The study is based only on secondary data, therefore, the findings depend on the accuracy and reliability of existing sources

The gap

Evidence profile

Sourced from the limitations section and stated research gap and inline gaps of the source papers, classified as general, drawn from work published between 2024 and 2026, spanning 2 journals. Those papers have been cited 175 times in total.

Supporting evidence — 3 representative gaps

• The Future of Rural Employment in the Age of Artificial Intelligence: Opportunities and Challenges (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi

  The study is based only on secondary data, therefore, the findings depend on the accuracy and reliability of existing sources. The study does not include primary surveys or field investigations. Rapid technological changes in AI may affect the relevance of certain data over time. Availability of rural AI-related employment data is limited in some areas.

  generallimitations sectionevidence 5/5
  Keywords: study based only secondary data therefore findings depend
• Artificial Intelligence, Automation, and Employment Dynamics: Evaluating the Balance Between Job Displacement and Job Creation (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi

  The paper identifies a gap in the existing literature, which examines job displacement or job creation separately, but not the net employment balance across sectors. The study highlights the need to incorporate institutional factors in the analysis of AI's employment effects. The paper notes that developing economies with large informal labor markets remain underexplored in AI employment research.

  generalstated research gapevidence 5/5
  Keywords: paper identifies gap existing literature examines job displacement
• The impact of artificial intelligence on employment: the role of virtual agglomeration (2024) · Humanities and Social Sciences Communications · cited 175× · doi

  Therefore, the sample size of countries should be expanded in future studies, and the possible heterogeneity of AI should be explored and compared by classifying different countries according to their stage of development. First, only the effect and mechanism of AI in promoting employment from a macro level are investigated in this study, which is limited by the large data particles and small sample data that are factors that reduce the reliability and validity of statistical inference.

  generalinline gapsevidence 5/5
  Keywords: sample countries size expanded future possible heterogeneity explored compared classifying different according stage development first

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