Certainty Entrepreneurs

Popular Leadership Discourse Between the Industrialization of Reassurance and the Discipline of Inquiry

In the days following the shooting at the 2026 White House Correspondents’ Dinner, the role of the information environment and, specifically, the “conflict entrepreneurs” helping to shape it, re-entered public discussion (Chazan 2026). Commentators pointed, once again, to actors who amplify division, sharpen binaries, and profit from polarization in an already fragile media environment. The diagnosis felt accurate but incomplete: conflict is indisputably an important and troubling aspect of the current informational economy, but it is not the only one that warrants our attention.

Around the same time, I found myself reading two unusually thoughtful and substantive LinkedIn threads initiated, respectively, by cultural anthropologist Corina Enache and complexity scientist Dave Snowden. These threads generated rich and searching comment exchanges and discussions that drew in practitioners, researchers, and organizational scholars from across the globe. Both take aim at sacred cows of practical management thinking: Elisabeth Kübler-Ross’s change curve and Bruce Tuckman’s model of team development (Enache, 2026a; Enache, 2026b; Snowden, 2026).

Together, the threaded discussions trace a pattern that recurs throughout popular management thinking and illuminates how descriptive insights endlessly recirculated by media lose their context and too easily become prescriptive dogma. (Enache continued her brief LinkedIn series to critique three other models – MBTI, Amy Edmondson’s idea of psychological safety, and Kurt Lewin’s unfreeze-change-refreeze model – but my focus here is on the first two only.)

Reading these threads alongside the renewed attention to conflict entrepreneurs pointed for me to a parallel phenomenon. If conflict entrepreneurs thrive by intensifying disagreement, another class of actors thrives by distilling and repeating messages to the point of easy resolution. Rather than inflaming their consumers, they reassure by converting ambiguity into certainty and distribute it at scale, elevated by the very conditions that make their product most appealing.

I view these tireless actors as certainty entrepreneurs, and they dominate popular leadership and self-improvement discourse across platforms and channels. Their tone is assured, their frameworks clean, and their advice often appears straightforwardly actionable. In a more stable world, the appetite for such content would already be substantial; in the current one, it has reached something closer to structural demand.

The World Uncertainty Index, developed by economists at the National Bureau of Economic Research, reached historic highs during the early 2020s and has remained elevated as geopolitical fracture, economic disruption, technological upheaval, and even active conflicts have compounded (Ahir, Bloom, and Furceri, 2022).

These macro-environmental changes are reshaping energy corridors and global supply chains, renewing trade tensions, and fragmenting the post-1945 economic order, all while generative AI is reshaping labor markets at a pace that outstrips institutional adaptation. As workplaces negotiate the unsettled norms of hybrid and AI-augmented collaboration, leaders at every level face the need to address both genuine uncertainty and calculable risk.

Into this condition, certainty entrepreneurs insert themselves as guides, and their influence rests less on the depth of their insight than on their alignment with platform incentives and with the anxieties of the audiences they serve.

I. From Judgment to Visibility

Understanding why certainty entrepreneurs flourish requires attending to the informational environment that sustains them, an environment whose dynamics I have begin to examine in a series of essays preceding this one. Across four recent essays summarized in “From Judgment to Visibility,” I argue that platforms reorganize leadership discourse around visibility, engagement, and repetition, that is, around content that, by being seen, shared, and continually reinforced – and not via evidence-based outcomes – comes to stand in for what is known, tested, and judged (Slocum, 2026a). Certainty entrepreneurs are not anomalies within such a system but its logical outcome.

Platforms privilege content that is immediately legible, emotionally resonant, and easily transmissible, while complex arguments depending on context, contingency, and genuine trade-offs struggle to travel. Today’s popular leadership discourse therefore increasingly rewards those who can compress responses to ambiguity into clear sound bites, aphorisms, and checklists. The more uncertain the macro-environmental conditions, the greater the demand for those who can render it otherwise, and the greater the rewards in attention, reach, and revenue for those willing to supply it on demand.

