As organizations rush to adopt Generative AI to boost productivity, a silent threat is emerging in the workplace.A groundbreaking study published in the Journal of Service Management reveals that when employees collaborate with AI, they frequently fall into the trap of AI complacency—the tendency to intentionally neglect verifying AI-generated output, even when it contains systematic errors.And here is the kicker: It has nothing to do with how tech-savvy or experienced your employees are.

This paper explores the potential emergence of an economy driven by autonomous AI agents capable of executing complex tasks with minimal human supervision. The authors examine how these digital entities might function as consumers and producers, potentially leading to market collusion or a decoupling of prices from true human preferences. They suggest that AI could drastically alter firm structures by reducing coordination costs, though this may also introduce systemic fragility through correlated errors. To manage these risks, the text argues for the creation of new digital institutions and legal frameworks to handle agent identity and accountability. Ultimately, the researchers call for a distinct economic theory to address the "alignment problem," ensuring that autonomous systems remain beneficial to human society.

This article by Seidl, Ma, and Splitter examines the concept of strategy-as-practice by addressing the fundamental ambiguity regarding what makes an activity "strategic." The authors propose a new framework that categorises strategic activities into four distinct perspectives: those with significant consequences, those formally labelled as strategy, those performed by recognised strategists, and those constituting a recurrent pattern of action. Each viewpoint introduces unique research questions, ranging from how specific outcomes are produced to how professional identities are constructed. By differentiating these views, the researchers aim to integrate strategy-as-practice with broader management theories such as managerial cognition and dynamic capabilities. Ultimately, this framework provides a structured approach for scholars to expand the boundaries of strategic management and develop more cumulative knowledge. This multidimensional perspective ensures that the field captures the full complexity of how strategy is actually performed within organisations.

This academic article proposes a significant ontological shift in how we understand artificial intelligence, moving away from viewing it as a standalone entity or autonomous agent. The authors argue that AI is more accurately defined as an organizing capability that is fundamentally connective, codependent, and emergent. Rather than residing solely within software, this capability arises through the complex system of relations between human participants and learning algorithms. By focusing on these human-algorithm relations, the research highlights how organizational tasks like analysing, learning, and acting are collectively produced rather than pre-programmed. Ultimately, this perspective suggests that AI is a doing and becoming process that reconfigures organizational structures, power dynamics, and intelligence.

This National Bureau of Economic Research paper investigates the productivity impact of generative AI on software development by tracking three generations of coding tools. The authors analyse data from over 100,000 GitHub developers to compare simple autocomplete features, interactive sync agents, and autonomous async agents. While these tools dramatically increase task-level activity, such as code volume and commit frequency, the study reveals that these gains diminish significantly as they move toward final output. This attenuation is attributed to a "weak-link" effect, where human bottlenecks in code review and project management limit the overall speed of software releases. Finally, the research finds that while AI has increased the supply of new applications in digital marketplaces, there has been no corresponding increase in total user engagement.

The future of customer experience is no longer just conversational—it’s deeply vocal. 🎙️Many organizations still rely on robotic, inflexible Interactive Voice Response (IVR) systems that frustrate customers. While digital assistants like Siri or Alexa set the stage for basic voice interaction, modern service organizations need to aim much higher

This research investigate the psychological and social effects of integrating artificial intelligence into collaborative work teams. Through three empirical studies, the authors explore how an AI teammate's social presence influences a person's motivation to contribute to collective tasks. The results indicate that while people initially perceive AI as having less presence than humans, this gap can be narrowed by increasing the transparency and familiarity of the system. Crucially, the studies reveal that social presence does not always drive productivity directly; instead, it works by fostering a willingness to depend on others and a sense of team-oriented commitment. Ultimately, the findings suggest that successful human–AI collaboration relies less on making robots look human and more on building interpersonal trust and clear operational understanding.

This academic editorial from the Journal of Management Studies examines the profound ways artificial intelligence is currently reshaping work, leadership, and institutional structures. The authors argue that scholarly research must move beyond treating AI as a single tool, proposing instead a heuristic framework that distinguishes between predictive, generative, agentic, and embodied systems. By categorising these different modes, the text clarifies how specific technologies alter core organisational concepts such as expert authority, decision-making, and professional identity. The collection explores the human-AI relationship, highlighting tensions between algorithmic efficiency and human judgment alongside the risks of occupational displacement. Ultimately, the sources set a comprehensive research agenda to address the governance, ethics, and shifting power dynamics defined by this rapid technological acceleration. Throughout the analysis, the writers emphasise that AI acts as an active participant in organisational life rather than a passive instrument.

We've all seen AI fail in customer service. But how should your AI system apologize to actually repair trust?Recent research on "AI Apology" highlights that as we deploy more customer-facing AI—from support chatbots to hospitality robots—we must intentionally design how they recover from mistakes.

A poorly designed apology can severely damage the user's perception of your system, while a good one makes the AI seem more trustworthy and easy to work with.If you are building or adopting AI for customer interactions, here is a practical, research-backed framework for designing effective AI apologies.

This research examines how generative artificial intelligence (GenAI) acts as an agentic force that transforms service systems through its interaction with human actors. By moving beyond the view of technology as a passive tool, the authors introduce the concept of human–GenAI hybrids that co-create hybrid intelligence and alter traditional task delegation.

The paper identifies two unique GenAI capabilities, autoreflexivity and autoreformation, which allow these hybrids to recognise and intentionally reshape the institutional arrangements governing service exchanges.

These dynamics influence the mechanisms of transformation, leading to more frequent and rapid phase transitions within service ecosystems. Ultimately, the study challenges human-centric assumptions in service design by positioning GenAI as an active contributor to systemic change and market evolution.