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Artificial intelligence (AI) and robotics are already here, influencing almost every single industry in one way or another. Organisational scientists at Qlearsite use AI and machine learning to unleash the business potential languishing in workforce data – something previously unusable because of its format. This paper aims to track the initial implementation of AI up to present day, based on Qlearsite’s corporate experience.

Using actual experiences, Qlearsite were tasked with demonstrating how businesses can better understand their workforce, identify performance hurdles and develop strategies to clear them, ultimately improving productivity.

While initial implementation strategies may have faced challenges by senior human resources (HR) members across industries, the multiple benefits are evident and measurable against corporate success and productivity levels today.

Where HR leaders and senior decision-makers struggle to solve ongoing issues, such as absenteeism, an acute problem for the financial services industry. This paper demonstrates the true value of AI, with complex issues solved by data analysis – a monumental and expensive task for any employee to carry out.

Introduction: Many organisations nowadays use artificial intelligence (AI) in human resource (HR) activities like talent acquisition, onboarding of new employees, learning and development, succession planning, retention of employees, and automation of administrative tasks. When AI is integrated with HR practices, it helps HR personnel to focus more on the strategic aspects of the HR function and relieve them from routine HR activities.

Purpose: The readiness of employees to accept any change depends on organisational facilitation to change, employee willingness to accept the change, the requirement for change, situational factors, etc. This research studies the factors influencing employees’ change readiness towards acceptance of AI in HR practices. The researchers also strive to develop a conceptual technology adoption model for AI in HR practices by studying the earlier models. Finally, the research explores the acceptance of AI by various service sector employees and identifies whether there is any difference in their acceptance of AI based on demographic variables.

Methodology: A conceptual framework was derived using a combination of previous models, including the Technology Readiness Index (TRI), Change Readiness Scale, Technology Acceptance Model (TAM), Technology, Organization, and Environment (TOE) model, and change readiness scale. A structured questionnaire was designed and distributed to 228 respondents from the service sector based on the conceptual framework. An exploratory factor analysis (EFA) was used to determine the elements that influence employees’ level of change readiness.

Findings: The exploratory results on data collected from 228 respondents show that the model can be used for further research if a confirmatory factor analysis and validity and reliability test are performed. Employees are aware of AI and how it is used in HR practices, based on the study results. Moreover, while most respondents favour using AI in their company’s HR practices, they are wary of some aspects of AI.

We are pleased to publish in this issue an article by Mr. H. H. Bagnall, the recently retired City Analyst of Birmingham, who has for many years been a dominant figure in the world of public analysts. His annual reports have always attracted wide publicity, both for their originality in exposing “ tricks of the trade ” and for his comments, sometimes caustic, sometimes racy, on those who perpetuate such tricks. In his article, he looks backwards through the years to describe in his own inimitable style a few of the important cases he has figured in and we agree with him, that many others in the field of food administration and approaching the end of their public careers, could well emulate this example.

The study examines the relationship between the interaction of indigenous–foreign cultures and public employee performance (PEP) in the Ghanaian public sector due to the perceived unproductive cultures in the public sector.

The study employs a quantitative approach, where cross-sectional survey design is used to collect the data from Ghanaian public employees. The analysis is done using correlation and hierarchical regression techniques.

The results reveal that both indigenous and foreign cultures are pervasive in the Ghanaian public sector, with high power distance and individualism being dominant cultures. Furthermore, while the indigenous cultures have negative significant relationship with PEP, the foreign cultures have positive significant relationship with PEP. The foreign cultures effectively control the relationship between the indigenous cultures and PEP but insignificantly moderate such relationship.

The findings imply that deliberate attempts should be made to encourage the foreign cultures with attractive reward packages to induce workers. This will indirectly control the practice of the inimical cultures and ultimately reduce their negative effect on PEP.

The study contributes significantly to the extant literature by providing empirical evidence of the indigenous–foreign culture fit and PEP from a developing country, Ghana.