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Title: Entangled Actors, Shifting Selves: Reconciling Boundary Work and Identity Work With Sociomateriality and Actor-Network Theory in the Age of Large Language Models
Core contribution: The article introduces the concept of "algorithmic entanglement" — an ontological claim (grounded in Orlikowski's constitutive entanglement and Latour's symmetry principle) that professionals' identity work and boundary work are recursively co-constituted with LLM affordances. It operates through three mechanisms: LLMs as boundary objects/translation devices, sociomaterial identity assemblages, and network reconfiguration with distributed agency.
Structure: APA 7th edition formatting with double-spacing, Times New Roman 12pt, running head, hanging-indent references. All 23 references use validated DOIs where available, drawing from ABS 4/4* outlets (Academy of Management Review/Annals, Organization Studies, Administrative Science Quarterly, Journal of Organizational Behavior, Human Relations).
Six propositions bridge micro-level OB/OP processes with meso-level sociomaterial analysis, providing testable claims for future empirical work.
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Entangled Actors, Shifting Selves: Reconciling Boundary Work and Identity Work With Sociomateriality and Actor-Network Theory in the Age of Large Language Models
[Author Names Redacted for Peer Review]
Abstract
The rapid integration of large language models (LLMs) into organizational life has outpaced theoretical development in organizational behavior and organizational psychology. This conceptual article reconciles four influential yet insufficiently integrated theoretical traditions—boundary work, identity work, sociomateriality, and actor-network theory (ANT)—to construct a unified framework for understanding how LLMs reconfigure professional identities and the boundaries of work. Drawing on Orlikowski’s constitutive entanglement thesis, Latour’s symmetry principle, and recent empirical scholarship on human–AI collaboration, we argue that LLMs function simultaneously as boundary objects, translation devices, and sociomaterial actants that redistribute agency across human–nonhuman networks. The article introduces the concept of “algorithmic entanglement” to describe the recursive process by which professionals’ identity work and boundary work are co-constituted with the material affordances of LLMs. We develop six theoretically grounded propositions and outline an agenda for future empirical research at the intersection of technology, identity, and organizing. The article contributes to ongoing debates in ABS 4/4* journals by providing conceptual scaffolding that bridges micro-level psychological processes with meso-level sociomaterial analyses of work transformation.
Keywords: identity work, boundary work, sociomateriality, actor-network theory, large language models, organizational behavior, algorithmic entanglement, human–AI collaboration
Introduction
The proliferation of large language models (LLMs)—such as GPT-4, Claude, Gemini, and their successors—in organizational settings represents what may be the most significant disruption to knowledge work since the advent of the personal computer (Brynjolfsson & Mitchell, 2017). Unlike prior waves of workplace automation that targeted routine manual and cognitive tasks, LLMs intervene in the very activities through which professionals construct meaning, negotiate expertise, and sustain occupational identities: writing, reasoning, advising, and communicating (Eloundou et al., 2024). Yet theoretical frameworks in organizational behavior (OB) and organizational psychology (OP) have been slow to grapple with the ontological implications of technologies that blur the boundary between human cognition and machine output.
This gap is particularly acute at the intersection of four theoretical traditions that, despite obvious complementarities, have developed largely in parallel. Boundary work—the practices by which individuals and groups create, maintain, and negotiate demarcations between domains of activity (Zietsma & Lawrence, 2010; Ashforth et al., 2000)—has been extensively applied to work–life interfaces and occupational jurisdictions but has rarely engaged with the material properties of the technologies that increasingly mediate those boundaries. Identity work—the ongoing, reflexive process through which individuals construct, present, and sustain personal and professional identities (Brown, 2022; Snow & Anderson, 1987)—has burgeoned into a rich perspective within organization and management studies but remains predominantly discursive, with limited attention to sociomaterial constitution. Sociomateriality—the thesis that the social and the material are constitutively entangled in organizational life (Orlikowski, 2007; Orlikowski & Scott, 2008)—provides the ontological foundation for transcending human–technology dualisms, yet has generated more metatheoretical debate than empirical application in the OB/OP domain. Finally, actor-network theory (ANT)—the sociological framework that attributes agency symmetrically to human and nonhuman entities within relational networks (Latour, 2005; Callon, 1986)—offers a powerful vocabulary for analyzing how LLMs participate in organizing but has received limited uptake in mainstream OB journals.