We’re all familiar with the easily recognizable forms of the content. For example, the LinkedIn carousel that converts a complex psychological framework into a list of tightly formatted “actionable insights,” or the podcast applying a single model with equal confidence to each week’s most-shared headlines, or the short video that distills years of research into sixty seconds of motivational clarity. These formats are not incidental to the message but constitutive of it, allowing the medium to signal that the subject, however knotty, has already been resolved.

More than a matter of style, this is a shift in epistemology. Leadership knowledge becomes less about understanding situations in their particularity and more about asserting confident positions within them. As management reasearchers may recognize, that pressure and the response to it is not new.

Organizational psychologist Tomas Chamorro-Premuzic’s research on leadership selection documents a corresponding and persistent pattern in organizational life. He argues that confidence is routinely mistaken for competence, and the traits that help individuals gain organizational influence – like expressive self-assurance, projected calm, and the appearance of having answers – are largely at variance with those that actually predict effective leadership (Chamorro-Premuzic, 2019).

Algorithmic and digital platforms and channels amplify this distortion at industrial scale. In face-to-face organizational settings, perceptive observers eventually accumulate evidence that relies on demonstrated performance as a basis for building confidence. Yet platforms governed by engagement metrics like shares, follows, and time-on-content have no such mechanism.

The result is a selection environment for leadership ideas in which the most-circulated voices define what leadership knowledge means and can do, and the gap between that definition and what effective leadership actually requires widens with every cycle of recommendation and reach. The machinery for producing, distributing, and monetizing false clarity has never been more efficient, more rewarded, or more actively scaled.

The certainty entrepreneur is, in this sense, less a rhetorical choice than a structural adaptation, well-fitted to an informational environment that has been deliberately engineered to reward exactly the qualities certainty entrepreneurship supplies.

II. The Mechanics of Certainty

A series of LinkedIn posts by Corina Enache and Dave Snowden from April 2026 and the subsequent discussion threads they generated illuminate the mechanics with unusual clarity. What distinguishes them beyond their specific conclusions is the disposition the threads model as exchanges or even, in places, dialogues.

Both authors proceed from genuine curiosity about why the well-known Kübler-Ross and Tuckman frameworks persist and what they actually do, treating the limits of their own critique as part of the argument rather than as details to be managed away. And both trace the familiar arc of models that each emerged from careful observation within a specific domain, only over time to be simplified, linearized, and generalized, and finally applied prescriptively in contexts far removed from its original conditions.

The posts, for example, recount how Bruce Tuckman’s four-stage team-building framework was drawn from a 1965 review of small-group therapy and training literature, not from organizational teams in the field. That origin of the forming-norming-storming-performing process is typically ignored in subsequent applications of the frameworks. As Enache observes, the stepwise description of how individuals come together to form working teams becomes law when context is stripped away. Despite recognizing how the stages were initially observed in specific, bounded settings, leaders are expected to manage and follow the same inevitable sequences in radically different ones (Enache, 2026b). The leader adopting the framework therefore becomes a guide who “holds the map,” shepherding others through predefined phases rather than investigating what is actually happening in the group.

Enache notes that Tuckman himself added a fifth stage in 1977 and later expressed reservations about the framework’s universality, yet that very contextual heuristic was turned into a kind of managerial legislation. The misuse is not, as several commenters in the Tuckman thread on LinkedIn write, incidental to the model’s success but, rather, integral to it.The simplified, inevitabilized version travels quickly and easily because it is simplified and inevitabilized, not in spite of it.

Snowden extends this critique in the case of the five stages of grief model (denial, anger, bargaining, depression, and acceptance) developed by Swiss and American psychiatrist Elisabeth Kübler-Ross and adopted widely in discussions of change and transformation efforts. Building on another initial post by Enache, he argues in both his original re-post and in the exchanges that followed that the model’s durability lies not in its accuracy but in how it serves particular power arrangements. He names the pattern “Augustinian consulting practice,” contending that the change curve has persisted not because practitioners fail to notice its problems but because it actively concentrates interpretive authority in them as the consultant, coach, or leader themself. The logical endpoint of this drift, as Snowden frames it, recasts change management as emotional processing, with the consultant positioned as therapist and the workforce as patients (Snowden, 2026).

