Journal of Excellence in Social Sciences

When AI Helps but Humans Feel Less Capable: The Impact of Generative AI Reliance on Professional Self-Efficacy and Meaningful Work

Muhammad Usman Siddqiue, Syed Ali Sultan — Mon, 15 Jun 2026 00:00:00 +0100

While generative artificial intelligence (GenAI) has the potential to enhance knowledge work, the psychological impact of its use is not fully known. Based on Social cognitive theory and Self-determination theory, this study explores whether the use of GenAI erodes employees' professional self-efficacy and subsequently their meaningful work, and whether AI-literacy helps to protect against this negative trend. The three-wave time-lagged survey of 350 knowledge workers in Pakistan was analysed using composite-based regression (PROCESS Model 7) with bootstrapping method, which was cross-validated with PLS-SEM. Professional self-efficacy (β = −.277) and meaningful work (β = −.123) decreased with the dependence on GenAI. Professional self-efficacy was a significant predictor of meaningful work (β = .479) and accounted for half of the total effect (indirect effect = −.133). The indirect effect was reduced when AI literacy was low (−.199), but it became less negative and significant at high AI literacy (−.068; index of moderated mediation = .066). Results were consistent across the control variables, the PLS-SEM and the method-variance checks. The study moves the discussion about GenAI productivity to one about psychological cost, clarifies the role of self-efficacy in the link between reliance and meaningful work and introduces the concept of AI literacy as a trainable organisational shield.

Sovereign Future or Distant Spectacle? A Comparative Content Analysis of Artificial Intelligence Coverage in Pakistan’s English and Urdu Press after the National AI Policy 2025

Madanlal Tembhre, Muhammad Ashfaq — Thu, 25 Jun 2026 00:00:00 +0100

Artificial Intelligence (AI) has become a pivotal element in the state's policies, business strategies, and daily operations in Pakistan. Since the National AI policy was accepted in July 2025, the press has become an important space for negotiations around the definition of AI. Based on framing theory and agenda-setting theory, and sociotechnical imaginaries, this exploratory study analyzes the national dailies in English and Urdu to understand how they have framed AI in the first year of policy. Framing devices were qualitatively analysed in conjunction with a localised ten-frame codebook for a quantitative content analysis of 53 articles in 11 local newspapers. National development and sovereignty were the dominant frame, followed by misinformation and deepfakes, and economic opportunity. The risk-oriented frames outnumbered the opportunity-oriented ones, as is more common in the Global South, and regulation and ethics seemed to be represented primarily in the English-language commentary. Words were balanced for tone in both languages. The sources were dominated by the government officials, with few ordinary citizens present. The greatest difference lay in the concept of proximity, English newspapers transformed AI into a national policy issue, while Urdu newspapers mostly treated it as a global war spectacle, a celebrity and moral crisis, and only Urdu newspapers used a religious lens to discuss AI. This study provides the first English–Urdu comparative analysis of AI coverage in Pakistan and its relevance for the areas of AI literacy and inclusive technology governance.

Who Am I When AI Does the Work? Human–AI Collaboration, Professional Identity, and Meaningful Work

Zohaib hassan, Faisal umar — Thu, 18 Jun 2026 00:00:00 +0100

How is this cognitive work done by AI affecting the identity and significance of employees' work?How is the professional identity of employees affected when AI increasingly performs cognitive work? Based on the social identity theory, identity-work scholarship, and meaningful-work literature, this study aims to analyze how professional identity serves as a boundary condition between human–AI collaboration and meaningful work, and to explore AI augmentation cognition as a first-stage boundary condition. The data gathered from the survey were analyzed using a confirmatory factor analysis, and conditional process analysis was conducted through regression analysis for 372 employees who had experienced AI related to their work. Human-AI collaboration was positively related to both professional identity and meaningful work, and partially mediated the relationship between human-AI collaboration and meaningful work. The moderated mediation hypothesis was not confirmed as collaboration positively influenced professional identity but did not significantly enhance the positive effect of AI augmentation cognition on professional identity. The results suggest that human-AI interactions can aid in meaningful work partly through the mediation of helping workers maintain and remediate a desired sense of professional self. They also propose that augmentation beliefs can function as an independent identity resource whether or not engagement in collaboration is identity enhancing. The study builds on research on human–AI collaboration by connecting existing research on work design, professional identity, and meaningful work within a single explanatory framework as well as identifying implications for designing meaningful work with AI that maintains human agency, expertise, and purpose.

When Resilience Becomes a Burden: Rethinking Employee Resilience in Contemporary Workplaces

Sidra Raza, Marwa Tahir — Thu, 25 Jun 2026 00:00:00 +0100

Uncertainty, increased workload, regular upheavals and the need for adaptability among employees are more and more the challenges organizations are dealing with. In general, resilience has been considered as a good personal and job attribute which helps employees bounce back, adjust and remain functional when facing difficulties. Less focus has been placed on situations where resilience is an expectation of an organization, rather than a capability of an individual. This conceptual paper introduces employee resilience pressure (ERP) which is the employee's perceived expectation that he or she will be able to adapt, remain emotionally composed, productive and recover from the lack of organizational resources. Based on the Conservations of Resources Theory, Job Demanding-Resources theory, research on emotional labor, and recovery literature, the present paper introduces the concept of Resilience Burden framework that consists of two types of resilience: resilience as a resource and resilience as a demand. Resilience expectations can improve coping ability, learning, adaptability and sustained performance in supportive contexts. On the other hand, chronic stress and lack of resources can lead to compensatory activity, difficulty with emotional regulation, impaired recovery, and progressive depletion of resources, leading in turn to exhaustion, cynicism, withdrawal, and burnout. The following boundary conditions are suggested: organizational support, autonomy, psychological safety, workload intensity, recovery-supportive leadership, and adversity controllability. The framework also looks at how to understand the limits of sustained expectations of resilience in an individual and highlights the role of the organisation in ensuring conditions are created for sustainable employee resilience.