Introduction

In the modern workplace, the pursuit of higher employee motivation and productivity is more critical than ever. As organisations adapt to rapid technological changes and increasingly competitive environments, they are turning to innovative solutions that promise not only efficiency but also cognitive and emotional optimisation. One such frontier is neurotechnology—a field that integrates neuroscience with advanced technological tools such as brain–computer interfaces (BCIs) and neurofeedback to monitor and enhance brain activity.

While neurotechnology has historically been associated with clinical rehabilitation and assistive applications, its potential use in non-clinical settings such as corporate environments is gaining momentum. Employers are beginning to explore how tools that enhance focus, reduce stress or regulate emotions can lead to better employee engagement and improved decision-making. This shift aligns with the growing interest in organisational cognitive neuroscience, an emerging discipline that seeks to connect brain science with management and organisational behaviour.

Despite these exciting developments, the application of neurotechnology in the workplace remains a relatively underexplored area—both scientifically and ethically. Several critical questions emerge: Can neurotechnological interventions meaningfully improve motivation and performance? How do they align with established theories of human motivation and behaviour at work? What ethical boundaries must be respected when accessing an employee’s neural data? These questions become particularly relevant in knowledge-intensive industries where performance is closely tied to mental acuity and emotional resilience.

From a theoretical perspective, motivation and productivity have been extensively studied through models such as the self-determination theory (SDT), which emphasises autonomy, competence and relatedness, and the job demands-resources (JD-R) model, which focuses on how workplace demands and resources influence employee burnout and engagement. However, the intersection of these theories with neurotechnology remains poorly defined in the current literature.

This study aims to address this gap by conducting a systematic literature review (SLR) following PRISMA 2020 guidelines, examining how neurotechnology influences cognitive processes, motivation and productivity in professional settings. Beyond mapping existing evidence, the study seeks to critically evaluate the practical benefits, theoretical alignment and ethical concerns associated with using neurotechnology in the workplace. In doing so, it contributes to both scholarly discussion and practical decision-making for HR professionals, organisational leaders and policymakers.

Purpose of the Study

The primary aim of this study is to explore how neurotechnology can influence employee motivation and productivity. With workplaces becoming more data driven, understanding the impact of neurotechnological tools can help organisations develop evidence-based HR strategies that optimise employee well-being and performance. Additionally, this study seeks to identify ethical considerations and potential challenges in implementing neurotechnology in workplace settings.

Literature Review

This study employs a literature review of peer-reviewed articles and other credible online sources. A literature review allows for the exploration of diverse perspectives from multiple studies and authors, providing a broader and more comprehensive understanding of the subject. Conducting a literature review follows a structured process that includes selecting a topic, developing an argument, searching for relevant literature, surveying and analysing the literature, critiquing findings and, finally, writing the review. Literature reviews can take various forms, including narrative reviews, integrative reviews and systematic reviews. For this study, the SLR methodology was adopted, adhering to PRISMA 2020 guidelines. A comprehensive review of peer-reviewed journals, books and conference proceedings was conducted to analyse the relationship between neurotechnology, employee motivation and workplace productivity. Relevant data were systematically extracted, evaluated and synthesised to provide a well-rounded understanding of the topic. For this systematic search, a tailored search strategy was developed using databases such as Dimensions and Google Scholar. Keywords included: neuroscience, employee motivation, productivity, brain–computer interface and neurofeedback. The search spanned publications from 1996 to 2025, focusing exclusively on English-language studies conducted in Asian countries. Only original research articles, review papers and conference papers were included to ensure quality and relevance. Duplicates were removed, and articles were screened for relevance through abstract analysis. A PRISMA flow diagram (Figure 1) illustrates the inclusion and exclusion process.

 

Figure 1. PRISMA Flow Diagram.

Source: The authors.

 

The reviewed studies converge on three dominant themes: the cognitive enhancement potential of neurotechnology, its role in emotional self-regulation and its influence on employee engagement and productivity. For instance, Bonetti and Casoni (2024) and Ahmed and Muhammed (2021) demonstrate how neurofeedback and BCIs support attentional control and stress reduction—factors directly linked to improved work performance. These findings suggest that neurotechnology acts as a psychological resource that supports workplace productivity. However, the literature also presents contradictory findings and limitations. While some studies praise the efficacy of neurotechnology for boosting workplace focus and emotional regulation, others caution against overreliance, technostress or ethical blind spots (Traunwieser, 2025). The variability in outcomes across individual profiles and organisational contexts remains insufficiently addressed. Moreover, most existing studies lack methodological diversity, with very few longitudinal or experimental designs that could clarify causality and long-term impact.

