The Indian technology sector offers a compelling setting for this kind of investigation. Employees in IT and ITeS companies operate in environments defined by rapid technological change, evolving client demands, and constant upskilling. Automation, artificial intelligence, and shifting service models mean that yesterday’s expertise can become obsolete within a few years. In such an atmosphere, whether an employee feels safe enough to voice a half-formed idea, admit uncertainty, or challenge a manager’s plan can determine not only individual wellbeing but also an organisation’s capacity to innovate. Yet, as the authors note, most existing evidence on psychological safety and innovation comes from Western contexts, and relatively little qualitative research has captured how Indian employees actually experience these dynamics.

To address that gap, the researchers adopted a hermeneutic phenomenological approach, a qualitative method designed to uncover the lived experiences of participants and interpret the meanings they attach to those experiences. Rather than measuring psychological safety with survey scales, the study sought depth: what does it feel like to speak up, or stay silent, in a workplace innovation setting? The researchers conducted semi-structured interviews with 20 employees drawn from IT and ITeS organisations located in Chennai and Bengaluru, two of India’s most important technology hubs. Semi-structured interviews allowed participants to describe their experiences in their own words while ensuring that key topics, such as leadership, feedback, and change, were consistently explored across conversations.

The study met rigorous ethical standards. Approval was granted by the Institutional Ethics Committee for Studies on Human Subjects at Vellore Institute of Technology, Chennai Campus, and the research was conducted in line with the principles of the Declaration of Helsinki. All participants provided written informed consent before taking part and consented to the anonymised use of their responses for research and publication. The authors declare no competing interests, and the work was published open access, with funding support provided by Vellore Institute of Technology.

Analysis of the interview data was carried out using NVivo 15, a widely used qualitative data analysis software package. The researchers applied coding and thematic analysis, a systematic process in which interview transcripts are broken down into meaningful segments, labelled with codes, and then grouped into broader themes that capture recurring patterns across participants. From this process, five themes emerged: autonomy, flexibility and empowerment; organisational strategy and change; technology adoption and support; leadership and team culture; and open feedback. Together, these themes map the terrain on which psychological safety is either built or eroded in technology workplaces.

The first theme, autonomy, flexibility and empowerment, points to the importance of giving employees genuine control over how they work. Participants who felt trusted to make decisions, manage their schedules, and experiment with new approaches reported a stronger sense of psychological safety and a greater willingness to contribute ideas. Empowerment, in this sense, is not merely a managerial buzzword but a structural condition: when employees believe their judgement is respected, the perceived risk of proposing something novel drops, and innovation becomes a shared activity rather than a top-down mandate.

The remaining themes highlight the organisational scaffolding around the individual. Organisational strategy and change emerged as a double-edged factor. On one hand, a clear strategic direction helps employees understand why innovation matters and where their contributions fit. On the other, the study found that frequent organisational changes can undermine confidence, leaving employees uncertain about their roles and reluctant to invest energy in new initiatives. Technology adoption and support proved similarly consequential: access to adequate training and technical support made employees feel equipped to engage with new tools, whereas insufficient training left them anxious about being judged for falling behind. Leadership and team culture, along with open feedback, rounded out the picture, with accessible leaders and honest, constructive communication emerging as key ingredients of a climate in which people dare to speak.

The findings paint a coherent picture of what builds and what breaks psychological safety in Indian technology workplaces. Organisational support, leadership accessibility, training opportunities, recognition, and open communication all contributed to employees’ perceptions of psychological safety and their willingness to participate in workplace innovation. Conversely, frequent organisational changes, insufficient training, communication gaps, and fear of negative judgment reduced employees’ confidence to contribute ideas and engage in innovation activities. The fear of negative judgment deserves particular attention: it is the psychological mechanism at the heart of psychological safety theory, first articulated by Harvard Business School professor Amy Edmondson, who showed that teams learn and perform better when members can admit mistakes without penalty. This study extends that logic into the Indian IT and ITeS context, showing that the same interpersonal dynamics operate even in high-throughput, globally connected service environments.

