ATLAS SkillTech University, Mumbai, India
1 shared publication - Manoranjan Dash
Associate Dean, Institute of Business & Computer Studies (IBCS), SOA University, Bhubaneswar 751030, Odisha, India
1 shared publication - Mathan N
Master Of Business Administration, Sathyabama Institute of Science and Technology, Chennai, India
1 shared publication - Reshma Sibichan
Presidency Business School, Presidency Collge, Bengaluru, India
1 shared publication - Sonia Riyat
Department of Management, ARKA JAIN University, Jamshedpur, Jharkhand, India
1 shared publication
Latest Publications
- Open Access
- 1 August 2025
- Published by Salud, Ciencia y Tecnologia in Management (Montevideo)
- Vol. 3, 197
Integration of AI Technologies and Knowledge Management Enhances Business Process Efficiency and Competitive Advantage
The integration of Artificial Intelligence (AI) and Knowledge Management (KM) structures have emerged as a powerful strategy to streamline business processes and gain a competitive edge. The primary objective is to examine how the integration of AI and KM improves business efficiency, fosters innovation, and enhances competitive advantage across various industries, providing insights into the measurable benefits. Key variables include the level of AI integration, knowledge management (KM) effectiveness, business process efficiency, competitive advantage, and employee satisfaction. These factors were measured using standardized scales to determine their interrelations and impact on business performance. Data was collected using surveys from 750 employees across 10 companies, alongside 15 interviews with senior managers. SPSS was used to analyze quantitative data. SPSS was also used for correlation, regression, and descriptive statistics of key variables. There are strong positive correlations between business process efficiency and AI integration level (0.64) as well as between competitive advantage and KM effectiveness (0.67), and the results show that all variables have high mean scores, with business process efficiency having the highest mean (4.22) and employee satisfaction having the lowest (3.98). The investigation concludes that integrating AI technologies with KM systems significantly improves business process efficiency and provides a competitive edge. Organizations should prioritize these integrations to stay competitive, though challenges such as resistance to change must be managed.
- 1 August 2025
- Published by Salud, Ciencia y Tecnologia in Management (Montevideo)
- Vol. 3, 197
Open AccessIntegration of AI Technologies and Knowledge Management Enhances Business Process Efficiency and Competitive Advantage
The integration of Artificial Intelligence (AI) and Knowledge Management (KM) structures have emerged as a powerful strategy to streamline business processes and gain a competitive edge. The primary objective is to examine how the integration of AI and KM improves business efficiency, fosters innovation, and enhances competitive advantage across various industries, providing insights into the measurable benefits. Key variables include the level of AI integration, knowledge management (KM) effectiveness, business process efficiency, competitive advantage, and employee satisfaction. These factors were measured using standardized scales to determine their interrelations and impact on business performance. Data was collected using surveys from 750 employees across 10 companies, alongside 15 interviews with senior managers. SPSS was used to analyze quantitative data. SPSS was also used for correlation, regression, and descriptive statistics of key variables. There are strong positive correlations between business process efficiency and AI integration level (0.64) as well as between competitive advantage and KM effectiveness (0.67), and the results show that all variables have high mean scores, with business process efficiency having the highest mean (4.22) and employee satisfaction having the lowest (3.98). The investigation concludes that integrating AI technologies with KM systems significantly improves business process efficiency and provides a competitive edge. Organizations should prioritize these integrations to stay competitive, though challenges such as resistance to change must be managed.