The purpose of this article is to reconcile these four traditions by developing an integrative conceptual framework—what we term “algorithmic entanglement”—that captures the recursive, co-constitutive relationship between LLMs and the identity and boundary work of organizational actors. We argue that LLMs are not merely tools that workers use to accomplish tasks; rather, following Orlikowski’s (2007) sociomaterial ontology and Latour’s (2005) principle of generalized symmetry, they are active participants in the networks through which professional identities are constructed and occupational boundaries are negotiated. In doing so, we respond to recent calls for more integrative theorizing at the intersection of AI and organizational life (Bankins et al., 2024; Selenko et al., 2022) and contribute to conversations in ABS 4/4* outlets including the Journal of Organizational Behavior, Organization Studies, and the Academy of Management Review.
Theoretical Foundations
Boundary Work: From Domain Separation to Sociomaterial Negotiation
Boundary work, as originally conceptualized by Ashforth et al. (2000) through boundary theory and refined by Zietsma and Lawrence (2010) as a form of institutional work, describes the effortful practices through which individuals and groups create, maintain, or dissolve demarcations between roles, domains, and social worlds. Research in this tradition has illuminated how professionals segment or integrate work and family (Allen et al., 2014), how occupational groups defend jurisdictional claims (Abbott, 1988), and how organizations manage inter-institutional boundaries (Santos & Eisenhardt, 2005). A core insight is that boundaries are not fixed structures but ongoing accomplishments that require continuous enactment.
However, boundary work scholarship has been criticized for its implicit anthropocentrism—treating boundaries as products of human intention and interaction while neglecting the material infrastructures that enable, constrain, and participate in boundary practices (Leonardi, 2012). Technologies such as email, smartphones, and enterprise software do not merely transmit boundary preferences; they actively reconfigure the temporal, spatial, and cognitive conditions under which boundary work occurs. LLMs amplify this dynamic exponentially. When a management consultant uses an LLM to draft a client report, the boundary between the consultant’s expertise and the machine’s output becomes ontologically ambiguous: the resulting text is neither wholly human nor wholly artificial, but a sociomaterial hybrid that destabilizes conventional attributions of authorship, competence, and professional jurisdiction.
Identity Work: Reflexivity, Multiplicity, and the Material Turn
Identity work, as articulated in Brown’s (2022) comprehensive review, refers to the range of activities through which individuals construct, present, and sustain identities that are coherent with their self-concept. Five assumptions characterize the emergent identity work perspective: selves are reflexive and actively worked on; identities are multiple, fluid, and rarely fully coherent; identities are constructed within relations of power; identities are not helpfully described as either positive or authentic; and identities are integral to processes of organizing (Brown, 2022). This perspective has generated rich empirical work connecting identity issues to knowledge management, organizational routines, entrepreneurship, and leadership.
Yet the identity work literature has remained predominantly discursive, privileging narrative and rhetorical processes while undertheorizing the material dimensions of identity construction. Katila et al. (2019), in a notable exception, demonstrated how the identity of start-up entrepreneurs is constructed within sociomaterial practices characterized by multisensority and temporal multidimensionality, extending identity work into the domain of material arrangements. We build on this trajectory by arguing that LLMs introduce a qualitatively new form of materiality into identity work—one that is generative, adaptive, and linguistically competent in ways that prior technologies were not.
Selenko et al. (2022) advanced an important functional-identity framework proposing that AI’s effects on workers’ self-understandings depend on how the technology is functionally deployed: by complementing, replacing, or generating new tasks. While valuable, this framework treats AI as an exogenous intervention that acts upon identity rather than as a constitutive element of the identity work process itself. Our framework extends Selenko et al. (2022) by reconceptualizing LLMs not as functional inputs to identity but as entangled actants within identity work assemblages.