Gail Severini, a transformation and change specialist who contributes to the Kübler-Ross thread, offers a complementary diagnosis grounded in decades of organizational experience. She perceptively observes that this processing is precisely how change is often done to employees in organizations carrying industrial-era history and expectations. That imposition without engagement means employees experience challenging announcements as shock and loss rather than as shared purpose-building. The model’s death-and-grief metaphor therefore can be seen to work not because it is accurate but because it mirrors the actual power structure of the transaction (Severini, 2026).

Coach and transformation facilitator Cordula Plassmann, in the Tuckman thread, identifies the systemic consequence with comparable precision. As models come to be treated as law, the system optimizes for prescribed stages, phases, and behaviors, and the model stops serving people and starts serving the machinery (Plassmann, 2026).

Certainty entrepreneurs take precisely these kinds of models and repackage them for continuous circulation. The process is efficient – and this is not accidental. Context is stripped away, caveats removed, sequence and actionability emphasized, and a confident voice attached. The result is an ongoing stream of content that feels both authoritative and accessible, circulating through networks already primed to receive it as such.

In fact, the content enters what has become a highly streamlined distribution machinery. Consider the podcast series revisiting the same frameworks from episode to episode, the weekly newsletter applying familiar insight to the latest headline, the short first-person video clip delivering conviction in sixty seconds, and the carousel or thread recirculating the same ideas to an audience already primed to receive them. Such repetition is not incidental, but is itself the process, and it works precisely because familiarity, amplified by algorithmic recommendation, produces the felt sense of truth.

Lost in the process is the conditionality and context that made the original insight meaningful and the disciplined caution that led the original researcher to acknowledge the limits of generalization. The effect, as Plassmann observed, is that a model originally designed to serve human understanding ends up serving the machinery of content production and distribution instead, and the practitioner who inherits it receives less a tool than a script.

The contrast with how the same frameworks travel through certainty-entrepreneur channels is instructive. Tuckman’s stages, once processed through algorithmic platforms, appear without the 1965 small-group therapy provenance, without his 1977 reservations, and without any of the power-dynamics analysis that Snowden’s reading surfaces. The frameworks are literally restaged as a universal progression with legible waypoints that the confident leader follows and helps others navigate.

Such decontextualization is not acknowledged as a trade-off but presented as the model’s practical value. Enache’s and Snowden’s reminders of the original contexts of the models are, in this view, not supplementary but subversive. It is precisely why their threads stand out from the ongoing flow of LinkedIn and other platform content and inspires the quality of discussion it does, and why certainty-entrepreneur treatments of the same material generate unqualified and ostensibly unreflective shares instead.

III. When Management Models Become Mental Infrastructure

The deeper risk is not only that simplified management models dominate what people read. It is that they come to structure how leaders think before they encounter reality. By the time a team is formed, a change initiative is launched, or a conflict emerges, many leaders are already interpreting what they see through preloaded frameworks. Storming is expected, for instance, resistance is anticipated, and emotional reactions are mapped according to predefined stages.

Importantly, the situation is not first observed and then interpreted. It is instead fitted into an existing template, and the fitting feels natural precisely because the template has been so thoroughly internalized that it no longer presents itself as a frame but as the situation itself.

The mechanism through which this anticipatory framing takes hold is not ordinarily a single encounter with an influential book or seminar. My claim here is about the cumulative effect of daily immersion in exactly this kind of content, that is, across the podcasts, newsletters, carousel slides, and short video clips that recirculate familiar frameworks through digital platforms and professional networks long after their original posting.

Each individual exposure may seems innocuous, even occasionally useful. However, the aggregate effect, compounded by algorithmic amplification and the illusory-truth dynamics that Lisa K. Fazio and a team of psychologists identified, is a gradual pre-stocking of interpretive templates that leaders carry into their organizations and apply, largely unconsciously, at the moments a seemingly recognizable situation appears (Fazio et al., 2015).

The practitioner who has absorbed hundreds of posts about Tuckman’s stages, Kübler-Ross’s curve, or any of the five-step change frameworks that circulate at similar scale and frequency arrives to the situation already primed to recognize it as an instance of the model. That priming is partly cognitive. Crucially, though, it is also motivational, because applying the model confirms competence and applying nothing risks visible uncertainty.

