In the modern ever-changing organizational environment, where hybrid workplace arrangement is becoming increasingly common, and artificial intelligence (AI) technology has been used widely, employees tend to face a situation characterized by ambiguity of work and it is difficult to perceive an understanding of role, expectations, and employment. The paper explores the interrelationship between task ambiguity, risk-taking by managers, AI-induced job insecurity, and employee outcomes in a hybrid working environment. This is based on Social Information Processing Theory where we advance a theoretical model that explores how workforce members actively learn and process information in their social context to get through ambiguity and foster resilience. The evidence of the proposed relationships is substantiated by three studies. Study 1 focuses on the way task ambiguity influences active lurking and also job engagement. Study 2 explores with the moderating factor on the relationship among the variables of task ambiguity, active lurking, and job engagement on managerial risk-taking. Study 3 examines how AI-induced job insecurity can moderate the link between task ambiguity and active lurking and job engagement. The results emphasize the need to ensure clear task specification, active lurking, management risk-taking and proactive efforts to reduce the issue of AI-induced job insecurity as factors that enhance employee engagement. The implications of the study are given and recommendations to conduct further research are outlined.