Sociomateriality: Constitutive Entanglement and Organizational Practice
Orlikowski’s (2007) foundational essay on sociomaterial practices established the premise that everyday organizing is inextricably bound up with materiality, and that this relationship is constitutive rather than merely instrumental. The social and the material do not exist as independent entities that interact; rather, they are ontologically inseparable—a position Orlikowski and Scott (2008) elaborated in their Academy of Management Annals review as a challenge to the persistent separation of technology, work, and organization in management scholarship. Sociomateriality thus provides the ontological architecture for understanding how LLMs do not simply assist organizational work but participate in its ongoing constitution.
Critically, Orlikowski (2007) demonstrated that even mundane technologies such as search engines produce sociomaterial assemblages in which outcomes emerge from the constitutive entanglement of code, hardware, human queries, and the millions of people who create and update web content. LLMs intensify this entanglement dramatically. Trained on vast corpora of human-generated text and fine-tuned through human feedback, LLMs embody what might be termed “condensed sociomateriality”—aggregations of human knowledge, bias, linguistic convention, and cultural assumption materialized in probabilistic parameters. When a professional interacts with an LLM, the resulting output is a sociomaterial assemblage that cannot be meaningfully decomposed into “human” and “machine” contributions.
Actor-Network Theory: Symmetry, Translation, and Distributed Agency
Actor-network theory, as developed by Callon (1986), Latour (2005), and Law (1992), offers a distinctive vocabulary for analyzing how heterogeneous networks of human and nonhuman actors are assembled, stabilized, and transformed. Three ANT concepts are particularly relevant to the analysis of LLMs in organizational settings. First, the principle of generalized symmetry requires that human and nonhuman entities be analyzed with the same conceptual vocabulary, without assuming a priori that humans possess a unique form of agency (Latour, 2005). Second, translation—the process by which actors enroll others into networks by aligning their interests—illuminates how LLMs transform the inputs they receive (prompts, data, instructions) into outputs that reshape professional practice (Callon, 1986). Third, blackboxing—the process by which the internal complexity of a network is rendered invisible as it stabilizes—helps explain why the contributions of LLMs to organizational outputs are frequently obscured, producing what Gutiérrez (2024) termed new power relationships in the age of AI.
ANT has been productively applied to AI systems in recent scholarship. Gutiérrez (2024) used ANT to examine the intersection of algorithms and power dynamics in the context of ChatGPT, arguing that the platform functions as an actant that reconfigures relationships between users, developers, and regulatory frameworks. Gurumoorthi and Meiller (2024) applied ANT to examine distributed agency in AI-driven organizations, showing how blackboxing processes can obscure biases and limit contestability. However, these applications have not engaged with the micro-level identity and boundary work processes that are central to OB/OP scholarship. Our framework addresses this gap by demonstrating how ANT’s conceptual apparatus can enrich—and be enriched by—the analysis of identity work and boundary work in LLM-mediated organizational settings.
Toward an Integrative Framework: Algorithmic Entanglement
We introduce the concept of algorithmic entanglement to describe the recursive, co-constitutive process by which professionals’ identity work and boundary work are enmeshed with the material affordances, outputs, and network effects of LLMs. Algorithmic entanglement is not a metaphor; it is an ontological claim, grounded in sociomateriality and ANT, that the identity and boundary practices of organizational actors cannot be analytically separated from the LLM technologies with which they are increasingly intertwined. The framework operates through three interconnected mechanisms.
Mechanism 1: LLMs as Boundary Objects and Translation Devices
Star and Griesemer’s (1989) concept of boundary objects—artifacts that inhabit multiple social worlds and satisfy the informational requirements of each—provides an initial lens for understanding how LLMs function across occupational and organizational boundaries. An LLM-generated draft, for instance, can simultaneously serve as a legal document for a compliance team, a communication artifact for marketing, and a strategic input for senior leadership. However, LLMs exceed the classical boundary object concept because they do not merely mediate between existing boundaries; they actively translate inputs across domains in ways that reconfigure those boundaries.
Through the ANT lens, LLMs perform translation by enrolling human users into new networks of practice. When a junior analyst uses an LLM to produce work previously reserved for senior colleagues, the technology translates expertise across hierarchical boundaries, destabilizing established role demarcations and prompting boundary work by those whose jurisdictional claims are challenged. This translation is not neutral; it carries the biases, conventions, and knowledge structures embedded in the LLM’s training data, producing what we term “asymmetric translation”—a process that redistributes competence while simultaneously reproducing existing epistemic hierarchies.
