Fading into insignificance: Why mainstream OT scholars “missed the boat” on intelligent technologies and what we can do about it

Abstract

In this essay, I argue that mainstream organization theory (OT) scholars have failed to include intelligent technologies in their theorizing and that this omission is making the core of OT increasingly irrelevant in a world of organizations constituted by cloud computing, blockchain, social media, and artificial intelligence. I begin by examining three of the most active areas of research in mainstream OT—institutional theory, organizational identity, and sensemaking—and argue that theorizing in all three areas has not been updated sufficiently to reflect the central role of intelligent technologies in the phenomena they theorize. I go on to discuss some of the reasons mainstream OT scholars have missed the boat on intelligent technologies including (1) early framings of technology as exogenous to organizations; (2) a fascination with the ideal; (3) the ubiquity and invisibility of intelligent technologies in modern organizations; and (4) a lack of interest in technology among mainstream OT scholars. I close with some suggestions for steps that OT scholars might take to resolve this challenging situation.

Intelligent technologies—machines that perform “tasks that previously relied on human intelligence” (Sergeeva et al., 2023: 733)—are a ubiquitous feature of modern society. The introduction of new intelligent technologies has repeatedly driven significant change in organizing and organizations. ¹ Generative AI, the most recent intelligent technology to appear, is currently creating fundamental changes in organizational life, affecting “how decisions are made, knowledge is produced, and actions are coordinated” (Stelmaszak et al., 2025: 1), while earlier intelligent technologies like social media, digital platforms, and cloud computing continue to reverberate through organizations and organizing. Meanwhile, other intelligent technologies, such as quantum computing and autonomous drones, are waiting in the wings. As a result, organizational researchers are all, as Bailey et al. (2022) succinctly observed, “theorists of technology now.”

Except we aren’t. Even a cursory glance at the field reveals that much of mainstream organization theory (OT) remains silent on intelligent technologies while the study of intelligent technologies and their impacts on organizations remains a specialized area of research largely disconnected from the core theoretical streams of OT. ² Despite the profound implications of intelligent technologies for organizing—and their increasingly central role in the processes of social construction that constitute organizations (Phillips and Moser, 2024)—they remain almost invisible in the core theoretical streams of OT research like institutional theory, organizational identity, and sensemaking.

Perhaps this is not that surprising given the historical disinterest in technology more generally among mainstream OT scholars. As Orlikowski and Scott (2008: 434) observed almost two decades ago, “a quick perusal of the academic management literature would suggest that from the point of view of organizational research, technology is largely absent from the world of organizing.” It seems little has changed in the intervening decades beyond an ever-increasing disparity between the importance of technology in organizations and the lack of attention to technology in the mainstream OT literature.

This is not, of course, to say that some organizational researchers have not recognized the importance of intelligent technology and done extensive work on its effects on organizations (e.g. Beane, 2019; Lumineau et al., 2021; Mindel et al., 2024). Taking a recent example, in an article in the Journal of Management Studies, Stelmaszak et al. (2025: 1) begin by clearly marking out the opportunity: “Developments in artificial intelligence (AI) are transforming organizing and organizations, creating a space for novel theorizing in organization and management theory.” They go on to propose an ontological shift in how we conceptualize AI. Building on posthumanism, they theorize that instead of residing within algorithmic actors, AI arises from the relations among human and algorithmic actors as an organizing capability. Yet this sort of robust recognition of the centrality of intelligent technology to organizing remains unacknowledged in the core theories of OT, and this theorization of AI as an organizing capability (or even something that might have implications for core constructs like institutions and identities) has little parallel in the existing literature that makes up the core of OT. And, sadly, given the theoretical framing and focus of this article, there is little chance of it having much of an impact on the core theories of OT.

As a result, the field of OT is in a challenging situation. While some organizational researchers are doing great work exploring the implications of intelligent technologies for organization and organizing, the OT researchers engaged in the ongoing development of the core theories of OT remain remarkably unconcerned with the role of intelligent technologies in the phenomena they focus on and show little interest in the work on technology and organizations that is being done. This leads to the following thesis statement that motivates this essay:

OT as a field is no longer fit for service. We need to rethink our most basic concepts and theories to reflect the reality of technology mediated and enabled organizations or risk irrelevance.

As the role of intelligent technologies in organizing becomes ever more central, and as intelligent technologies become increasingly implicated in the processes of social construction that constitute organizations and their environments, the core theories of OT are becoming more and more detached from the reality of organizations today and are therefore becoming increasingly unhelpful in understanding organizations and organizing. As a result, as the editors of this special issue argued in the initial call for papers, “the time is ripe to recognize how technology is more constitutive of strategy and organization than has so far been recognized” (Sergeeva et al., 2023: 733). In this essay, I will build on this call to action and argue that mainstream OT scholars need to recognize the constitutive role of intelligent technology in organizations if they wish to rescue 50 years of OT theorizing that is rapidly losing relevance.

But it is important to note that the problem is not just one of attention and theorizing. It also reflects an unhelpful bifurcation of researchers interested in the core theories of OT and researchers interested in technology and organization. While technology and organization researchers often identify with OT more broadly, scholars working in mainstream OT often see technology and organization research as an adjacent field (perhaps more closely aligned with the field of information systems) and technology and organization researchers are therefore seen as distinct from OT researchers by mainstream OT scholars. While this separation is generally amicable, it is highly problematic. So, a part of our challenge as organizational researchers is to figure out ways to bridge this identity challenge.

