AI service robots in physical retail: Can they reduce the intrusiveness of human retail assistants and prevent shoppers from leaving the store early?
https://doi.org/10.1016/j.jbusres.2026.116244
Authors #Choi, W., Lee, H., & Ki, C.*
Publication Year 2026
Journal Journal of Business Research
DOI 10.1016/j.jbusres.2026.116244
Keywords
AI service,Service robots, AI robots; Retail service; In store technology
Abstract
Although in-store shopping has traditionally been viewed as enjoyable, recent industry reports suggest a contrasting reality: consumers increasingly describe it as socially taxing and psychologically stressful. Our preliminary study empirically supports this observation, demonstrating that consumers frequently experience stress—particularly perceived intrusiveness—in physical retail environments during interactions with human retail assistants (HRAs). Importantly, our findings further indicate that this sense of intrusiveness is largely driven by perceived judgment, which in turn triggers emotion-focused coping responses (prematurely leaving the store). Building on these preliminary findings and drawing on Transactional Stress Theory, we conducted five experimental studies in fashion and skincare retail contexts to examine whether artificial intelligence retail assistants (AIRAs) can disrupt this stress process and serve as a more comfortable alternative to HRAs: retail assistant type (HRA vs. AIRA) → perceived judgment → perceived intrusiveness → emotion-focused coping (premature store departure). We also investigated whether service design cues (the presence vs. absence of smile) and consumers’ shopping goal clarity (low vs. high) function as boundary conditions within the proposed serial mechanism. Across five studies, the findings consistently support the proposed serial mediation effect (H2), as well as a direct effect of retail assistant type on store departure (H1). Moreover, the results reveal significant moderated mediation effects involving retail assistants’ smiling behavior (H3) and consumers’ shopping goal clarity (H4). Taken together, these findings suggest that AIRAs can alleviate an often-overlooked source of stress in physical retail environments—namely, the social-evaluative judgment and perceived intrusiveness embedded in human service interactions. These findings offer important implications for both theory and practice.
Introduction
“Shoppers don’t want human contact.” This headline captures a growing tension in contemporary brick-and-mortar retail (Dasilva, 2025). Although in-store shopping has traditionally been viewed as enjoyable, experiential, and even therapeutic (Seekis et al., 2025), many consumers now describe it as socially taxing and psychologically stressful (Albrecht et al., 2017). Ironically, one of the primary sources of this stress appears to be the very individuals who are supposed to enhance the shopping experience: retail associates (Morine, 2025, Ryan, 2021). Numerous industry reports echo this observation, indicating that many consumers perceive interactions with sales associates as intrusive—and, consequently, stressful (Lloyd-Wallis, 2020, Poole, 2015).
Intrusiveness refers to the perception that a retail associate’s behavior is interfering, interruptive, or overly involved (Smink et al., 2020, Yang et al., 2025). Practitioners suggest that such perceptions are especially common when associates approach shoppers as soon as they enter, repeatedly offer help, or provide detailed product information before the consumer has formed clear purchase intentions (Han, 2018). When shoppers lack well-defined shopping goals, unsolicited assistance can even intensify feelings of intrusion (Albrecht et al., 2017). As these feelings of intrusiveness develop, practitioners have observed that consumers often attempt to alleviate their discomfort by distancing themselves from the interaction (Poole, 2015). In retail settings, such distancing may take the form of minimizing engagement, reducing time spent in the store, or leaving before fully exploring available products. These avoidance responses pose a substantial challenge for retailers, as they constrain customer involvement, limit in-store dwell time, and ultimately lower purchase likelihood.
The consequences may extend beyond these immediate in–store behaviors. When consumers repeatedly encounter interactions they perceive as intrusive, those experiences can gradually influence how they think about in–store assistance overall. For instance, continued exposure to unwanted interpersonal engagement may lead shoppers to rethink what qualifies as “good service.” Rather than valuing proactive, attentive, or overly persistent assistance, they may come to prefer service that protects their autonomy and minimizes social pressure. This shift is likely intertwined with broader changes in the retail environment. As retail evolves from purely physical stores to a blend of online and omnichannel models (Grewal et al., 2025), consumers have become accustomed to self-directed, technology-mediated shopping experiences. For example, online shopping has normalized private browsing, self-paced decision-making, and quiet shopping, often supported by virtual assistants when needed (Xue et al., 2026). As these norms become internalized, consumers may carry similar expectations into physical stores; consequently, unsolicited interaction in these settings may feel more intrusive.