Behavioral psychologist Daniel Kahneman’s groundbreaking work on cognitive ease helps explain the dynamic. Fluent, familiar ideas feel more true than unfamiliar or complex ones, and repeated exposure reinforces this effect, making the most circulated frameworks seem not only useful but correct (Kahneman, 2011).

The consequences compound in predictable ways. Signals that do not fit the model are ignored or reinterpreted, alternative explanations are crowded out, and inquiry gives way to confirmation. What leaders may consider the diagnosis of a given situation becomes, in fact, more of a projection. Platform dynamics deepen the problem, because repetition reinforces familiarity and familiarity produces perceived truth, so that the most widely circulated models become the most cognitively available, chosen not because they are most accurate but because they are most readily at hand.

Theo Niessen, a Dutch organizational scholar responding in the Tuckman thread on LinkedIn, locates the practical stakes of this dynamic with helpful precision. He succinctly writes that the conditions allowing trust and genuine conflict-navigation to emerge are not things a leader can install but arise in micro-interactions. To take a familiar example, leaders must account nearly every day whether they genuinely hear and act on dissent or merely politely absorb it without meaningful change. He goes on to note that trust cannot be engineered but only cultivated through active and intentional participation (Niessen, 2026). Certainty entrepreneurs consistently obscure this inconvenient reality by packaging participation as a stage and trust as an inevitable outcome of following the framework.

IV. The Political Economy of Reassurance

The sustained demand for certainty entrepreneurship is, at its root, an anxiety economy, and the current environment has made that anxiety both more intense and more widely distributed. Geopolitical volatility, from disrupted maritime trade routes to the fracturing of multilateral institutions, has elevated strategic uncertainty to a sustained baseline condition for organizations operating globally.

Economic uncertainty has continued to intensify through successive shocks. These include inflationary aftereffects, interest rate volatility, the restructuring of global supply chains, and the accelerating displacement of job categories by artificial intelligence. The industry analysis of successive Edelman Trust Barometer reports has tracked declining public trust in governments, media, and major institutions across successive years (Edelman, 2025), collectively creating a crisis of legitimacy that makes confident, accessible voices all the more compelling to leaders trying to project stability for their teams.

Within organizations, ways of working that navigate hybrid arrangements, generational transitions, and the introduction of AI-powered tools find leaders and employees alike hungry for orientation, and increasingly willing to accept managed clarity as a substitute for genuine presence, communication, and sensemaking.

Into this environment, certainty entrepreneurs insert the consistent message that the situation is understandable, the path is clear, and you are capable of navigating it. This message carries real value when it is grounded in seemingly actual situational knowledge, since it promises to reduce anxiety, support action, and catalyze momentum. Unverified, though, the message displaces the discomfort required for deeper sensemaking, encourages premature closure, and rewards decisiveness over discernment by providing ready-made outcomes over actual, on-the-ground processes.

The implicit promise of certainty entrepreneurship also rests on the misread structural assumption that turbulence is episodic, a disruption to navigate after which stability can be restored, rather than a permanent operating condition within which leadership must learn to function (Slocum, 2026b). Certainty entrepreneurs offer episodic remedies for structurally persistent conditions, and the gap between the remedy and the reality tends to become visible only once the model has already been applied, the resolution declared, and the next disruption arrived.

As psychological and cognitive science research on social media diffusion demonstrates, emotionally charged and morally framed content spreads more rapidly than neutral or deliberative material (Brady, et al., 2017). Especially when coupled with encouragement, such content travels well whereas ambivalence and complexity do not. The result is a constantly reinforced popular leadership discourse that systematically favors resolution over exploration, and that grows more influential precisely as the environment it simplifies becomes more intractable.

V. The Certainty Machine: AI’s Amplifying Role

Generative AI has introduced a qualitatively new dimension to this dynamic, one that deserves critical scrutiny beyond the enthusiasm or other concerns that usually accompany it. The first and most direct effect is one of the production and sheer volume of content. AI tools have lowered the cost of generating polished, confident-sounding leadership content to near zero, and any certainty entrepreneur can now produce frameworks, summaries, reflections, hacks, and how-to lists at industrial scale in the time it once took to draft a single paragraph.