In this essay, I will build on these observations to discuss some of the reasons we have ended up in this situation and argue that there is much to be gained from moving intelligent technology as a topic of scholarship in OT—and the organizational researchers who are focusing on it—out of the technology studies “ghetto” and integrate them into the core of OT. My arguments here are primarily aimed at mainstream OT scholars but also point to opportunities for technology and organization researchers. We need to make intelligent technology as central in mainstream OT as it is in actual organizations. But this will require a dramatic change to the core of the field of OT and to the way mainstream OT scholars are dealing (well, not dealing) with the reality of intelligent technology in organizations.

I will also argue that mainstream OT scholars have largely failed to recognize that intelligent technologies are profoundly social both in their production and in their use. Technologies like artificial intelligence and cloud computing have fundamentally changed how people interact, communicate, and organize. Even more, these technologies are implicated in the processes of social construction that underpin the social-symbolic objects (Lawrence and Phillips, 2019) that make up organizations and their contexts. Yet, these technologies and their implications have not really appeared in the core theoretical streams of organization theory (see Lounsbury and Gehman, 2024 for a review of the core theories in organization theory). Ironically, the failure to understand that intelligent technologies are “symbolic machines” (Phillips and Moser, 2024: 25) has meant that OT scholars who are deeply interested in the symbolic have failed to include them in their theorizing about organizations.

In the rest of this essay, I present my arguments in three steps. First, I discuss what I mean by intelligent technology and examine how the reality of modern organizations has become disconnected from three of the most well-developed areas of OT scholarship—institutional theory, organizational identity, and sensemaking. I go on to discuss some of the reasons that the theoretical foundations of OT have fallen so far behind the reality of intelligent technology in organizations today. Finally, I present a plan for reconnecting the theoretical foundations of OT with intelligent technology, which I believe will help the field of OT regain its relevance to academia and practice.

OT and intelligent technology

In this section, I start by discussing what I mean by intelligent technologies and why intelligent technologies are so important to organizations and organizing. I then discuss three of the most important theories of organization that all first appeared in the 1970s and 1980s and are all important parts of the core of OT—institutional theory, organizational identity, and sense making—and highlight the stark disparity between the role of intelligent technology in the phenomena they seek to explain and the role of intelligent technology in the theories themselves.

Intelligent technology

By intelligent technology, I mean digital technologies that perform tasks in organizations that previously required human intelligence or that could not previously be done as human intelligence was insufficient (Sergeeva et al., 2023). For example, a machine learning algorithm that recommends books to a customer on Amazon replaces, in terms of function, a knowledgeable bookstore clerk at a local bookstore. Of course, the intelligent technology is often able to do things that a human could not (the algorithm has access to a large database of previous buying patterns and book reviews that a human could never master), but these technologies perform tasks that are analogous to organizational activities that were done by humans in the past and require something recognizable as intelligence to complete successfully.

In my discussion here, I will use the tripartite typology of technologies—informating, dispersive, and generative—introduced by Shen and Phillips (2026) to structure my discussion. This typology is useful for us here as it provides a way to organize various types of intelligent technologies into categories based on how they affect the production and dissemination of texts, and therefore highlights how these different technologies affect the processes of social construction upon which organizational phenomena depend (e.g. Phillips et al., 2024).

Informating, a term coined by Zuboff (1988), describes the process by which activities, objects, and events are transformed into information and thus become both visible and measurable. Informating technologies produce texts by harvesting digitalized information, converting it into a storable and transferable forms, and enabling its persistence over time and space. Think, for example, of the engine sensors and specialized computer system on a commercial jet engine that communicate data on the state of the engine to the engine’s manufacturer during a flight.

Dispersive technologies, on the other hand, refer to intelligent technologies that enable and shape the ways that texts are transferred, disseminated, and consumed. These technologies fundamentally alter the way that ideas and attitudes diffuse through social networks and influence others. In addition to the data permanence afforded by informating technologies, the advent of the Internet has broadened the reach of online discourse, enabling texts to be disseminated exponentially faster than before the advent of these technologies, but also in ways that completely change who can produce texts and what texts individuals encounter. Social media such as LinkedIn or X are examples of dispersive technologies.

Finally, generative technologies refer to technologies capable of generating original texts, images, or video in response to prompts through a process that is interactive, autonomous, and opaque. These technologies, generally referred to as generative AI, generate novel texts that can then be consumed locally or made available more broadly through dispersive technologies. Generative AI systems such as ChatGPT or Claude are examples of generative technologies. It is worth noting that more than 50% of the texts being published on the web are now produced by these systems (Paredes et al., 2025), making their role in processes of social construction at the societal level highly significant and, arguably, increasingly important at the organizational level.

What these technologies share and what makes them very different from previous generations of technology that affected organizing (i.e. the steam engine or the assembly line) is that they are not just “intelligent machines” but also “symbolic machines” that manipulate texts in ways that have radically new and highly significant implications for organizations and society. And it is the fact that these technologies deal with the symbolic that makes them so important to phenomena that OT researchers focus on. But much of OT as a field has done little to explore the impact of these symbolic machines on the basic processes through which organizations and their contexts are socially constructed. As Phillips and Moser (2024: 3818) explain:

While there is a growing stream of literature looking at the impact of digital technologies on organizing … we lack a comprehensive theory of the effect of these technologies on the symbolic underpinnings of management and organization. Organizations are social constructions and much of the work in OT reflects a social constructivist epistemology. This means that we are at risk of ending up with a fragmented and unintegrated landscape of research, and that a broad understanding of the complex impact of symbolic machines on organizing and the symbolic remains to be developed.