Given these evolving expectations, a critical question arises for brick-and-mortar retailers: Can technology-enabled service agents—specifically AI retail assistants (AIRAs)—mitigate the psychological strain caused by human retail assistants (HRAs) and offer a less intrusive alternative? AIRAs, such as Pepper—a commercially deployed humanoid social robot—are AI-enabled, embodied service agents designed to interact with customers, provide information, and assist with retail tasks in physical store environments, while minimizing the interpersonal and evaluative cues typically associated with human employees (Lee & Yi, 2025). Emerging research suggests that consumers perceive AI agents (e.g., AI robots) as more competent, efficient, and socially neutral—less judgmental and more impartial—compared to human associates (Yang & Sundar, 2024). If feelings of intrusion are primarily driven by concerns about judgment, rather than just surveillance or pressure (as indicated in industry reports), replacing human interactions with AI assistance could be more effective in reducing these stress responses. However, this possibility has yet to be rigorously tested.
To fill this important gap in understanding, academic research needs to first confirm whether interactions with HRAs indeed elicit consumer stress, particularly in the form of perceived intrusiveness, as suggested by industry reports. Beyond merely validating this phenomenon, it is essential to theorize and test the psychological mechanisms behind these perceptions. Specifically, what key factors (e.g., perceived judgment) drive consumers to appraise in-store HRA interactions as intrusive? Furthermore, how do consumers cope with these stressful, intrusive encounters? Do they engage in emotion-focused coping strategies (e.g., leaving the store early to alleviate stress) or in problem-focused coping strategies (e.g., confronting HRAs and requesting that they stop interfering)? Without a comprehensive understanding of both the psychological drivers and coping mechanisms associated with perceived intrusiveness, academic research may lack a coherent theoretical framework and, consequently, be unable to guide retailers in designing strategies that reduce consumers’ in-store psychological strain while also improving retail performance.
Once the underlying psychological drivers and coping mechanisms behind perceived intrusiveness are identified, the next logical step is to test whether replacing HRAs with AIRAs can effectively reduce these stress responses and mitigate negative outcomes (e.g., premature store departure). However, the relative effectiveness of AIRAs versus HRAs is unlikely to be uniform. Rather, it may depend on boundary conditions at both the contextual and individual levels. For example, service design cues (e.g., the presence vs. absence of a retail associate’s smile) and consumers’ shopping goal clarity (e.g., low vs. high purchase intention) may shape how assistance is appraised and, consequently, how intrusive it feels. Therefore, to gain a deeper understanding of these dynamics, academic research should examine how these boundary conditions moderate the relationship between retail assistant type (HRAs vs. AIRAs) and consumers’ stress responses.
Our research aims to address these critical gaps by investigating the following questions:
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Do interactions with HRAs in physical retail stores elicit consumer perceptions of intrusiveness? If so, what psychological factors (e.g., perceived judgment) contribute to feelings of intrusiveness, and how do consumers cope with this discomfort (e.g., by leaving the store prematurely)?
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Can AIRAs reduce HRA-induced perceptions of judgment, intrusiveness, and premature store departure, thus positioning them as a more effective alternative for improving the in-store shopping experience?
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How do design or individual factors—retailers’ service design (e.g., absence vs. presence of a smile) and consumers’ shopping goal clarity (e.g., low vs. high)—shape these experiences and potentially moderate the effects of HRAs versus AIRAs?
This study draws on the transactional theory of stress and coping (Lazarus, 1984) to address these questions in a theoretically grounded manner. Before introducing the theory, we review prior research on AIRAs to clarify what has been examined—and, more importantly, what remains underexplored—thereby positioning our research within the broader literature on technology-enabled service interactions.
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AI service robots in physical retail: Can they reduce the intrusiveness of human retail assistants and prevent shoppers from leaving the store early?
https://doi.org/10.1016/j.jbusres.2026.116244
Authors #Choi, W., Lee, H., & Ki, C.*
Publication Year 2026
Journal Journal of Business Research
DOI 10.1016/j.jbusres.2026.116244
Keywords
AI service,Service robots, AI robots; Retail service; In store technology
Abstract
Introduction
“Shoppers don’t want human contact.” This headline captures a growing tension in contemporary brick-and-mortar retail (Dasilva, 2025). Although in-store shopping has traditionally been viewed as enjoyable, experiential, and even therapeutic (Seekis et al., 2025), many consumers now describe it as socially taxing and psychologically stressful (Albrecht et al., 2017). Ironically, one of the primary sources of this stress appears to be the very individuals who are supposed to enhance the shopping experience: retail associates (Morine, 2025, Ryan, 2021). Numerous industry reports echo this observation, indicating that many consumers perceive interactions with sales associates as intrusive—and, consequently, stressful (Lloyd-Wallis, 2020, Poole, 2015).
