Artificial Intelligence (AI) sounds omnipotent and affects almost everyone in the workplace. Yet, is AI really that good? Two specific questions are proposed. First, does AI help employee management, if so, how? And second, does AI-driven management (AI-M) affect employees’ emotions, if so, why?
Does AI help employee management?
The quick answer is yes. AI appears both interesting and ubiquitous in the workplace. AI has been applied to the marketing strategies, energy saving, weather forecast, risk analysis, customer services, education and business solutions.
AI processes smart technology, assisting both entrepreneurs and organisations in delivering better quality service and more efficient performance. Broadly speaking, there are four types of AI: reactive, limited memory, theory of mind, and self-awareness.
Recently reactive-AI has demonstrated its influence into the field of employee management; for instance, managers have improved employee performance through the AI-driven techniques, such as performance-tracking APPs and KPI-monitoring software. Different from the conventional approach that focuses on the target achievement, AI-M adopts a more holistic and interactive approach, enabling both managers and subordinates to monitor the performance progress more effectively, from the initial goal-setting stage to the final completion stage.
Businesses and enterprises also adopt big-data in their employee management practices, with a view that AI-M offers better insights into how to execute and operate in performance appraisal, staff recruitment and succession planning and performance management.
Take the recruitment of assembly-line workers for instance, the conventional way is that applicants submit their resumes and application forms to the company first. Managers then spend weeks reviewing all applications and getting the best candidates shortlisted, in which delays and errors may occur from time to time.
Unlike the conventional approach where the candidate assessment relies on one specific dimension (or stage) of career characteristics, AI works in a holistic way. Once the applicants complete the surveys online, AI can take over the recruitment process, execute multi-staged-assessments and get the job done within seconds.
Specifically, the reactive-AI assisted recruitment is operated through multiple stages of measurement and assessment, allowing cross-reference checks, reciprocal comparison and social-desirability checks. The multiple stages of measurement often include the utilisation of psychometrics, such as Holland occupational codes, Myers-Briggs, and job-based skills and knowledge.
Reactive-AI assisted recruitment is capable of providing an accurate prediction of the best candidates, including their job-fitness and performance potential. Simply put, AI does the hassles and managers enjoy the benefits.
Does AI-driven management affect employees’ emotions?
The answer is positive, but with conditions. According to Richard Lazarus, emotion is a subjective and conscious experience that is characterised by psycho-physiological expressions, biological reactions and mental states. Emotion has an ability to affect employees’ attitudes and behaviours, generating different impacts on their organisational commitment, job loyalty and lying tendency at work.
Emotion is related with employees’ organisational identification and deviance behaviour. Emotion reacts to the stimuli and affects health swiftly, explaining why employees with stable emotion better cope with threat and stress. Following this line of research, we can understand why emotion is an important factor to workplace attitudes and behaviours. As such, when AI gradually exercises its influence into the employee management practices, it would be sensible for managers to know how AI-M may affect their employees’ emotion and performance.
Despite AI-M’s merits, such as more efficient performance and less human errors, it may imply triggers of negative emotion, and some employees are concerned about it. For instance, AI-M has an ability to replace human labour in mechanical and routine tasks of a job, such as manual and non-heuristic duties, and could replace some jobs, therefore individuals in those roles may develop concerns about their job security and career development opportunity. These remarks help explain why some employees develop a feeling of anger, unfairness, frustration, and disgust.
Moreover, the values of AI-M seem different in the eyes of managers. Researchers from the University of East London summarise managers’ viewpoints in two ways. First, AI-M has an ability to take over the ownership and responsibility of decision-making in managerial policies and practices. Secondly, AI-M may compromise managers’ job roles and affect their influence in the teams, groups and the organisation. This can explain why some managers develop a series of negative emotions about AI-M.
Stephen Hawking said: “AI is no longer science fiction, as it has penetrated into our life.” AI has shaped our workplace and, very likely, will continue to affect our working experiences.
In the field of employee management, more specifically, we have witnessed that AI-M is currently benefiting both employers and employees, but carrying some challenges too. To the employees, AI-M may lead to job insecurity and less career development opportunities. To the managers, AI-M may take over their ownership of decision-making and compromise their influence at work.
Therefore, managers should remember that unless the challenges of AI-M are intervened, their managerial policies may not reach the maximum effect. AI is a double-edged sword in employee management.
Kirk Chang is professor of business at the Royal Docks School of Business and Law, University of East London