Institutional theory

Since the first papers on what was then called “new institutional theory” appeared in the late 1970s and early 1980s (e.g. DiMaggio and Powell, 1983; Meyer and Rowan, 1977), this approach to the study of organizations and their contexts has grown to become what is arguably the dominant theoretical perspective in organization theory. Central to this theoretical approach is the notion of institutions as social constructions that shape human behavior; they are “historical accretions of past practices and understandings that set conditions on action” (Barley and Tolbert, 1997: 99). They condition action because they are self-policing (e.g. Douglas, 1986) in the sense that failing to adhere to them is “counteracted in a regulated fashion, by repetitively activated, socially constructed, controls” (Jepperson, 1991: 145). Thus, institutions differ from the myriad of other socially constructed objects that populate social reality by the consequences that occur when actors fail to conform to them.

New institutionalism provided an interesting alternative to the overly rational explanations of organizing that existed both in organization theory, like theories of bureaucracy (e.g. Weber, 1952), and in economics, like transaction cost economics (e.g. Williamson, 1973). Organizations were not simply the result of rational action by the people who designed and ran them but were also subject to complex social forces that produced results that were not consistent with such simple explanations. Institutional theory also connected organization theory to social constructionism (Berger and Luckmann, 1966), in at least a weak form, as an ontology for understanding what institutions are and how they are constructed.

For example, as DiMaggio and Powell (1983) famously asked, “[w]hat makes organizations so similar?” Or put another way, why do organizations in a field become more and more alike over time? Their answer was that, despite the arguments of early OT scholarship, there were social forces that overrode the rational impulses of managers to build highly specialized and differentiated organizations and led to increasing similarity—what they referred to as isomorphism—in organizations within a field over time even when the increased similarity did not make sense from an efficiency point of view.

But while work in institutional theory began with a focus on how institutions shaped action (and particularly on isomorphism), in the early 2000s attention turned increasingly to the impact of agents on institutions, as concepts like institutional entrepreneur (Maguire et al., 2004), institutional work (Lawrence et al., 2009) and social-symbolic work (Lawrence and Phillips, 2019) attracted more and more attention from researchers in a much-needed correction to the overly narrow focus on the effects of structure on action. The result was a broad stream of research balancing the effects of institutions on actors within a field combined with a concern for how actors sought to shape institutions in order to advance their interests.

Around this time, work also appeared focusing on the question of what institutions are and how institutionalization happens. In their early paper on institutionalization and discourse, Phillips et al. (2004) argued that it is not the micro-level actions of organizational members that produce the institutions that shape action in organizational fields, but rather texts that arise describing the actions of organizational members: “It is primarily through texts that information about actions is widely distributed and comes to influence the actions of others” (Phillips et al., 2004: 635). For example, actors do not come to know about the implementation of a new organizational structure in the organizations within an organizational field by direct observation, but rather this happens when other actors produce and disseminate texts describing the new organizational structure and its effectiveness.

But despite the ongoing and extensive development of this literature, what hasn’t happened is any attempt to discuss how waves of intelligent technologies might affect institutions and institutionalization understood in this way or what role intelligent technologies might play in institutional processes more generally. While institutional theory has been used widely to study intelligent technology in adjacent literatures such as information systems (e.g. Faik et al., 2020; Jensen et al., 2009), science and technology studies (e.g. Fuenfschilling and Truffer, 2014), innovation (e.g. Geels, 2004), and even tourism studies (e.g. Soares et al., 2021), a concern for the impact of intelligent technologies among researchers developing and extending the core of institutional theory remains largely notable by its absence.

So, what would a version of institutional theory look like that was updated to reflect the centrality of intelligent technology in modern, algorithmic society? While intelligent technologies have a variety of implications for institutional theory, there are two areas of institutional theory that seem particularly important to rethink. First, intelligent technologies have important implications for how texts are disseminated. As I discussed above, institutions are socially constructed conventions that become institutionalized through the construction and dissemination of texts (Phillips et al., 2004). But the ways in which texts are constructed and disseminated fundamentally changed with the introduction of dispersive technologies. Social media, for example, have not only changed the way texts are distributed, they have made the ability to participate in the production of texts available to many more actors. Perhaps even more importantly, these technologies use algorithms to decide what texts a user sees (think, for example, of the Netflix algorithm that decides what movies to suggest to you when you are looking for a movie). How these “recommender systems” (Roy and Dutta, 2022) shape the texts that users encounter can fundamentally affect the process of institutionalization, yet there has been little discussion about this among institutional scholars.

Second, while dispersive technologies have important ramifications for processes of institutionalization, generative technologies bring with them even more radical implications. Generative technologies produce novel texts and can therefore directly participate in the processes of social construction that construct institutions (Phillips et al., 2024). These technologies can engage in “institutional work” and act as “institutional entrepreneurs,” yet there is little in the literature on these concepts that has even begun to deal with the truly radical implications of generative technologies specifically, and intelligent technologies generally, for institutional processes and institutional theory.

Organizational identity

Since the publication of Albert & Whetton’s influential article in 1985, a large literature has grown up exploring the nature and dynamics of organizational identity (Pratt et al., 2016). In their initial formulation, Albert & Whetton defined organizational identity as that which is central, enduring, and distinctive about an organization’s character, and researchers have spent considerable energy exploring the implications of this idea. In fact, as Gioia et al. (2013: 125) argued in their review a decade ago, “identity now has become one of the core concepts in organization study itself.” And interest in the nature and effects of organizational identity have only continued to increase in the decade since their observation.