The infrastructure of reassurance has become, quite literally, automated, and the volume of certainty-entrepreneur content circulating through professional networks has increased accordingly. LinkedIn’s own platform data, widely reported by marketing researchers, indicates that content in LinkedIn feeds generates over 30 billion impressions per month, a figure driven in part by the platform’s creator monetization push and the ongoing generative AI content surge (Simmonds, 2026).

Within this never-ending stream, leadership and management content is overwhelmingly represented. LinkedIn’s own multi-year research with Edelman finds that 56% of target B2B decision-makers apply “thought leadership as part of their vetting process” of services and providers, making it a dominant genre of professional engagement (Edelman-LinkedIn, 2025). If the infrastructure of reassurance was already substantial before generative AI emerged, production costs have been drastically reduced while output volume has expanded, and the ratio of content to genuine contextual grounding has shifted accordingly.

The second effect is subtler and arguably more consequential. Large language models are architecturally disposed toward fluency and coherence. Trained predominantly on human-generated text, including the vast corpus of popular leadership content that platforms have already optimized for engagement and emotional resonance, they produce answers that are confident and stylistically smooth by design. Research from teams of multidisciplinary European and North American social scientists has documented a systematic yes-response bias in major language models (Dentella, Günther, and Leivada, 2023) and social desirability effects that mirror human tendencies toward positive, agreeable responses (Salecha et al., 2024).

Another team, composed of computer scientists and linguists led by Emily Bender, identified the core of this risk in their foundational paper. Language models, put simply, produce convincing, fluent text without any grounding in the truth-value of the claims they articulate, making them generators of confident prose rather than verified knowledge (Bender, et al., 2021). Applied to leadership advice, AI does not introduce new knowledge so much as it operationalizes existing platform preferences at scale, allowing speed, positivity, and stylistic coherence to be delivered on demand.

Considered together, these effects mean that AI has become a kind of certainty entrepreneur in its own right. Leaders who consult a language model about a difficult organizational situation receive structured, confident, and actionable advice within seconds. The model does not say “this depends” unless explicitly prompted toward that response. It also does not surface disconfirming evidence or structural trade-offs as a default. Instead, it delivers managed clarity, and it does so reassuringly, at scale, around the clock, and without institutional accountability.

In making these criticisms, I am not negating the potential value of AI in leadership development, but, rather, identifying a specific and deeply problematic distortion. AI accelerates and scales the informational economy of certainty, making the already dominant tendency toward premature closure of critical thinking and consideration harder to resist and easier, intellectually and organizationally, to justify. In combination with the anticipatory framing mechanisms that I described earlier, this creates a compound reinforcement loop in which certainty-entrepreneur content primes the interpretive template, AI confirms and operationalizes it, and the template is applied to situations that required something more nuanced and demanding.

VI. Disciplined Inquiry over Premature Certainty

This is precisely what makes the posts by Enache and Snowden, and the discussions they generated, notable. They do not offer immediate alternatives in the form of new models or frameworks but reopen the space of inquiry, resisting the very impulse toward premature resolution that certainty entrepreneurs package as their core product.

The comment threads that followed the initial posts extend and deepen both arguments, with practitioners adding from their own experience that what distinguishes effective change or team leadership is precisely what the certainty-entrepreneur frameworks typically strip out. The exchanges demonstrated the value of sustained presence with the group, genuine attentiveness to what a given situation is producing, and the willingness to treat conflict and stalemates as information rather than as phases to manage.

In her initial post and numerous responses to comments in the Tuckman thread, Enache essentially cuts to the core of a problem with the existing and widely-known model. Even if the framework works in a given practitioner’s hands, she argues, it is because of what the practitioner brings to the situation. The emphasis is thus on a quality of attention and judgment that no model automatically supplies, and that can only be developed through experience, reflection, communication, and a genuine willingness to question what one already believes one knows.

Put more simply, the model is often doing less work than the deliberate judgment of the person applying it. That differentiation sheds light on the work of certainty entrepreneurs, who package the model as if the judgment is universally and easily transferable, and it is not.

