Artificial Intelligence in Succession Planning: A Systematic Review of Capabilities, Strategic Enhancements, and Organizational Challenges
B. Pranaya Sree
, Dr. S. Venkata Siva Kumar
Artificial Intelligence, Succession Planning, Predictive Analytics, Workforce Planning, Talent Management, Human Resource Analytics
Artificial Intelligence (AI) is transforming succession planning through data-driven, predictive, and portfolio workforce planning. The current study methodically reviews the latest research between 2018 and 2026, thus exploring the role of AI in reinforcing the leadership pipeline by predictive analytics, real-time skill real-time, and personal learning systems. The results show that AI improves the process of decision-making by predicting talent requirements, screening high-potential employees, and reducing the use of subjective opinions. In addition, highly developed functionality like foresight towards risk and transfer of knowledge also helps to solidify the preparedness and continuity of organizations. However, notable obstacles still exist, including data quality issues, algorithm bias, ethics, and employee confidence, all of which are a big hindrance to general use. The research highlights the need to establish open AI systems, effective data handling, and cooperative human-AI model in human resources practice. Overall, AI-based succession planning provides both a strategic edge as it enhances organizational responsiveness, efficiency, and talent fit in unstable corporate contexts but also suggests that the task needs to be ethically conducted.
"Artificial Intelligence in Succession Planning: A Systematic Review of Capabilities, Strategic Enhancements, and Organizational Challenges", JETNR - JOURNAL OF EMERGING TRENDS AND NOVEL RESEARCH (www.JETNR.org), ISSN:2984-9276, Vol.4, Issue 4, page no.a56-a60, April-2026, Available :https://rjpn.org/JETNR/papers/JETNR2604008.pdf
Volume 4
Issue 4,
April-2026
Pages : a56-a60
Paper Reg. ID: JETNR_233489
Published Paper Id: JETNR2604008
Downloads: 00055
Research Area: Management All
Country: Mahabubnagar, Telanagana, India
ISSN: 2984-9276 | IMPACT FACTOR: 9.87 Calculated By Google Scholar | ESTD YEAR: 2023
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.87 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: RJPN (IJPublication) Janvi Wave