Yet, given the large and growing literature on organizational identity, there has been surprisingly little consideration of the role of intelligent technology in organizational identities or of the role of intelligent technology in the processes of social construction that underpin identities. There are some discussions of how identity affects the ability of organizations to deal with technological change (Tripsas, 2009), but this is not so much about intelligent technology as it is about technology in general and it is primarily focused on the effect of organizational identity on technological adoption. So, how does intelligent technology impact theories of organizational identity?

One important area that needs attention from organizational identity scholars is the role of intelligent technologies in the processes of social construction that underpin organizational identity. Like institutions, organizational identities are social constructions, and intelligent technologies have significant implications for their construction. This happens in at least two important ways. First, dispersive technologies do not simply distribute texts randomly. As I described in the previous section, these technologies use algorithms of various kinds to decide what texts to provide to a particular user and in doing so shape the experience of the user and the user’s understandings of the topic. For example, the search results from a particular search engine will shape the understandings of a company that users that search engine come to hold. Similarly, the recommender systems on social networking platforms like LinkedIn will shape the networks that users develop over time and therefore shape the stream of information they encounter about a company from their networks on social media platforms.

Second, generative AI is increasingly replacing search as the source of information for many people. But rather than recommender systems that distribute existing texts (social media posts, movies, etc.), generative AI produces novel texts based on the training data the system was trained on and the prompts the user provides. However, training data is always biased (Rogers and Jonker, n.d.) and is never complete. And user prompts are highly idiosyncratic. So, the ways that members encounter information about their organization are becoming more and more shaped by a complex combination of recommender systems and generative AI. How this affects organizational members’ (and external stakeholders’) perceptions of their organization requires careful theorizing by OT scholars.

But some intelligent technologies play a more direct role in the identities of a specific group of organizations: intelligent technologies can also be at the core of an organization’s identity. Many organizations are now “blockchain companies” or “AI companies,” and the adoption of these technologies is centrally important for their identities. While the great majority of these firms are small, a large portion of the US stock market is currently made up of a small number of these firms, and the idea of an identity as simply symbolic and amenable to social construction ignores the materiality of the technologies to which these firms’ identities are tethered. This aspect of organizational identity continues to grow in importance as technology companies come to be ever more central in developed Western economies, yet little work has been done by identity scholars to examine this phenomenon.

Many aspects of the organization are defined by the way they have adopted these technologies as central to what they are, and this has important implications for the dynamics of identity in this important group of organizations. This includes the process through which the identity of these organizations becomes linked to an emerging category of technology and how their identity is affected by the link to a category of organizations (e.g. blockchain company) and also to the materiality of the evolving technology. The details of how this happens and the implications of this for the identities of the organizations in question are an important area of research that deserves more attention from organization identity researchers.

Sensemaking

The concept of sensemaking, first introduced by Karl Weick (Weick and Weick, 1995), has gone on to become one of the core areas of research in OT with a recent review identifying 2,838 articles on the topic in “business and management research” (Eckstein et al., 2024). The sensemaking perspective in organization theory focuses on “the process through which people work to understand issues or events that are novel, ambiguous, confusing, or in some other way violate expectations” (Maitlis and Christianson, 2014: 57). While much of Weick’s work involves how groups make sense in crisis situations, the idea has been applied widely in OT research.

While researchers in this tradition have recognized technology, and in particular technology failure (e.g. Weick, 1988), as a source of the sorts of issues that require sensemaking—in other words, that technology can be the cause of an instance of sensemaking—there has been surprisingly little attempt to theorize the role of intelligent technology in sensemaking processes more generally. Yet, the introduction of intelligent technology into organizations has significant implications for theories of sensemaking; they do so because they are not simply technologies that require sensemaking when they fail, but active participants in the process of sensemaking more generally.

First, informating technologies change the way humans perceive the world by producing new forms of information that affect human understandings. These technologies both create new instances where sensemaking is required and they often engage in sensemaking with humans by processing the data they collect and providing interpretations of the patterns that result. Imagine, for example, a farmer introducing new intelligent technologies on a dairy farm that produces reports on individual cows as they come into a robotic barn and are milked. The technology senses the cow’s temperature, samples the milk for infections and other markers of ill health, as well as testing hormone levels to determine whether the cow is fertile and ready to be impregnated. The system can also analyze gait and walking speed as further data points reflecting the health and wellbeing of the cow. The implementation of informating technology in this example fundamentally changes the process of sensemaking that a farmer carries out on an ongoing basis to assess their herd, as he or she now carries out sensemaking with these intelligent technologies.

Generative technologies take this a step further. These systems can not only participate in the process of sensemaking but can also engage in “sensegiving”: “the process of attempting to influence the sensemaking and meaning construction of others toward a preferred redefinition of … reality” (Gioia and Chittipeddi, 1991: 442). Generative technologies can not only participate in sensemaking by providing information like the informating technologies in the example of the farmer above, they can also provide comprehensive explanations of events that humans are struggling to understand. They can carry out sensegiving in an effort to convince humans to accept an understanding of a situation.

For example, it is becoming increasingly common for individuals to seek relationship advice from generative AI systems like ChatGPT. In fact, research shows that “[o]nline interventions have emerged as a prominent alternative to traditional therapeutic approaches” and that the “[a]vailable literature suggests that these interventions, which often parallel evidence-based, in-person therapies, are effective and address some of the accessibility issues tied to traditional therapy” (Vowels et al., 2024: 1). In engaging in interactions that look like traditional therapeutic approaches, generative AI is engaging in sensegiving based on the description of the situation provided by the “patient” and its understanding of human relationships and human behavior in general. In doing so, it provides a way to think about a situation happening between humans, and I would argue, it is performing sensegiving.