The practical implications are significant for leaders and human resource professionals. If innovation is a strategic priority, the study suggests that organisations should invest in structured training before rolling out new technologies, stabilise communication during periods of change, and cultivate leadership styles that keep managers approachable. Recognition also matters: employees who see their contributions acknowledged are more likely to keep offering them. Human resource functions can embed these insights into onboarding, performance management, and leadership development, treating psychological safety not as a soft perk but as measurable infrastructure for innovation. For a sector that competes on its ability to absorb new technologies faster than its rivals, the message is that human confidence is as much a competitive asset as technical capability.

The study also makes a scholarly contribution by adding qualitative evidence from India to a literature dominated by quantitative Western studies. By capturing employees’ own accounts of what safety feels like in innovation settings, the research complements survey-based findings with texture and nuance, revealing how autonomy, change, technology, leadership, and feedback interweave in daily working life. The authors position the work as a resource for both researchers and practitioners seeking to create supportive work environments that encourage employee participation, learning, and innovation. As artificial intelligence reshapes the global services industry, understanding the human conditions under which employees embrace rather than resist change may prove decisive, and this study offers a grounded starting point for organisations across India’s technology sector and beyond.

Subject of Research: Psychological safety and workplace innovation among employees in Indian IT and ITeS organisations

Article Title: Exploring psychological safety and workplace innovation in Indian IT and ITeS organisations

Article References: Shanmuganathan, S., & G N, S. (2026). Exploring psychological safety and workplace innovation in Indian IT and ITeS organisations. Discover Psychology. https://doi.org/10.1007/s44202-026-00808-2

Image Credits: AI Generated

DOI: 10.1007/s44202-026-00808-2

Keywords: psychological safety, workplace innovation, Indian IT sector, ITeS, leadership, organisational support, qualitative research, hermeneutic phenomenology, employee empowerment, open feedback, training, Chennai and Bengaluru

The research, led by Azatullah Zaheer of Salam University in Kabul together with colleagues from Malaysia, Bangladesh, and the United Arab Emirates, surveyed 404 employees working in organizations in Kabul, Afghanistan, that have adopted generative AI tools. The choice of setting is significant. Most studies of workplace AI adoption have been conducted in wealthy economies with mature digital infrastructures, leaving a substantial gap in our understanding of how these technologies perform in developing contexts, where connectivity may be patchy, training resources scarce, and organizational support uneven. By focusing on Kabul, the team offers one of the first empirical windows into how generative AI reshapes productivity where digital transformation is still very much a work in progress.

The study rests on two well-established theoretical pillars. The first is Task–Technology Fit Theory, which holds that technology only improves performance when its capabilities match the demands of the tasks at hand. The second is Social Cognitive Theory, which emphasizes that human behavior is shaped by an interplay of personal capabilities, beliefs, and environmental factors. Combining these frameworks, the researchers conceptualized generative AI adoption not as a single yes-or-no variable but as a multidimensional construct with three distinct dimensions: frequency, meaning how often employees use AI tools; depth, meaning how intensively and sophisticatedly they integrate AI into their workflows; and purpose, meaning the range of tasks for which they deploy it.

To test the relationships among these dimensions, digital skills, AI trust, and productivity, the team employed structural equation modeling, a statistical technique that allows researchers to estimate networks of direct and indirect relationships among observed and latent variables simultaneously. This approach is particularly well suited to questions like the present one, where the pathway from technology adoption to productivity is unlikely to be a simple straight line. The researchers hypothesized that digital skills — the ability to operate, adapt, and troubleshoot digital tools — would act as a mediator, carrying the effect of AI adoption through to measurable productivity gains. They also tested whether trust in AI would moderate, or amplify, the entire chain of relationships.

