by Dr Alexander Fruehmann, LL.M., EMC

Old thinking

I have spent years working with top management teams on culture strategies – diagnosing the current cultural state, uncovering the psychodynamic blockages within their systems, and navigating the often-unspoken dynamics inside boardrooms. Classic and contemporary theories provided a solid foundation, useful up to a point – yet grounded in assumptions of stability that no longer hold in rapidly changing, AI-mediated environments. They are often most coherent in hindsight, but offer limited guidance in the midst of cultural change as it unfolds.

With AI, the lens on culture shifts. Established models can’t simply be carried forward. Complexity resists linear thinking – but that doesn’t mean abandoning structure. It means replacing grand designs with enabling conditions: altering constraints, shifting contexts, and creating the space for new cultural patterns to emerge and be sustained.

I have had to update my own perspectives and practice accordingly – not in isolation, but in active sensemaking with leaders who are facing these shifts in real time. What follows are some reflections that now shape my work with clients navigating an AI-infused organizational reality.

In discussions about organizational culture, the vocabulary remains familiar: values, purpose, belonging, identity. Yet, AI is already changing the silent rules by which companies decide, prioritize, and invest – and, with that, the cultural grammar in which those decisions are embedded. These shifts rarely act in a straight line. They work indirectly – by altering the processes through which meaning is made and decisions are framed in the first place.

Top management that still dismisses this as a “soft factor” overlooks one thing:
When culture shifts, the mechanisms that determine capital allocation, risk assessment, and profitability shift with it. These changes don’t happen in strategy papers, but in the systems whose weightings and filters already co-determine what counts as relevant.

When systems shape meaning without thinking

AI doesn’t just act as a tool – it is a structural change agent. It operates with different selection logics: filtering, classifying, prioritizing – without context, but with consequence. What was once negotiated through implicit cultural practices is now often silently replaced by algorithmic weightings.

And those weightings don’t start at the moment of output – they begin in what Dave Snowden calls “pre-interpretation layers”: the filtering mechanisms that decide, often invisibly, which data is even noticed and which is ignored. Organizations rarely examine these layers, yet they shape cultural reality before any conscious interpretation takes place.

Culture changes most profoundly where no one talks about it – where new assumptions silently creep in. Visibility, evaluation, meaning: these are now often created in systems that don’t explain why they decide, only that they do.

Anyone who thinks only in terms of technology misses the cultural shift: it is not the systems themselves, but their silent defaults, that are reconfiguring the social coordinate system.

When purpose becomes a re-enactment of the familiar

In response to technological uncertainty, many organizations are doing more culture work than ever: new values initiatives, new narratives, new alignment processes. But the effect is often not clarity – it’s reassurance. Cementing what’s already known. Culture work becomes a re-enactment of the familiar – with better branding, but the same mental model.

In Mary Douglas’s words: "Where there is dirt, there is system."¹ Being also a trained psychotherapist, I'd put it this way: what is repressed does not disappear – it resurfaces elsewhere. In many organizations, discomfort with the opacity of algorithmic systems has not been addressed directly; instead, it has been displaced into symbolic culture work – as if refreshing the values on the wall could help make sense of what is actually going on.

Leadership that fails to question this reflex invests in narratives – not in perceptiveness.

The withering “in-between”: when ambiguity is no longer allowed

Cultural rituals have long had a relieving function in organizations: they allowed disagreement without forcing resolution. But systems optimized for efficiency and clarity have no place for these in-between spaces. They recognize patterns – not tension. They produce recommendations – not dissent.

Complexity becomes a problem to be solved rationally. As if ambiguity were a failure rather than a cultural resource². Yet, organizations that can no longer tolerate ambiguity lose the capacity to listen.

Not every tension is a risk. Some are the only insurance against collective blindness.

Who asks the questions when systems deliver the answers?

In many organizations, the quality of decisions is being discussed – often in terms of bias, fairness, explainability. What’s asked far less often: Who, or what, decides which questions get asked in the first place?

As Niklas Luhmann put it: “Meaning is the unity of actuality and potentiality, produced in an operative process of communication.”³ That is: meaning doesn’t emerge individually in the mind, but in exchange. In German, there is the wonderful word "Flurfunk" (literally "hallway radio"), referring to the informal communication channels in an organization – the grapevine – through which information, rumors, and opinions spread outside official structures. Or think of the simple chit-chat before a conference, whether in a physical venue or online. And when that exchange increasingly takes place between systems, the foundations of what counts as relevant begin to shift.

Equally critical is the erosion of questioning capacity – when individuals or teams stop challenging assumptions, not because they agree, but because the system’s outputs have quietly become the default authority. As Hal Gregersen notes in Questions Are the Answer, the quality of the questions we ask determines the quality of the answers we receive – and the courage to keep asking is often the first casualty in a culture shaped by automated certainty. In an article for INSEAD knowledge back in 2021, Prof Roger Lehman and I pointed out how organizational curiosity can be deliberately protected – and how leaders who maintain this space for inquiry, especially under pressure to “just decide,” preserve not only adaptability, but the very conditions for strategic innovation.

The silent rewriting of cultural grammar

Making culture future- and AI-fit does not mean creating new vision statements. It means recognizing the dynamics in which a new cultural grammar is already being inscribed – often unnoticed. Some examples: - scoring models in HR that redefine performance and potential without conscious negotiation; - automated feedback processes that turn conversational culture into standardized check-in routines, flattening the social nuances of recognition or critique; – reports from AI systems that project an appearance of objectivity while embedding unspoken normative assumptions – deciding, in effect, which topics count as “important” or “unimportant.”

The problem is not just that these shifts happen. It is that they are rarely recognized as cultural interventions – and therefore never consciously negotiated. Failing to see them means losing influence over how meaning and belonging are generated in the organization at all.

In practice, this means leadership must create structures where such systemic effects become visible before they harden into the new normal.

What remains?

Cultural shifts driven by AI are not necessarily loud or obvious. They appear in small but consequential patterns: which metrics suddenly take priority; which conversations are shortened or never happen; which decisions no one questions anymore because “the system says so.”

Failing to detect these patterns means losing room for maneuver – often without noticing. Once they are entrenched, however, they are hard to reverse. This should be worrying leadership more than whether the corporate values poster uses the right shade of blue.

This is where leadership teams need to act – to identify, interpret, and deliberately shape these dynamics before they inscribe themselves irrevocably into the cultural foundation and, in doing so, significantly shift decisions, investment priorities, and ultimately value creation.

In our work, we use our own Singularity Deduction Framework (SDF) – not to produce a static snapshot, but to reveal how changes across organizational layers interact, often in ways that reshape cultural patterns long before anyone notices. It gives leadership teams an early view of where AI-mediated processes are beginning to shift meaning-making and decision logics – and where timely, deliberate intervention can preserve both cultural coherence and economic performance. On this basis, once the fog clears and the real patterns become visible, we can have the conversations that matter. Anyone claiming to have ready-made answers in such contexts is, at best, guessing. Far more valuable is the willingness to explore, together, the range of options that the organization’s emerging reality actually makes possible.

For discussing further, feel free to contact me at alex@singularity.inc.

Footnotes:

1. Douglas, M. (1966). Purity and Danger: An Analysis of Concepts of Pollution and Taboo. Routledge.

2. Haraway, D. (1991). Simians, Cyborgs, and Women: The Reinvention of Nature. Routledge.

3. Luhmann, N. (1984). Soziale Systeme: Grundriß einer allgemeinen Theorie. Suhrkamp.