Yet, the importance of these intelligent technologies to sense-making remains all but unexplored. What are the effects of engaging with generative technologies in this way? And how should we include these technologies in theories of sense-making? Are they a complement to human sense-making or a replacement? And how do the affordances of intelligent technologies affect human sense-making? For example, how does their ability to synthesize information and deal with large volumes of texts that far exceed human abilities impact sense-making? How intelligent technologies affect sense-making remains a central question for sense-making scholars to include in their theorizing. Until they do, the relevance of sense-making theories will continue to erode as intelligent technologies assume an ever-larger role in these fundamental social processes.

Why have mainstream OT scholars ignored intelligent technology?

The fact that the core theories of OT do not reflect the reality of the impact of intelligent technology on organizations raises an important question: why have OT researchers not updated the foundations of OT to reflect the transformation in how we organize as intelligent technologies have appeared in organizations? Somehow, despite the significant academic (e.g. Vial, 2021) and practitioner (e.g. Neeley and Leonardi, 2022) literature on the digital transformation of organizations, mainstream OT researchers have continued to develop the core theoretical streams underpinning the field as if nothing has changed. And while technology and organization researchers have done a lot to theorize technology and to explore the impact of intelligent technology on organizing, they have spent little time revisiting the theoretical perspectives at the core of OT. In this section, I will discuss some of the reasons for this as a prelude to suggesting some strategies to remedy the situation in the next section.

The early framing of technology in OT

Perhaps somewhat ironically given the current challenges facing mainstream OT, some of the earliest work in OT focused on the effect of technology on organizations and organizing. For example, Woodward’s (1958) early work is famous for showing that the nature of the systems of production that a firm used had important implications for how they organized, and in fact, firms that used the same kind of technology of production (e.g. small batch, large batch or continuous process) tended to be organized in similar ways. This idea that patterns of organizing were “contingent” on technology was an important early finding that led to a significant stream of research in OT (Sewell and Phillips, 2010).

Yet despite this early focus, new theoretical areas that appeared in OT beginning in the 1970s and 1980s failed to include much of a concern for technology and the many theories that first appeared in that period (including institutional theory, network theory, sensemaking, etc.) are, as a result, ill-suited to reflect the growing role of intelligent technology in modern society as they are currently theorized. Taking institutional theory as an example, Meyer and Rowan (1977) mention technology 12 times in their paper. But their view of technology is as something an organization has or something that is exogenous to the organization and affects organizing but is not implicated in it (Orlikowski, 2010). For example, they cite Woodward (1965) while discussing technology as a factor that increases the need for coordination and Ellul (1964) when discussing technologies as something that can become institutionalized and act as myths that shape organizing. But none of this really helps in building an understanding of technology that is useful in dealing with the appearance of intelligent technologies in organizations.

And, in defense of these early framings, when an organization acquired a blast furnace or organized production as an assembly line, the nature of these technologies meant that saying that technology is something an organization has, rather than something it is, was of little consequence. These technologies did add complexity that needed to be managed, could lead to the formation of rationalized myths that shaped organizing, and, most importantly for us here, they did not play a role in the social construction of the organization. Focusing on the organization of the management hierarchy, and not being particularly concerned about the role of technology in the social process that constitute organizations, was not unreasonable in the 1970s.

But this is a significant problem today, given that many of the most important and developed streams of research in mainstream OT originated during this time. Across these streams of literature, it is not surprising that OT researchers during this period did not include a concern for intelligent technology as these technologies played an insignificant role in most organizations at the time. However, that does create a challenge to include the role of these technologies at this point given their widespread adoption in the organizations we study.

There are, of course, theoretical resources available in the existing technology and organizations literature. For example, Orlikowski (2010) identifies four different ways technology appears in organizational research: it can be absent, exogenous, emergent, or entangled. But currently, research in mainstream OT either simply ignores technology (so it is absent) or treats it as exogenous, so the last two approaches to technology remain to be explored for their potential as ways to integrate a theoretically sophisticated view of technology in mainstream OT. While the latter two approaches are currently almost exclusively used by technology and organization researchers to understand technologies, they also have real potential for rethinking the relationship between technologies and organizing in mainstream OT.

Anti-materialism

The second reason for the lack of a recognition of the importance of intelligent technologies to mainstream OT is straightforward: OT has been characterized by a strong anti-materialism since its beginnings in the 1970s, and technologies are, in an important sense, material (Kallinikos et al., 2012). This is not, I suppose, surprising given the general absence of an interest in the material in social science generally. As Carlile et al. (2013: 1) observe, “for several decades the attention to objects and materiality, more broadly, both in organization studies and in social science has been limited.”

To some degree, this makes sense. The social sciences were founded to provide rational, evidence-based understandings of human society and to address the complex challenges brought about by modernity, with the aim of improving social conditions and governance. As Cravens (1985: 183) succinctly observed, “[t]he social sciences have been concerned with people, not things.” This necessarily meant that social scientists would focus primarily on the symbolic aspect of human society rather than the material aspect. The material aspect was mostly ignored in favor of a focus on what happened among people and what was unique to human interaction.

