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Successful localization policies are critical to the resolution of difficult social problems in the Gulf States relating to rising populations and youth unemployment. Successful localization is proving difficult, however, and this paper aims to look specifically at Omanization in an effort to contribute to a better understanding of a complex socio‐economic arena.

The paper is based on 25 interviews with Ministerial officials and senior private sector managers with human resource management responsibilities in Oman. Interviews were open‐coded to allow factors specific to Oman to emerge from the data.

Key findings are that the perceptions of the employability of locals remains a difficult supply side problem and employers' preferences for foreign labour remains a difficult demand side problem.

The paper is strengthened by the involvement of senior managers yet it is difficult to separate stereotypes of local labour from stereotypes of foreign workers.

The insights reported in the paper identify key areas for further development of localization policy.

The paper provides a new perspective on the difficulties of localization in the Gulf States.

From a technological determinist perspective, machine learning (ML) may significantly contribute towards sustainable development. The purpose of this study is to synthesize prior literature on the role of ML in promoting sustainability and to encourage future inquiries.

This study conducts a systematic review of 110 papers that demonstrate the utilization of ML in the context of sustainable development.

ML techniques may play a vital role in enabling sustainable development by leveraging data to uncover patterns and facilitate the prediction of various variables, thereby aiding in decision-making processes. Through the synthesis of findings from prior research, it is evident that ML may help in achieving many of the United Nations’ sustainable development goals.

This study represents one of the initial investigations that conducted a comprehensive examination of the literature concerning ML’s contribution to sustainability. The analysis revealed that the research domain is still in its early stages, indicating a need for further exploration.