The results delivered a clear verdict on the first two dimensions. Both the frequency and the depth of generative AI adoption were positively and significantly associated with employee productivity. In other words, workers who used AI tools more often, and who wove them more thoroughly into the fabric of their daily tasks, tended to report higher productivity. This aligns neatly with Task–Technology Fit Theory: the more a tool is used, and the more deeply it is matched to actual task demands, the more performance benefits it delivers. Interestingly, the third dimension — the purpose of AI adoption — showed no significant direct association with productivity. Simply using AI for a wider variety of tasks did not, by itself, translate into better outcomes, suggesting that breadth of use without frequency or depth may spread attention thin rather than compound gains.

The mediation findings may be the most consequential part of the study. Digital skills demonstrated significant indirect associations between generative AI adoption and employee productivity. In plain terms, AI adoption did not magically make workers more productive on its own; rather, its benefits flowed through the workers’ own capabilities. Employees with stronger digital skills were better positioned to convert their AI usage into tangible output, whether that meant crafting more effective prompts, verifying and refining machine-generated content, or integrating AI outputs into larger workflows. This finding reframes the popular narrative around AI and productivity: the technology is less a replacement for human skill than an amplifier of it, and the amplifier only works when there is a signal worth boosting.

Perhaps the most surprising result was the one that failed to materialize. The researchers hypothesized that trust in AI would moderate the relationship between adoption and productivity — that employees who trusted the technology would extract more value from it. The data did not support this. AI trust did not significantly moderate these relationships, a finding that cuts against a substantial body of adoption literature in which trust is treated as a gating factor for technology acceptance. The authors’ result hints that in the workplace context, what matters may not be whether employees emotionally trust AI but whether they possess the competence to use it well. Trust, in this framing, may be a prerequisite for adoption rather than a multiplier of its benefits — or it may simply matter less than skills once tools are already in daily use.

The practical implications reach well beyond Kabul. For managers contemplating generative AI rollouts, the study suggests that procurement alone is a poor strategy. Buying licenses and granting access addresses only the frequency dimension; without investment in training that builds depth of use and strengthens digital skills, organizations may see adoption statistics rise while productivity remains flat. The finding that purpose of use showed no direct effect adds a caution against broad, unfocused AI mandates. Instead, the evidence points toward targeted skill development: teaching employees not just how to operate AI tools but how to embed them deeply and appropriately into specific, recurring tasks where the technology’s strengths match the work’s demands.

The study also carries a developmental dimension. The authors explicitly connect their findings to the United Nations Sustainable Development Goals, particularly SDG 8 on decent work and economic growth and SDG 9 on industry, innovation, and infrastructure. In economies like Afghanistan’s, where formal employment is fragile and digital infrastructure is still maturing, the difference between AI as a productivity engine and AI as an expensive distraction could have outsized consequences. The research suggests that digital skills training may be among the highest-leverage interventions available, allowing workers in developing contexts to leapfrog into AI-augmented productivity rather than being left behind by a technological wave they cannot ride.

As with any cross-sectional survey, the study has limits that invite further work. Measuring adoption and productivity at a single point in time cannot establish causality with certainty, and self-reported productivity may diverge from objective output measures. The single-city sample, while valuable for illuminating an understudied context, raises questions about generalizability to other developing and developed settings alike. Still, the core message is likely to travel. Generative AI is not a productivity switch that organizations can simply flip. Its benefits are conditional — conditional on frequent use, conditional on deep integration, and above all conditional on the human skills that turn machine output into meaningful work. In the emerging economy of AI-augmented labor, it appears, the decisive investment is not in the machines but in the people who use them.

Subject of Research: The relationship between generative AI adoption dimensions, digital skills, AI trust, and employee productivity in developing-country workplaces

Article Title: Generative AI utilization and employee productivity through digital skills with the moderating role of AI trust

Article References: Generative AI utilization and employee productivity through digital skills with the moderating role of AI trust. (n.d.). https://doi.org/10.1007/s43621-026-04863-6

Image Credits: AI Generated

DOI: 10.1007/s43621-026-04863-6

Keywords: generative AI, employee productivity, digital skills, AI trust, workplace innovation, Task-Technology Fit Theory, Social Cognitive Theory, structural equation modeling, Afghanistan, developing economies, sustainable development, digital transformation