But, in addition to the general anti-materialism of social science, I believe two other factors are particularly important. First, the early work in OT, which now forms the foundations of the field, was, to a significant degree, a reaction to neoclassical economics and Marxism. From the perspective of both theoretical streams, society (or at least the economy) is largely derivative of the material conditions of production. In neoclassical economics, this is accompanied by an emphasis on individual rationality and a belief in the superiority of competitive markets. In Marxism, the focus is on the ownership of the means of production, class struggle, and the distribution of wealth. But while the conclusions each group of scholars came to are very different, the starting point is the same: the material conditions of production determine the social structures that result.

The theories of organization that appeared in the 1970s and 1980s were in part motivated by a reaction to the materialism of these theoretical perspectives and instead focused on cultural and symbolic explanations for organizational phenomena. This generation of organizational scholars was heavily influenced by sociology and anthropology and sought to understand organizations and organizing through a new vocabulary rooted in human social interaction (think, for example, of the “myths” and “ceremonies” invoked by Meyer and Rowan (1977)) and a new ontology based in social constructionism (e.g. Berger and Luckmann, 1966). Organizations were no longer a reflection of a material reality but became a human social accomplishment. From this new perspective, “technologies themselves hardly matter at all” (Kallinikos et al., 2012: 4).

Second, while this early formative period of OT was shaped in important ways by a reaction to the materialism of economics and Marxism, the tendency to ignore intelligent technology was also shaped by the linguistic turn in OT that occurred in the 1990s and 2000s (Alvesson and Kärreman, 2000). The linguistic turn involved a growing interest in language and its role in the construction of organizations among OT scholars and the adoption of various methodologies for studying linguistic phenomena in organizations, including discourse analysis (e.g. Phillips and Oswick, 2012), narrative analysis (e.g. Feldman et al., 2004), and rhetorical analysis (e.g. Suddaby and Greenwood, 2005). While the linguistic turn provided important new insights into organizing and organizations, it also moved the focus of attention further from the material aspects of organization to the symbolic in organizations (Phillips and Moser, 2024), and in doing so moved the focus of attention further away from technology.

This is, of course, ironic given that intelligent technologies are, as I discussed earlier, machines that manipulate symbols (and, perhaps more importantly, texts constructed out of symbols) in new and powerful ways. These technologies, unlike the steam engine or the assembly line, participate in social processes in ways that were, until recently, the sole province of humans.

The ubiquity and invisibility of intelligent technology

As I mentioned above, in her pathbreaking work Woodward (1958) found that the best organizational form depended on what production technology a firm was using. While this may seem obvious today, at the time, it was a revolutionary observation. It required Woodward to reject the common view among OT scholars at the time that there was “one best way” to organize. Rather than “one best way,” she found “it depends,” and the contingency theory of organizations was born.

Why is the story of the beginning of contingency theory and Joan Woodward relevant to why OT scholars have underplayed technology in their research? Most recent research in organization theory focuses on organizations full of knowledge workers who mostly use the same technologies in their work. These technologies include personal computers, mobile phones, database systems, cloud computing, and increasingly, generative AI. There is little variation in the technologies these firms use, and the adoption of new technologies happens at basically the same time across these organizations. As a result, intelligent technology disappears into the background and seems as unimportant as the electrical supply or ventilation system for understanding the organizations being studied. Even more, as new generations of intelligent technologies are introduced into organizations, researchers also adopt the same technologies in their universities, making the technologies seem mundane and uninteresting (if not simply irritating!).

But perhaps even more, these technologies are hard to observe. While Joan Woodward focused on factories where the production technology was obvious and visible, many of the intelligent technologies that have fundamentally changed how we organize are difficult to see, and the average respondent in an organization only has the dimmest notion of how they work or what they do. Take, as an example, cloud computing: from both anecdotal evidence and the business press, it is clear that cloud computing has revolutionized business organizations in profound ways.

Few technological advancements have had as profound an impact as the rise of cloud computing. Looking back at the cloud revolution illustrates how this paradigm has reshaped global business operations. From established enterprises optimizing their workloads, to startups “born in the cloud,” the cloud’s impact is pervasive and continually shaping the landscape of innovation. (Sayegh, 2023)

Yet a quick search of the Academy of Management Journal, Academy of Management Review, Administrative Science Quarterly, Organization Science, and the Journal of Management Studies turns up only scattered references to cloud computing as an example or as part of the description of an organization’s business focus. There are no papers discussing how “the cloud revolution” might have changed organizing given its “profound impact” on businesses. The fact that how humans organize has fundamentally changed now that we have this intelligent technology remains unmentioned in the mainstream OT literature, and little has been done to rethink core theories like organizational identity or network theory in the light of this revolution in organizing.

A lack of interest in technology

Finally, with a few notable exceptions, organization theorists are not technologists. This is neither surprising nor is it a criticism of OT scholars. But it does mean there is a general lack of enthusiasm among mainstream OT scholars for understanding the role of intelligent technologies in organizational phenomena, accompanied by an unfortunate lack of appreciation for how revolutionary these technologies are for organizations and organizing. While technology and organization research (and adjacent literatures like management information systems) is characterized by well-developed conversations about the impact of intelligent technologies on organizations and organizing, mainstream OT scholars show no similar enthusiasm for these conversations and continue to focus on a historical version of organizations that no longer exists.

This is not surprising of course. OT scholars have self-selected into a field that has, at least since the early 2000s, viewed organizational phenomena from a weak social constructionist point of view, understanding organizations as something constituted in human interaction. Furthermore, organization theory is largely rooted in social theory from sociology, anthropology, and psychology from the 1970s and 1980s. Scholars who are attracted to join the community of OT scholars are generally not particularly interested in intelligent technology nor sensitive to the bias against intelligent technology in the existing literature. The fact that we are no longer alone in the processes of social construction that produce organizations and society has largely gone unnoticed.

