Table 4.1 Perceived Gains and Losses and... | Emerald Publishing

Table 4.1

Perceived Gains and Losses and Implications for Trust for Stakeholders of AI Tools in HRM

Stakeholders of AI Tools in HRM
	Employer	Decision Makers	Decision Target	HR Professionals
Perceived Gains	Increased competitiveness in hiring Decision-making speed Employer branding benefits	Reduced responsibility for HR decisions More time for other tasks	Clear rules and high consistency in HR decisions Avoidance of decision biases (attractiveness, liking, etc.) Voice Adaptions of individual working conditions	Relief from routine tasks, more time for other tasks Support for complex tasks and better decision-making Advancing own skills Reduced responsibility for some HR decisions
Perceived Losses	Monetary investments Non-financial costs Potential poor or biased decisions Potential lawsuits	Potential displacement by technologies Reduced control over decisions	Opaque and potential unfair decision making, algorithmic reductionism Loss of privacy and control over personal data	Loss of professional identity Learning costs Change management processes Potential displacement by technologies
Risk Propensity Trend	Positive	Positive	Negative	Mixed, many moderators

Stakeholders of AI Tools in HRM
	Employer	Decision Makers	Decision Target	HR Professionals
Perceived Gains	Increased competitiveness in hiring Decision-making speed Employer branding benefits	Reduced responsibility for HR decisions More time for other tasks	Clear rules and high consistency in HR decisions Avoidance of decision biases (attractiveness, liking, etc.) Voice Adaptions of individual working conditions	Relief from routine tasks, more time for other tasks Support for complex tasks and better decision-making Advancing own skills Reduced responsibility for some HR decisions
Perceived Losses	Monetary investments Non-financial costs Potential poor or biased decisions Potential lawsuits	Potential displacement by technologies Reduced control over decisions	Opaque and potential unfair decision making, algorithmic reductionism Loss of privacy and control over personal data	Loss of professional identity Learning costs Change management processes Potential displacement by technologies
Risk Propensity Trend	Positive	Positive	Negative	Mixed, many moderators