The Transversal Technician Does Not Yet Have a Name
Every systemic transition generates new professional figures that the system does not yet know how to name. Before the category “data scientist” existed, those performing that work were called statisticians, programmers, or quantitative analysts, depending on their organisational home. The name arrived later, when demand was already high and supply still limited.
The transition described in this series creates a similar demand. It requires individuals who understand the structure of allocative power in financial markets and the technical architecture of foundational models, who can read a balance sheet and a machine-learning paper, who can grasp cognitive systemic risk and translate it into operational terms for a board of directors. This figure does not yet have a precise name. They are called AI strategist, chief AI officer, or AI policy advisor depending on context. None of these labels is adequate.
The absence of a name is structural. Names emerge when a sufficiently large community of peers exists to create a shared identity, a common body of knowledge, and recognised training pathways. None of these conditions has yet been met. Those who occupy this position today do so through improvised trajectories often invisible to the organisations that employ them.
The competitive advantage of this figure is temporary. The window in which transversality is rare is open now. When universities establish dedicated programmes, organisations codify competence profiles, and a stable labour market forms, the advantage of scarcity will disappear. Competence will remain, but rarity will not.
This series of essays is also an attempt to name this figure before the system names it inadequately. The transversal technician is not a generalist. They are someone who has crossed enough domains to understand the structures that connect them without being captured by any of them. Transversality is the condition required to see what specialisation renders invisible.
The longer paper from which this series derives is titled The Infrastructure of Power: Finance and Artificial Intelligence. The title is deliberately dual. The infrastructure of power is finance seen from the outside, and it is also the epistemic position required to see it: the position of those who understand the technical infrastructure and its implications for power. The two readings are the same reality observed from different angles.