The study identifies a gap in the existing literature on AI adoption in supply chain

The gap

Evidence profile

Sourced from the stated research gap and limitations and recommendations and inline gaps and limitations section and stated challenges of the source papers, classified as general, spanning 4 journals. Those papers have been cited 2 times in total.

Supporting evidence — 6 representative gaps

• Barriers to Artificial Intelligence-Driven Supply Chain Integration: An Interpretive Structural Modeling-Cross-Impact Matrix Multiplication Applied to Classification (ISM-MICMAC)-Based Analytics Modeling Approach (2026) · Cureus Journal of Business and Economics · doi

  The study identifies a gap in the existing literature on AI adoption in supply chain management. The analysis highlights the need for a detailed understanding of the hierarchical and causal relationships among barriers. The study aims to address this gap by providing a comprehensive analysis of the barriers to AI adoption.

  generalstated research gap
  Keywords: study identifies gap existing literature adoption supply chain
• A Study on Role of AI in Strengthening India's Digital Trade Ecosystem (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi

  • The study is primarily based on secondary data and survey responses, which may not fully capture the complexity of AI implementation at an enterprise level. • Rapid advancements in AI technology mean that findings may evolve quickly as the sector progresses. • The sample of respondents is drawn from urban commercial centres and may not represent rural traders and micro-enterprises. III.

  generallimitationsevidence 5/5
  Keywords: primarily based secondary survey responses fully capture complexity implementation enterprise level rapid advancements technology mean
• A Study on Role of AI in Strengthening India's Digital Trade Ecosystem (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi

  engines are the most widely deployed AI applications in Indian digital trade. • AI-powered customs automation has demonstrably reduced clearance time and improved compliance accuracy at major Indian ports. • Supply chain and logistics companies using AI report measurable improvements in delivery efficiency and inventory management. • Lack of AI awareness, high implementation costs, and data infrastructure gaps are the primary barriers to broader adoption among smaller trade businesses.

  generalrecommendationsevidence 5/5
  Keywords: indian trade engines widely deployed applications digital powered customs automation demonstrably reduced clearance time improved
• Unveiling the AI–SCM Nexus: A Bibliometric and PRISMA-Based Review of Trends, Technologies, and Future Directions (2021–2025) (2026) · International Journal of Latest Technology in Engineering Management & Applied Science · doi

  Additionally, the limited focus on SMEs and cross-sectoral applications calls for targeted studies that examine AI integration in smaller firms and across different industries, while further research is needed to explore data quality, algorithm design, and human–AI interaction in shaping effective decision-making in supply chains.

  generalinline gapsevidence 5/5
  Keywords: additionally limited focus smes cross sectoral applications calls targeted examine integration smaller firms across different
• A Study on the Impact of Artificial Intelligence on Strategic Decision-Making in Indian Businesses (2026) · International Journal of Emerging Research in Science Engineering and Management · cited 1× · doi

  The shortage of skilled professionals remains a significant barrier to AI adoption in Indian businesses. Insufficient government support, limited policy clarity, and inadequate institutional guidance continue to hinder AI adoption. The absence of comprehensive national standards and clear compliance guidelines creates uncertainty regarding responsible AI usage, data protection, and accountability.

  generallimitations sectionevidence 5/5
  Keywords: shortage skilled professionals remains significant barrier adoption indian
• A Study on the Impact of Artificial Intelligence on Strategic Decision-Making in Indian Businesses (2026) · International Journal of Emerging Research in Science Engineering and Management · cited 1× · doi

  The shortage of skilled professionals remains a significant barrier to AI adoption in Indian businesses. Ethical concerns associated with AI adoption significantly influence organisational trust and decision reliability. The financial burden associated with AI implementation remains a significant obstacle for small and medium-sized enterprises.

  generalstated challengesevidence 5/5
  Keywords: shortage skilled professionals remains significant barrier adoption indian

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