Indispensable skills for human employees in the age of robots and AI

Purpose

Based on sociotechnical systems theory, social (human) and technological sub-systems in an organization should be taken in account when making strategic decisions and designed to fit the demands of the environment for organizational effectiveness. Yet there is very limited information in literature on whether employees are well equipped with indispensable (human) skills to prepare them combating challenges caused by advanced technology. The purpose of this study is to empirically investigate employees’ human skills that are critical for success in the Age of Robots and Artificial Intelligence from human resource development’s perspective.

Design/methodology/approach

A questionnaire was developed for the purpose of this exploratory study. A total of 422 US Midwest employees were surveyed on their human skills level that are critical for success in the Industry 4.0 transformation.

Findings

In general, the respondents could perform all the measured human skills (which can be categorized into social skillset and decision-making skillset) more than adequate but may vary by education level and gender. To strengthen one’s human skills, organizations may begin with facilitating employees on relationship building to create a support system and a strong sense of belonging, which will promote their social sensitivity and collaboration skill development, as well as decision-making skillset.

Originality/value

The findings of this study can be used for techno-structural interventions and employee development programs. This study highlights the importance of investigating human skills to cope with the changing nature of work and make upskilling more feasible and flexible for workers to be robot-proof.

Embracing the sobering reality of technological influences on jobs, employment and human resource development

Purpose

This paper aims to provide a sobering and unique view of technological unemployment and job changes by identifying endangered jobs and skills, as well as the essential up-skills critical to employees’ performance, which cannot be replaced by technology.

Design/methodology/approach

A systematic literature review, used because it is replicable, transparent, and scientific, was implemented to examine the current and future technological influences on employment, job outlook, work structure, and human resource development (HRD).

Findings

The study concludes that HRD professionals should promptly reexamine their social responsibility relative to the technological influence on workers by focusing developmental efforts on employees’ human skills while assisting workers’ transition to a skill-polarized workplace. HRD professionals should play a major role in facilitating employees’ coexistence with robots in the workplace.

Originality/value

While recognizing the valuable contributions of previous researchers with similar concerns, this comprehensive review provides an amalgamated and updated view, which reveals the escalating and combined challenges of a skill-polarized workplace, a tendency of technological unemployment for those positioned in middle-skill jobs, and an increased demand for employees with a higher level of human skills.

Predicting Consumer Responses to a Chatbot on Facebook

As chatbots have become increasingly popular over the past years, most social networking sites have recognized their far-reaching potential for commercial purposes. Their rapid and widespread usage warrants a better understanding. This study examines the effectiveness of chatbots on Facebook for brands. The study proposes and tests a model based on the Consumer Acceptance of Technology model (CAT-model) including three cognitive (i.e., perceived usefulness, perceived ease-of-use, and perceived helpfulness) and three affective (pleasure, arousal, and dominance; PAD-dimensions) determinants that potentially influence consumers' attitude toward brands providing a chatbot, and hence, their likelihood to use and recommend the chatbot (i.e., patronage intention). Structural equation modeling analyses show that two cognitive (i.e., perceived usefulness and perceived helpfulness) and all three affective predictors are positively related to consumers' attitude toward the chatbot brand. The findings further indicate that attitude toward the brand explained a significant amount of variation in consumers' patronage intention. Finally, all the significant determinants also have an indirect effect on patronage intention, mediated through attitude toward the brand. In conclusion, our findings hold valuable practical implications, as well as relevant suggestions for future research.