Critically, the ethical dimension of neurotechnology in the workplace is often underdeveloped. Several scholars (e.g., Goering et al., 2017; Tindale et al., 2022) warn of serious implications regarding data privacy, autonomy and consent. Many reviewed studies fail to adequately explore the psychological effects of invasive monitoring, neuro-surveillance or pressure to conform to cognitive performance norms. These challenges signal a need for organisations to develop transparent governance frameworks before adoption. Finally, a major theoretical gap in the reviewed literature is the limited integration of foundational organisational behaviour (OB) theories. SDT, which emphasises autonomy, competence and relatedness (Deci & Ryan, 1985), offers an essential lens for evaluating how neurotechnology influences motivation. Similarly, the JD-R model (Bakker & Demerouti, 2007) could be used to assess whether neurotechnology serves as a resource or becomes an additional job demand. The reinforcement sensitivity theory (RST; Corr et al., 2016) also holds relevance, particularly when interpreting how neural feedback influences individual motivation patterns. Unfortunately, a few studies explicitly anchor their findings within these theoretical models, resulting in a disconnect between empirical findings and conceptual understanding.

The reviewed studies converge on the promise of neurotechnology but also highlight several contradictions. For instance, Ahmed and Muhammed (2021) and Bonetti and Casoni (2024) demonstrate that neurofeedback and BCIs can significantly improve attentional control and reduce workplace stress, thereby supporting employee engagement. Similarly, Miller et al. (2019) reported that EEG-based brain training interventions enhanced employees’ task performance and sustained focus in high-demand environments. These findings align with the growing interest in neurotechnology as a resource for boosting productivity. However, other scholars caution against uncritical optimism. Traunwieser (2025) points to the phenomenon of technostress, where constant cognitive monitoring may overwhelm workers and erode well-being. Goering et al. (2017) and Tindale et al. (2022) further highlight ethical blind spots, particularly concerning data privacy, informed consent and neuro-surveillance in organisational contexts.

Geographically, most existing studies originate from Asian workplaces, which tend to operate in high-intensity, hierarchical contexts where such technologies are often adopted as performance enablers. This regional concentration limits generalisability, as Western or African workplaces may frame adoption differently, emphasising employee autonomy and privacy. Another limitation is methodological: many studies are cross-sectional or exploratory, with very few longitudinal or experimental designs to establish causality or long-term effects. Finally, while neurotechnology is often described as a promising workplace intervention, empirical studies rarely compare its impact against other digital tools such as wellness apps or AI-driven monitoring, leaving gaps in understanding its relative value. These contradictions and gaps underscore the need for more rigorous, diverse and cross-cultural research designs.

In summary, while the literature supports the promising role of neurotechnology in enhancing motivation and productivity, it also reveals significant methodological, ethical and theoretical gaps. Future research must bridge these deficiencies by embracing interdisciplinary frameworks, ensuring rigorous ethical practices and grounding empirical inquiry in well-established OB theories.

Objectives of the Study

1. To examine the role of neurotechnology in enhancing employee motivation and engagement
2. To analyse how neurotechnological tools, such as BCIs and neurofeedback, impact cognitive functions related to productivity
3. To identify potential ethical and privacy concerns associated with using neurotechnology in the workplace
4. To provide recommendations for organisations looking to integrate neurotechnology into their employee management strategies

Theoretical Framework

Understanding how neurotechnology influences employee behaviour requires anchoring the analysis in both neuroscientific principles and OB theories. While neuroscience explains the biological underpinnings of attention, emotion and cognition, OB theories help contextualise how these functions impact work motivation and performance. At the neuroscience level, neurofeedback and BCIs are designed to monitor and train brain activity, improving an individual’s capacity for self-regulation, working memory and emotional control. These neurocognitive functions are closely linked to behaviours such as sustained attention, stress management and goal-directed thinking—all critical for workplace effectiveness. To understand how these biological enhancements influence behaviour at work, the following psychological and organisational theories are particularly relevant:

1. SDT, which posits that motivation is the highest when individuals feel autonomy, competence and relatedness. Neurotechnology may support competence by enhancing cognitive control and emotional stability, but its implementation must ensure that autonomy is not compromised through coercive or surveillance-based practices.
2. `JD-R model, which asserts that workplace performance is influenced by the balance between demands (e.g., workload, stress) and resources (e.g., support, tools). Neurotechnology can be seen as a resource that boosts psychological resilience and energy levels. However, it could also introduce new demands if misused or mandated without sufficient support.

Regarding the role of neurotechnology in the workplace, it is essential to anchor the discussion in established OB theories. SDT emphasises that motivation flourishes when employees experience autonomy, competence and relatedness (Deci & Ryan, 1985). Neurotechnology may enhance competence by strengthening focus and working memory, yet it risks undermining autonomy if adoption is mandated rather than voluntary. The JD-R model (Bakker & Demerouti, 2007) further clarifies this duality: neurotechnology can function as a resource by reducing stress and improving resilience, but if poorly managed, it may create new demands in the form of technostress or surveillance pressure. RST (Corr et al., 2016) provides an additional lens, explaining how neural feedback may differentially influence individuals depending on their sensitivity to rewards or punishments.

Beyond these core models, theories such as psychological safety (Edmondson, 1999) and equity theory (Colquitt & Zipay, 2015) are highly relevant. If employees perceive that neural data collection threatens psychological safety, they may withdraw rather than engage. Similarly, if organisations use neurodata in ways perceived as unfair or opaque, it can erode trust and motivation. Operationalisation of these theories is critical: competence may be measured through cognitive test improvements, autonomy via surveys assessing voluntariness, job resources through reductions in reported stress and fairness through employee trust ratings. Integrating these theories ensures a more holistic understanding of how neurotechnology influences not only individual motivation but also organisational outcomes (see Figure 2).

 

Figure 2. Neurotechnology in the Workplace: A Conceptual Framework.

Source: The authors.

 

Problem Statement

As organisations strive to enhance employee motivation and productivity in an increasingly complex and technology-driven world, attention has turned towards novel approaches that go beyond traditional HR practices. One such approach is the use of neurotechnology, including BCIs and neurofeedback systems, which aim to optimise brain functioning to improve focus, reduce stress and support cognitive performance. While the application of these tools has shown promise in clinical and therapeutic settings, their role in the workplace remains ambiguous. Preliminary studies suggest that neurotechnology can support attention regulation, emotional control and decision-making—all of which are vital components of workplace effectiveness. However, the long-term impact, sustainability and practical application of these technologies within organisational environments are still poorly understood. In addition to functional uncertainty, several ethical dilemmas arise: How should organisations handle employees’ neural data? What constitutes informed consent when using wearable neurotech devices? How can organisations ensure voluntary participation without pressuring employees to conform? These concerns become especially critical when such technologies are used in contexts where performance evaluation is tied to mental output. Moreover, there is a noticeable gap in integrating neurotechnological interventions with established motivational and OB theories, which limits the academic grounding and practical direction of existing literature. This lack of theoretical coherence weakens our understanding of how and why neurotechnology may (or may not) work in improving workforce outcomes. Therefore, this study seeks to explore and evaluate the role of neurotechnology in enhancing workplace motivation and productivity. By critically reviewing existing research through a structured SLR approach, it aims to offer insights into its practical relevance, ethical viability and theoretical alignment, while outlining the implications for future research and organisational practice.

Methodology

This study adopts an SLR methodology to synthesise the existing research on the role of neurotechnology in influencing employee motivation and workplace productivity. The review follows the PRISMA 2020 guidelines to ensure transparency, replicability and methodological rigour in the selection and evaluation of literature.

A comprehensive search was conducted using multiple electronic databases including Google Scholar and Dimensions supplemented by Scopus and Web of Science, which broadens the scope. The search was limited to peer-reviewed articles, review papers and conference proceedings published between 1996 and 2025, and only English-language studies were included. The geographical focus was restricted to Asia, given the growing interest and application of HR technology in this region.