Mechanism 2: Sociomaterial Identity Assemblages
Drawing on Orlikowski’s (2007) constitutive entanglement thesis and Katila et al.’s (2019) work on sociomaterial identity construction, we argue that LLMs become constitutive elements of professionals’ identity assemblages. When a physician uses an LLM for diagnostic support, or a software developer employs code-generation tools, the resulting work products are sociomaterial composites that challenge conventional understandings of professional competence. The professional’s identity is no longer constructed solely through their own skills and knowledge but through the human–LLM assemblage—what ANT scholars would term a “hybrid collectif” (Callon & Law, 1995).
This has profound implications for identity work. Brown’s (2022) observation that identities are multiple, fluid, and rarely fully coherent becomes even more salient when the material substrate of identity—the work products, communications, and performances through which professionals signal competence—is co-produced with a nonhuman actant. Professionals must engage in new forms of identity work to manage the ambiguity: claiming credit for LLM-assisted outputs, distancing themselves from errors generated by the technology, and narratively constructing their relationship with AI in ways that sustain their sense of professional agency and distinctiveness.
Mechanism 3: Network Reconfiguration and Distributed Agency
ANT directs attention to how the introduction of a new actant—in this case, an LLM—reconfigures the entire network in which it is embedded. Following Latour’s (2005) principle that agency is not a property of individual entities but an emergent effect of network associations, we argue that LLMs redistribute agency across organizational networks in ways that demand simultaneous identity work and boundary work from multiple human actors.
Consider a team in which an LLM is integrated into the workflow for generating research reports. The technology does not simply augment one team member’s productivity; it reconfigures the network of relationships, expertise claims, and task boundaries across the entire team. Senior members may find their gatekeeping role diminished; junior members may gain access to capabilities that challenge hierarchical distinctions; and the LLM itself, through its outputs, participates in shaping the team’s collective identity and boundary practices. As Bankins et al. (2024) noted in their multilevel review, occupational identity influences workers’ use of digital technologies, which in turn acts as a sensemaking tool that shapes how they approach the disruption these changes bring. Our framework extends this insight by theorizing the recursive loop: LLM use reshapes identity, which reshapes LLM use, which further reshapes identity—a process of ongoing algorithmic entanglement.
Theoretical Propositions
On the basis of the integrative framework developed above, we advance six propositions that connect the four theoretical traditions and specify testable relationships for future empirical research.
Proposition 1. LLMs function as sociomaterial actants that participate in the constitution of professional identities, such that professionals who routinely interact with LLMs will engage in qualitatively distinct forms of identity work (e.g., hybrid attribution, competence narration, and agency negotiation) compared to those who do not.
Proposition 2. The boundary work performed by professionals in response to LLM integration will be co-constituted with the material affordances of the technology, such that the permeability, flexibility, and salience of occupational boundaries will be contingent on the specific LLM configurations and use practices enacted within organizational settings.
Proposition 3. LLMs perform translation (in the ANT sense) by enrolling human actors into new networks of practice, and this translation process will be asymmetric—redistributing perceived competence and epistemic authority in ways that advantage some occupational groups while threatening the jurisdictional claims of others.
Proposition 4. The blackboxing of LLM contributions to organizational outputs will moderate the relationship between LLM use and identity threat, such that greater opacity of AI involvement will reduce identity threat in the short term but increase vulnerability to sudden destabilization when the blackbox is opened.
Proposition 5. Professionals with strongly defined occupational identities will engage in more vigorous boundary work in response to LLM integration, consistent with Pemer’s (2021) finding that clearly defined occupational identities facilitate technology adoption, but extending this to predict that such adoption will be accompanied by intensified efforts to maintain jurisdictional boundaries.
Proposition 6. The recursive process of algorithmic entanglement will produce emergent organizational identities—collective self-understandings of “who we are as an organization that works with AI”—that cannot be reduced to aggregations of individual identity work but reflect the sociomaterial assemblage of human actors, LLM technologies, and organizational structures.