Intrusiveness refers to the perception that a retail associate’s behavior is interfering, interruptive, or overly involved (Smink et al., 2020, Yang et al., 2025). Practitioners suggest that such perceptions are especially common when associates approach shoppers as soon as they enter, repeatedly offer help, or provide detailed product information before the consumer has formed clear purchase intentions (Han, 2018). When shoppers lack well-defined shopping goals, unsolicited assistance can even intensify feelings of intrusion (Albrecht et al., 2017). As these feelings of intrusiveness develop, practitioners have observed that consumers often attempt to alleviate their discomfort by distancing themselves from the interaction (Poole, 2015). In retail settings, such distancing may take the form of minimizing engagement, reducing time spent in the store, or leaving before fully exploring available products. These avoidance responses pose a substantial challenge for retailers, as they constrain customer involvement, limit in-store dwell time, and ultimately lower purchase likelihood.
The consequences may extend beyond these immediate in–store behaviors. When consumers repeatedly encounter interactions they perceive as intrusive, those experiences can gradually influence how they think about in–store assistance overall. For instance, continued exposure to unwanted interpersonal engagement may lead shoppers to rethink what qualifies as “good service.” Rather than valuing proactive, attentive, or overly persistent assistance, they may come to prefer service that protects their autonomy and minimizes social pressure. This shift is likely intertwined with broader changes in the retail environment. As retail evolves from purely physical stores to a blend of online and omnichannel models (Grewal et al., 2025), consumers have become accustomed to self-directed, technology-mediated shopping experiences. For example, online shopping has normalized private browsing, self-paced decision-making, and quiet shopping, often supported by virtual assistants when needed (Xue et al., 2026). As these norms become internalized, consumers may carry similar expectations into physical stores; consequently, unsolicited interaction in these settings may feel more intrusive.
Given these evolving expectations, a critical question arises for brick-and-mortar retailers: Can technology-enabled service agents—specifically AI retail assistants (AIRAs)—mitigate the psychological strain caused by human retail assistants (HRAs) and offer a less intrusive alternative? AIRAs, such as Pepper—a commercially deployed humanoid social robot—are AI-enabled, embodied service agents designed to interact with customers, provide information, and assist with retail tasks in physical store environments, while minimizing the interpersonal and evaluative cues typically associated with human employees (Lee & Yi, 2025). Emerging research suggests that consumers perceive AI agents (e.g., AI robots) as more competent, efficient, and socially neutral—less judgmental and more impartial—compared to human associates (Yang & Sundar, 2024). If feelings of intrusion are primarily driven by concerns about judgment, rather than just surveillance or pressure (as indicated in industry reports), replacing human interactions with AI assistance could be more effective in reducing these stress responses. However, this possibility has yet to be rigorously tested.
To fill this important gap in understanding, academic research needs to first confirm whether interactions with HRAs indeed elicit consumer stress, particularly in the form of perceived intrusiveness, as suggested by industry reports. Beyond merely validating this phenomenon, it is essential to theorize and test the psychological mechanisms behind these perceptions. Specifically, what key factors (e.g., perceived judgment) drive consumers to appraise in-store HRA interactions as intrusive? Furthermore, how do consumers cope with these stressful, intrusive encounters? Do they engage in emotion-focused coping strategies (e.g., leaving the store early to alleviate stress) or in problem-focused coping strategies (e.g., confronting HRAs and requesting that they stop interfering)? Without a comprehensive understanding of both the psychological drivers and coping mechanisms associated with perceived intrusiveness, academic research may lack a coherent theoretical framework and, consequently, be unable to guide retailers in designing strategies that reduce consumers’ in-store psychological strain while also improving retail performance.
Once the underlying psychological drivers and coping mechanisms behind perceived intrusiveness are identified, the next logical step is to test whether replacing HRAs with AIRAs can effectively reduce these stress responses and mitigate negative outcomes (e.g., premature store departure). However, the relative effectiveness of AIRAs versus HRAs is unlikely to be uniform. Rather, it may depend on boundary conditions at both the contextual and individual levels. For example, service design cues (e.g., the presence vs. absence of a retail associate’s smile) and consumers’ shopping goal clarity (e.g., low vs. high purchase intention) may shape how assistance is appraised and, consequently, how intrusive it feels. Therefore, to gain a deeper understanding of these dynamics, academic research should examine how these boundary conditions moderate the relationship between retail assistant type (HRAs vs. AIRAs) and consumers’ stress responses.
Our research aims to address these critical gaps by investigating the following questions:
This study draws on the transactional theory of stress and coping (Lazarus, 1984) to address these questions in a theoretically grounded manner. Before introducing the theory, we review prior research on AIRAs to clarify what has been examined—and, more importantly, what remains underexplored—thereby positioning our research within the broader literature on technology-enabled service interactions.
Read Article