Inclusion Criteria

The inclusion criteria were as follows: studies focused on the application of neurotechnology (e.g., BCIs, neurofeedback) in workplace or HRM contexts; empirical and conceptual papers related to motivation, productivity and cognitive performance; and articles published in credible academic journals or conferences.

Exclusion Criteria

Exclusion criteria included the following: studies related to clinical or medical applications of neurotechnology (e.g., treatment of neurological disorders), papers not published in English and duplicates and non-peer-reviewed content.

Screening Process

Out of 1,090 records identified, 82 duplicates were removed. After title and abstract screening, 763 full texts were assessed, leading to the inclusion of 15 studies that met all quality and relevance criteria. A PRISMA flow diagram was used to document the review process and ensure compliance with systematic review standards.

Data Extraction and Synthesis

Key data extracted from each selected study included: author(s), year, country, methodology, sample characteristics, neurotechnology type, key findings and theoretical lens (if any). A thematic synthesis approach was used to identify recurring patterns, contradictions and gaps in the literature. Studies were categorised by the type of neurotechnology, outcome variables (e.g., motivation, engagement, performance) and theoretical alignment.

Analysis

The distribution of publication types is illustrated in Figure 3. A trend analysis shows how research output has evolved over time (Refer to Figure 4).

 

Figure 3. Publication Types.

Source: The authors.

 

Figure 4. Year-wise Publication Trend Between 1996 and 2025.

Source: The authors.

 

Result and Discussion

This section presents a thematic synthesis of the 15 selected studies, focusing on three overarching dimensions: technological effectiveness, cognitive and behavioural outcomes, and ethical considerations. These themes help uncover both the promise and the complexity of neurotechnology in workplace settings.

Technological Effectiveness

The reviewed literature consistently highlights the potential of neurotechnological tools—particularly BCIs and neurofeedback devices—in enhancing employee focus, attention span and stress management (Ahmed & Muhammed, 2021; Miller et al., 2019). Such tools are increasingly being positioned as cognitive enablers that support improved performance in high-demand work environments. However, differences in the types of devices used, outcome measures and research settings pose challenges in making direct comparisons across studies.

Cognitive and Behavioural Outcomes

Neurotechnology appears to have a positive impact on emotional regulation, intrinsic motivation and task engagement. These effects align with theoretical constructs from SDT, which posits that psychological needs for competence and autonomy enhance motivation when fulfilled (Deci & Ryan, 1985). Similarly, the JD-R model offers a lens to understand how neurotechnology can function as a job resource to support well-being and performance. However, the literature also suggests that if such tools are imposed without employee consent or adequate support, they may inadvertently become sources of psychological strain or technostress.

Ethical and Practical Considerations

A critical concern across several studies involves ethical risks, especially in relation to data privacy, informed consent and employee autonomy (Tindale et al., 2022; Traunwieser, 2025). The possibility of employers using neurodata for surveillance or performance monitoring raises serious questions about workplace fairness and trust. Despite the prominence of these concerns, there is a noticeable lack of concrete ethical frameworks or implementation guidelines in the literature.

Gaps and Divergence in Research

The findings from the selected studies vary in terms of scope, methodology and contextual relevance. Most rely on exploratory or cross-sectional designs, with limited longitudinal or experimental research available. Theoretical integration also remains weak, with few studies explicitly grounding their work in established OB frameworks. Additionally, there is limited discussion on how organisational context—such as industry type or job nature—affects the applicability or outcomes of neurotechnology adoption.

In summary, while the reviewed studies demonstrate that neurotechnology has considerable potential to improve employee motivation and productivity, significant gaps remain in terms of methodological rigour, ethical clarity and theoretical alignment. These gaps must be addressed to support the responsible integration of neurotechnology in the workplace.

Conclusion

This study examined the influence of neurotechnology—specifically BCIs and neurofeedback tools—on employee motivation and workplace productivity. The findings indicate that these technologies can enhance focus, emotional stability and decision-making capabilities, which are critical for effective performance. However, these benefits are counterbalanced by ethical and organisational concerns, such as data privacy, autonomy and the risk of over-surveillance. Given these complexities, a cautious and well-informed approach is essential for integrating neurotechnology into modern HR practices.