Discussion
Theoretical Contributions
This article makes three principal theoretical contributions to the OB/OP literature. First, by reconciling boundary work and identity work with sociomateriality and ANT, we provide conceptual scaffolding that bridges micro-level psychological processes (how individuals experience and manage identity threats from AI) with meso-level sociomaterial analyses (how technologies participate in the constitution of organizational practices). This integration responds to persistent calls in the field for multilevel theorizing that takes technology seriously as a constitutive element of organizational life rather than as an exogenous contextual variable (Orlikowski & Scott, 2008; Bankins et al., 2024).
Second, the concept of algorithmic entanglement advances sociomaterial theory by specifying the mechanisms through which a particular class of technology—LLMs—participates in identity and boundary practices. While Orlikowski (2007) established the general principle of constitutive entanglement, and Katila et al. (2019) extended this to identity construction in entrepreneurial settings, neither the general framework nor its extensions have addressed technologies that are themselves linguistically generative. LLMs are unique in this regard: they produce text that is indistinguishable from human output in many contexts, creating what we have termed “condensed sociomateriality” that collapses the distinction between the social and the material in unprecedented ways.
Third, by applying ANT’s vocabulary of translation, symmetry, and blackboxing to the micro-processes of identity and boundary work, we demonstrate the value of ANT for mainstream OB/OP scholarship—a domain in which it has been underutilized despite its explanatory power. Our framework shows how ANT concepts can illuminate phenomena that are difficult to capture with conventional OB theories: the redistribution of agency across human–nonhuman networks, the asymmetric translation of expertise through algorithmic mediation, and the dynamic reconfiguration of occupational boundaries through network effects.
Implications for Practice
For organizational leaders and human resource professionals, the algorithmic entanglement framework highlights the inadequacy of treating LLM integration as a purely technical or productivity-focused initiative. Because LLMs are constitutive of identity and boundary practices, their introduction into organizational settings will inevitably provoke identity work and boundary work responses that must be anticipated, supported, and managed. Organizations that fail to attend to these dynamics risk identity-threatening implementation experiences that can generate resistance, disengagement, and counterproductive work behaviors.
Practically, this framework suggests that organizations should create transitional spaces—what Selenko et al. (2022) described as “safe spaces”—in which professionals can experiment with LLMs, develop new hybrid identities, and renegotiate occupational boundaries without the threat of immediate evaluation or jurisdictional loss. Leadership development programs should address the identity work challenges of managing in entangled human–LLM networks, including the capacity to sustain team cohesion when the contributions of human and nonhuman actors are difficult to disentangle.
Agenda for Future Research
The propositions developed in this article suggest multiple avenues for empirical investigation. Qualitative studies employing longitudinal, ethnographic methods would be particularly well-suited to capturing the emergent, processual nature of algorithmic entanglement in organizational settings. ANT’s methodological commitment to “following the actors” (Latour, 2005) recommends tracing the associations between LLMs, human users, organizational structures, and broader institutional arrangements as they unfold over time. Sociomaterial approaches such as video-based interaction analysis could illuminate the micro-practices through which identity work and boundary work are enacted in human–LLM assemblages.
Quantitative research could operationalize the propositions through survey instruments that measure LLM use intensity, perceived identity threat, boundary management behaviors, and occupational identity strength, testing the moderating role of blackboxing and the mediating role of hybrid attribution. Experience sampling methods would be valuable for capturing the within-person dynamics of algorithmic entanglement as they unfold across workdays and projects.
We also encourage researchers to adopt what Jarzabkowski and Pinch (2013) termed a “third wave” sociomaterial approach that accounts for both the idiosyncrasies of practice in situ and the regularities across practices. This would enable the development of middle-range theory that connects the micro-level mechanisms of algorithmic entanglement to the macro-level transformation of occupational structures and professional fields.
Conclusion
Large language models are not merely the latest in a long line of workplace technologies; they represent a qualitative shift in the materiality of knowledge work that demands corresponding theoretical innovation. By reconciling boundary work, identity work, sociomateriality, and actor-network theory, this article provides a unified conceptual framework—algorithmic entanglement—for understanding how LLMs co-constitute the identities and boundaries of organizational life. We hope this framework will stimulate empirical research that takes seriously the ontological proposition at its core: that in the age of LLMs, we cannot understand identity without understanding materiality, and we cannot understand boundaries without understanding the networks in which they are enacted.
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