More parochially, but also completely understandably, most OT scholars have little understanding of intelligent technology. Their backgrounds and work experience (if they have work experience) lie in areas far from technology or predate much of the intelligent technologies that currently saturate companies. And while universities use a lot of technology, academics are largely uninvolved in the design and implementation of the information systems on which the modern university rests and find the systems they use more of an irritation than a major force transforming their activities. And while more discussions of the effects of intelligent technologies on academic work are happening in our field (e.g. Von Krogh et al., 2023), the day-to-day experience of OT scholars is experienced by them as largely the same despite the introduction of ever more revolutionary intelligent technology.

Given the combined effect of early theorizing of technology as exogenous, the anti-materialism that characterizes much of OT, the ubiquity and uniformity of intelligent technology in white-collar organizations, and the general lack of interest in intelligent technology among OT scholars, it is no wonder that the core theories of OT remain disconnected from the revolution in organizing that has occurred due to the introduction of intelligent technologies. But does this mean that the core theories of OT are simply past their “sell by” date and are destined to continue to lose their relevance? I don’t believe that outcome is unavoidable, and in fact, am excited about the possibilities of creating new versions of classical OT theories updated to reflect the presence of symbolic machines in our organizations. While understandable, the problem of OT and intelligent technology is hugely problematic but also eminently solvable!

What can we do?

One possible result of the growing disparity between the ever-increasing importance of intelligent technology in modern organizations and its invisibility in the theoretical core of OT—and the possible outcome that motivated me to write this essay—is that 50 years of work in mainstream OT fades into insignificance as research streams that are better placed to theorize the ramifications of intelligent technology for organizing become more prominent and better explain the reality of modern organizations. The increasing number of scholars interested in intelligent technology and organizing may simply focus on developing completely new theories of organization and lose interest in the existing theoretical frameworks that have been developed in mainstream OT. As a result, theoretical approaches like institutional theory, organizational identity, and network theory may simply fade away as new approaches based on theorizing technology move to the fore in OT and as adjacent fields with more of a technology focus flourish. But abandoning the existing theories of organization that have been developed over the last 50 years to focus on developing new theories of digital organizing that explicitly focus on intelligent technology would be an extreme case of “throwing the baby out with the bathwater.” But what is the alternative?

In this section, I propose three steps that would go some way toward solving the existential crisis facing mainstream organization theory. From my perspective at least, this seems like an eminently solvable problem for OT researchers if we are able to agree we have a problem and take appropriate, concrete steps to solve it.

Explicitly recognize the fundamental role of symbolic machines in social construction

Ironically, while one of the main drivers of the disinterest in intelligent technology among organization theorists is their focus on the symbolic, intelligent technologies are themselves highly symbolic both in the sense that they manipulate symbols and that they have fundamentally changed the way the symbolic in human society is created, stored, and disseminated.

As a result, as I have argued above, intelligent technologies are deeply implicated in the processes of social construction through which the social-symbolic objects that make up organizations and their contexts are constructed. As Phillips et al. (2024) summarized in their discussion of the role of generative AI in category creation:

From our point of view, whether the activities of AI systems, and generative AI in particular, are focused purposefully on category work or whether the effects on categories are a side effect of seeking other goals, the fact that their activities can affect processes of social construction and cultural evolution is important and deserves much more attention. But this will require organization theorists to engage more deeply with the symbolic and the socially constructed nature of categories.

While their focus in this paragraph was specifically on generative AI and categories, their fundamental point is that intelligent technologies have important implications for social construction. And, perhaps more radically, taking intelligent technologies seriously means focusing even more on the symbolic as it provides a powerful stepping-off point for organization theorists to begin the process of revising the core theories of OT to reflect the central role of intelligent technology in organizing. The basic ontological position underpinning the core of OT is, at the very least, weakly social constructivist in the sense that the theories explicitly theorize their core phenomena—such as institutions, organizational identities, and so on—as socially constructed. So, recognizing the implications of these symbolic machines really means refocusing on the roots of OT to retheorize our core theories to reflect the reality of social construction in modern organizations.

So, as a first step, I believe we need a “digital turn” in mainstream OT where there is a concerted effort to understand the role of intelligent technology in the social construction of organizations and then to use this as a stepping off point for rethinking our core theories of organization. This digital turn will require a widespread recognition among OT scholars that intelligent technology are symbolic machines that are profoundly changing the way humans encounter and manipulate the symbolic and an understanding of what these technologies are and how they work. Much of the work required to understand the impact of intelligent technologies on organizing has already been done, of course. There are multiple streams of literature within OT broadly defined and in adjacent literatures that have already theorized the ways organizations are changing due to the introduction of these technologies (including this special issue, of course). It simply requires OT theorists working in the core streams of literature to make the connections and rethink the implications of this work for their theoretical areas.

Change the institutional logic of organization theory

In their influential chapter on institutional logics, Thornton and Ocasio (1999: 804) define logics as “the socially constructed, historical patterns of material practices, assumptions, values, beliefs, and rules by which individuals produce and reproduce their material subsistence, organize time and space, and provide meaning to their social reality.” Institutional logics serve as the organizing principles that shape cognition and behavior within organizational fields. An extensive literature in organization theory has provided a deep understanding of the role of institutional logics in fields and their effects on organizations (e.g. Ocasio et al., 2017), how institutional logics change (e.g. Ocasio et al., 2015), and what happens when more than one logic operates in a field (e.g. Besharov and Smith 2014).

