Stakeholder engagement with AI service interactions
Terrence Chong, Ting Yu, Debbie Isobel Keeling, Ko de Ruyter, Tim Hilken
kHUB post date: January 2026
Originally published: April 7, 2025 (PDMA JPIM • Vol 43, Issue 1 • January 2026)
Read time: 60 minutes
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Recent advancements in artificial intelligence (AI) have ushered in a wave of AI innovations in the form of embodied conversational agents. These stakeholders offer new ways to engage customers in the co-creation of services but still face significant customer skepticism. To address this challenge, we frame interactions between customers and embodied conversational agents through the lens of stakeholder engagement and apply the concept of proxy agency from social cognitive theory. This framework allows us to identify two primary stakeholder roles for embodied conversational agents: partner and servant. We conceptualize how these roles inform optimal design for embodied conversational agents and shape a two-stage value-by-proxy process, comprising proxy efficacy and outcome expectancy. Additionally, we uncover tensions within this process due to over-reliance on AI, as well as significant outcomes that extend beyond the immediate interaction. Our study, using a custom-developed embodied conversational agent with a sample of 596 U.S.-based respondents, reveals that positioning an embodied conversational agent in a partner role, combined with a human (vs. robot) appearance and emotional (vs. functional) conversation style, has the strongest positive impact on perceived value-by-proxy, usage and advice implementation intentions, and willingness to pay. We also observe an inverted U-shaped moderation by reliance in the relationship between proxy efficacy and outcome expectancy, signaling the potential risks of over-reliance on AI. Furthermore, we provide qualitative insights into why some customers avoid engaging with embodied conversational agents. Overall, we offer a nuanced perspective on embodied conversational agents as active stakeholders within organizational systems, advancing both theoretical understanding and practical applications of this rapidly evolving technology.
Practitioner Points
- Managers should align the design of an embodied conversational agent with its intended role—whether as a servant (task automation) or partner (collaborative engagement)—to enhance stakeholder engagement in complex service interactions. Real-time analysis of customer speech can help dynamically adjust the embodied conversational agent's role and interaction style.
- Customers' trust in an embodied conversational agent's capabilities influences adoption. To foster confidence, managers should ensure the embodied conversational agent demonstrates clear benefits—such as responsiveness, reliability, and contextual awareness—while addressing concerns through education and testimonials.
- While an embodied conversational agent can support self-regulatory skills, managers should be mindful of potential over-reliance. Designing the embodied conversational agent to prompt independent decision-making at key moments, integrating interactive learning (e.g., quizzes), and incorporating feedback loops can help reinforce customer autonomy.
- Encouraging customers to reflect on when and how they would use an embodied conversational agent can improve engagement. Managers can use this approach to monitor adoption, refine pricing strategies (e.g., subscription vs. pay-per-use), and optimize value propositions for different customer segments.