The threads also stand as an important qualification of the broader critique of platforms as inherently inimical to serious thought. Much of the analysis in this piece, and in my previous “From Judgment to Visibility” articles, documents how platform incentives suppress complexity and reward managed clarity. The Enache and Snowden exchanges demonstrate that this tendency, while structural, is not inexorable. They show, encouragingly, how social media can host genuinely substantive discourse when participants bring analytical rigor, disciplined restraint, and a willingness to engage publicly with difficulty and incompleteness.

More than two dozen practitioners, researchers, and organizational scholars engaged across the two threads, and the quality of those exchanges, from Niessen’s analysis of trust as emergent micro-interaction to Severini’s account of industrial-era power arrangements, illustrates what platform discourse is capable of when it is not organized around the production and distribution of prepackaged certainty.

VII. Beyond Model Critique

The possibility revealed in the threads goes beyond questioning any particular model. Their deeper invitation is to examine the mental models that have been extended from these frameworks over years of accumulated exposure. That is, they foreground the assumptions that groups inevitably pass through in predictable developmental phases, that resistance is a stage to be managed rather than learned from, and that change done to people is eventually accepted through emotional processing.

These are not merely incorrect models misapplied in the wrong context. Rather, they are cognitive structures, reinforced by repetition and platform amplification, that shape what leaders notice, what they ignore, and what kinds of interventions they can even imagine. To question them requires the kind of sustained, organizationally supported inquiry that the Enache and Snowden threads briefly and valuably begin to model.

For consultants as well as leaders, the threads register this call with unusual candor. Severini, the transformation and change specialist, acknowledges that consultants are often complicit in the persistence of inadequate frameworks, not through endorsement but through accommodation. Writing from long experience in change management practice, she speaks of working within power structures that make genuine co-creation difficult while trying to incorporate it at the margins (Severini, 2026).

Such a willingness to name that complicity with existing institutional power and practices, rather than to defend the professional toolkit, is precisely the form of intellectual honesty that certainty entrepreneurs structurally cannot afford and that the platform environment rarely rewards. Both Enache and Snowden resist the temptation to resolve complexity too quickly and make clear the limits of abstraction. In doing so, they implicitly reassert a conception of leadership and consulting grounded in ongoing attention, participation, and judgment rather than in a performance of confidence.

Exceptionally, their posts circulate not because they are reassuring but because they are precise. That precision, offered honestly and without the scaffolding of false resolution, functions as a form of relief for practitioners who have long suspected that the received models, and the mental and behavioral habits those models have built up over decades, do not quite account for what they actually observe.

VIII. Practicing Countercultural Leadership

Certainty entrepreneurs are well adapted to current media conditions and will continue to thrive. My question in calling out their activities is less how to eliminate them and more how leaders can better engage with their unavoidable output. More broadly, my hope is that greater awareness of these dynamics might contribute to a reconception of leadership that makes premature certainty less appealing rather than simply less available. To begin that process, I believe four practices can help, with each operating against the grain of the incentive structures described so far.

The first practice is diagnostic. Leaders need to better and more consistently recognize the difference between insight and the presentation of insight. A compelling or imaginative formulation is not sufficient evidence of its applicability, and a widely shared framework is not proof of its validity. Psychologist Philip Tetlock and consultant Dan Gardner’s research on expert prediction provides a sobering reminder on this point. They argue that calibration, not confidence, is the mark of genuine predictive skill, and expert forecasters who project the most certainty are often among the least accurate (Tetlock and Gardner, 2015). Similarly, a model’s rate of circulation says considerably more about platform incentives than about the model’s own contextual utility, and heavily trafficked frameworks warrant the careful scrutiny rather than immediate acceptance owing to familiarity.

The second practice is temporal, which requires a commitment to active unlearning that entails more than patience. If suspending judgment is an initial step, genuinely interrogating the frameworks that feel most natural needs to follow. In fact, this means that familiarity itself can be seen as evidence of how thoroughly frameworks can be intenralized by those practitioners immersed in platform content, often without their awareness or consent.

Effective leadership often demands slowing the moment between encountering an idea and applying it, approaching each situation with genuine curiosity rather than pattern-matching, and remaining open to the possibility that what looks familiar may be something else entirely. Adaptive leadership, as Ronald Heifetz and his Harvard Kennedy School colleagues argue, involves sustaining productive discomfort rather than resolving it prematurely, and it is precisely that productive discomfort that managed certainty, however attractively packaged, limits by design (Heifetz, Grashow, and Linsky, 2009).