If we think about the academic discipline of OT as an organizational field, then one part of the problem that is preventing scholars from dealing more effectively with intelligent technology is an institutional logic that creates divisions between scholars of technology in organizations and those in other sub-streams of organization theory such as network theorists and institutional theorists. Building on Thornton and Ocasio’s (1999) definition, these “assumptions, values, beliefs and rules” function to “organize time and space, and provide meaning” that constitutes the social reality that OT scholars work in and that shapes what is interesting and what researchers see when they study organizations.

The overriding assumption causing this problem is the belief among many institutional theorists that technology is something an organization has rather than something an organization is. This belief leads many scholars interested in organizations to leave the study of intelligent technology to those interested in technology and to believe that one can study organizations without studying intelligent technology. This belief constructs technology as an epiphenomenon that can be ignored in the study of the process of organizing; a belief that may have been true with previous forms of technology but is no longer valid given the involvement of intelligent technology in social construction. From this perspective, technology is best left to specialists who focus on this aspect of organizations, much like other specialist areas of OT such as the legal aspects of organizing or aspects of organizing that arise when organizations internationalize.

Changing the institutional logic that characterizes OT will not, of course, be easy. Drawing on the research that has focused on changing institutional logics (e.g. Misangyi et al., 2008), it will require institutional entrepreneurs (Pacheco et al., 2010) with sufficient resources who are able to “infuse new beliefs, norms, and values into social structures” (Rao et al., 2000: 240). It will also require field configuring events—“temporary social organizations such as tradeshows, professional gatherings, technology contests, and business ceremonies that encapsulate and shape the development of professions, technologies, markets, and industries” (Lampel and Meyer, 2008: 1056)—where members of the OT community can rethink the logic of the field. This is a tall order, of course. But we have two advantages in our favor. First, the field is characterized by multiple overlapping institutional logics; thus, bringing technology into the core of OT requires only a shift to include elements of the existing logic that characterizes the study of technology in organizations, in OT more broadly, and in adjacent fields like information systems. Second, the fact that intelligent technologies are indisputably a key part of modern organizations creates the sorts of anomalies that often lead to a paradigm shift in science (Kuhn, 1970). The reality of organizations does not fit with our theories in obvious ways, making a change in the underlying paradigm of OT hopefully only a matter of time.

Retheorize the founding theories of OT

Finally, and perhaps most obviously, OT scholars need to retheorize the foundations of mainstream OT. As I discussed earlier, much of the work upon which OT as a field depends was developed in the 1970s and 1980s. This work was all done before much of the intelligent technology that now defines how we organize was developed (or at least before it became ubiquitous). As a result, these theories explain a world that no longer exists and their current formulation therefore limits the power and relevance of the core theories of OT. If we do not go back and rethink these once powerful theories, OT is destined to become less and less relevant and of less and less interest to people interested in understanding organizations and organizing.

What is needed, therefore, is a major program of research to bring the foundational theories of OT into the digital age. This will require a concerted effort, but will be interesting and result in a re-invigoration of the core theories of OT. It will also open up whole new research programs that will provide new and exciting views of organizing with important practical and academic implications. As OT scholars, we need to recognize the problem, create the necessary change in the institutional logic of the field, and then rethink our most basic understandings of organizations and organizing. Admittedly a tall order, but also an important opportunity to move mainstream OT forward.

Conclusions

In this essay, I have argued that mainstream OT has largely failed to recognize and theorize the profound changes that have accompanied the adoption of intelligent technologies in organizations in every sector of the economy, in government, and in not-for-profits. The invention and widespread adoption of intelligent technology has fundamentally changed how we organize, yet there has been only a limited attempt by organizational theorists to understand the implications of this fundamental change, and much of what has been done has remained outside of the core theories of OT.

Intelligent technologies now underpin much of the communication and interaction through which we organize. Intelligent technologies continue to change how we manage and share information, they produce vast quantities of data that fundamentally change how we perceive the world, and recent developments in generative AI mean that intelligent technology now participate directly in social construction in a way that requires a radical rethinking of how we construct all the social-symbolic objects that constitute organizations and their environments.

There are multiple ramifications of this that should concern organization theorists. Not least is the increasing lack of relevance of mainstream OT for understanding organizations and their contexts. These streams of research are rich repositories of understanding developed over decades. While concepts like institution and organizational identity are still useful for understanding organizations, the original theorizations are increasingly detached from the reality of the modern, digitally mediated organization. We need to go back and rethink the theoretical foundations of OT to encompass intelligent technologies if we want to remain relevant.

But at the same time, rethinking the core theories of OT to match the reality of modern organizations is not beyond reach. It simply requires organizational theorists to recognize the problem and to start the process of re-theorizing the basic theories of organization theory to reflect the reality of digital organizing. How, for example, might we rethink theories of organizational culture to include intelligent technologies? What might theories of power and politics look like with intelligent technologies taking their rightful place at the center of processes of organizinge? There are many exciting new questions to explore as we rethink the foundations of OT.

My goal in this essay was to convincingly argue that mainstream OT scholars have an opportunity to include intelligent technology in their theorizing, and unless mainstream OT scholars take up this challenge much of OT will become increasingly irrelevant in a world dominated by intelligent technology. I hope I have done so, and I hope this essay inspires some organizations theorists to join me in rethinking the core theories of OT and in creating a much more explicit shared identity bridging between the community of OT scholars who study technology and the more traditional OT scholars who continue to build theory at the core of OT. I believe this is an exciting project, and even more importantly, that the future of OT literally depends upon it!