Emerging Trends in Neurotechnology

Recent developments in workplace neurotechnology point towards significant emerging trends that are reshaping both research and practice. First, wearable EEG devices and portable BCIs are becoming increasingly affordable, moving beyond elite industries into mainstream organisational use. Companies are experimenting with headsets that measure attention and stress in real time, enabling more personalised feedback for employees. Second, AI–neurodata integration is gaining traction, where machine learning algorithms analyse brain signals to deliver individualised cognitive enhancement programs. This hybrid approach promises greater accuracy and adaptability but also raises unprecedented ethical concerns regarding data ownership and algorithmic bias.

Third, regulatory frameworks are evolving globally. The European Union’s Artificial Intelligence Act has begun to address high-risk applications, including neurotechnology, while OECD guidelines stress transparency and informed consent. These developments suggest that organisations must anticipate compliance obligations as adoption expands. Fourth, the mental health and well-being agenda is increasingly linked to neurotechnology. Post-pandemic, organisations are seeking innovative solutions to manage burnout, anxiety and focus in hybrid work environments, positioning neurotech as both an opportunity for resilience and a challenge for ethical governance. Finally, future-of-work dynamics, such as hybrid and remote working models, have amplified the demand for tools that monitor engagement, cognitive load and emotional balance. While these innovations suggest a promising trajectory, they also highlight the need for balanced approaches that align technological advancement with employee rights, ethical standards and cultural sensitivities.

Managerial Implications

To move beyond theoretical interest and towards responsible implementation, managers should adopt evidence-based and context-sensitive strategies:

1. Establish ethical governance frameworks: Create organisational policies that cover consent, data protection, usage boundaries and transparency. Reference best practices from bioethics and digital governance (Goering et al., 2017).
2. Develop training and awareness protocols: Train both managers and employees in the purpose, limitations and ethical considerations of neurotechnology to reduce fear, misunderstanding and misuse.
3. Customise implementation by industry type:
   • In knowledge-intensive sectors, where focus and emotional regulation are critical, technologies like neurofeedback may offer substantial ROI.
   • In labour-intensive or routine-task environments, simpler tools (e.g., fatigue-monitoring wearables) might be more appropriate.
4. Pilot programmes with voluntary participation: Roll out small-scale trials where employees opt in voluntarily. Evaluate impact using both quantitative metrics (e.g., productivity, attention scores) and qualitative feedback (e.g., user comfort, perceived benefit).
5. Encourage cross-disciplinary collaboration: Involve HR, legal, IT and occupational health experts to ensure well-rounded and compliant neurotech strategies.

These recommendations aim to help organisations ethically and effectively leverage the promise of neurotechnology while minimising potential harms.

Limitations of the Study

This study is limited by its reliance on secondary data and the scope of its literature review. The geographic focus on Asian contexts may limit the generalisability of findings to other regions. Furthermore, clinical applications of neurotechnology and its potential uses in creative or artistic job roles were excluded from the review. The study also does not address the differential effects of neurotechnology on individual versus team-level outcomes, nor does it assess variations across demographic groups.

Scope of Future Research

To advance the understanding and practical applications of neurotechnology in organisational contexts, future research should focus on the following areas:

1. Experimental and longitudinal studies: There is a need for well-designed experiments that assess the causal effects of neurofeedback or BCIs on workplace behaviour and motivation over time.
2. Multi-level and sector-specific analysis: Research should examine how neurotechnology affects employees at individual, team and organisational levels and how these outcomes differ across industries such as healthcare, manufacturing, education and IT.
3. Integration with OB theories: Future studies should embed neurotechnology research within established OB frameworks such as SDT, JD-R or RST, to better explain motivational outcomes and guide practice.
4. Ethical and regulatory exploration: More research is needed to develop ethical models and policy guidelines that can inform safe and inclusive implementation. Particular attention should be given to the challenges of informed consent, equity and surveillance.

By addressing these gaps, future research can contribute to a more nuanced and responsible understanding of how neurotechnology can shape the future of work.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

ORCID iDs

Triptii Shelkke  https://orcid.org/0009-0006-0574-9792

Divya Rahul Jain  https://orcid.org/0000-0002-1595-489X