The third practice is relational. Meaningful understanding emerges, as Snowden observes in his LinkedIn comments, from direct engagement with people before exisiting models frame decisions and impose solutions. He helpfully warns against the “first conversation bias” that shapes everything that follows once a change is announced or a direction is set. While this may not be as simple as applying a model, it is more reliable, and it is where the quality of judgment that Enache also identifies as the practitioner’s own contribution actually develops.

To these three, we now need to add a critical posture toward AI-generated advice that interrogates not only its accuracy but its structural tendency to deliver confidence where calibrated uncertainty would better serve the situation. The fluency of AI-generated prose compounds the challenge. An ill-grounded argument delivered with stylistic confidence (not to mention speed and precision) by an AI model is harder to detect than a human expert’s comparably ill-grounded because the absence of hesitation in the AI output actively suppresses the reader’s own impulse to question it.

I write this not to suggest that certainty has no legitimate place in leadership. Reassurance is a genuine human need, and leaders who communicate clearly, act decisively under pressure, and project confidence grounded in real situational understanding often serve their people and organizations well. The problem is not certainty itself but confidence detached from context, resolution packaged without engagement, and reassurance delivered at scale without the judgment that makes it trustworthy.

The current environment makes that distinction harder than ever to sustain. Platforms today reward the appearance of certainty regardless of its grounding, generative AI automates confident-sounding prose on demand, and the genuine pressure to project stability makes it difficult for leaders to resist supplying managed clarity precisely when the situation requires something more specialized, local, and thoughtful.

IX. Earning Certainty

What the platform environment actually requires is a deeper awareness operating across three distinct domains simultaneously: the external context, with its genuine volatility and its patterns that reward close reading; the management tools and frameworks that leaders rely on, each carrying embedded assumptions and contextual limits that their popular presentations suppress; and the mental models through which leaders interpret what they see, often shaped by years of immersion in exactly the kind of platform content this essay has examined. In each of these domains, some things are known, some are genuinely uncertain, and some are uncertain but routinely treated as known. My contention is that the failure to distinguish among them is where most leadership misfires originate.

Psychologists Karl E. Weick and Kathleen M. Sutcliffe’s analysis of organizations managing the unexpected identifies the relevant habits required for such work are not crisis-activation responses so much as continuous baseline disciplines that include a preoccupation with failure, reluctance to simplify, sensitivity to operations, and deference to expertise (Weick and Sutcliffe, 2015).

Each of these habits also requires holding one’s existing interpretations more lightly. That posture allows leaders to remain genuinely curious about what a situation is producing, actively seek evidence that may challenge or disconfirmthe prevailing frame rather than confirming what one already expected to find, and treat the discomfort of not-yet-knowing as the necessary precondition for learning something true. These are precisely the dispositions that certainty entrepreneurs erode by conditioning leaders to expect resolution rather than to attend to the variability that situations are actually producing.

None of this should appear new as aspiration for leaders. The novelty lies in the intensity and breadth of the contemporary environment in which these practices must now be sustained. Rather than serving as neutral hosts of leadership discourse, platforms actively shape its form, its pace, and its perceived authority. Likewise, rather than merely supporting leadership learning and development, Generative AI increasingly automates the production of managed certainty at a scale that makes the disposition toward coming to conclusions and closures of issues too soon harder to resist and easier to rationalize.

Certainty, in other words, must be earned by leaders again and again. It must be tested. In an environment engineered to supply it effortlessly and at industrial scale, maintaining the distinction between certainty that is grounded and certainty that is performed – and then acting on that distinction – is among today’s most consequential leadership practices. That maintenance is not a simplistic, stepwise method. It is a disposition requiring sustained humility about what one already believes, curiosity about what is actually happening in a given situation, and an ongoing willingness to unlearn templates offered through popular leadership discourse that can be ill-fitting and obscure more productive and considered solutions.

*With great thanks to Amy Grace Loyd for her support and generous input on the final version of this article.

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