For eighteen months, almost all major pharmaceutical companies have announced an initiative related to generative artificial intelligence: accelerating molecule discovery, optimizing clinical trials, automating medical-marketing, conversational assistants for field teams. And for the past few months, a question has been returning with striking regularity to executive committees: should they create a Chief AI Officer position to lead all of this? The most honest answer, in the majority of cases, is no. And it is precisely this answer that deserves to be explained, because it shifts the real subject: that of the capacity of the existing executive committee to govern a transformation that simultaneously affects research, digital, medical, and compliance.
Market Context
The pharmaceutical industry is experiencing a unique moment. Generative artificial intelligence is no longer an isolated innovation lab topic: it is simultaneously entering R&D, where it accelerates the identification of therapeutic targets and molecule design; clinical operations, where it optimizes patient recruitment and trial data analysis; medical affairs and marketing, where it transforms content production and personalization of relationships with healthcare professionals; and support functions, where it redefines the productivity of entire sections of organizations.
Faced with this rapid and transversal diffusion, many companies feel a legitimate need for coordination. The most common reflex consists of creating a dedicated role, a Chief AI Officer, responsible for carrying the AI strategy to the executive committee level. On paper, the idea is appealing: a single entry point, a global vision, faster decision-making. In reality, observing the organizations that have made this choice over the past two years tells a more nuanced and often more problematic story than announced.
Analysis
The first observation is that the Chief AI Officer role, in most pharmaceutical organizations, is born more from mimicry than from a clearly identified organizational need. Laboratories observe what their peers are doing, what big tech companies are doing, and deduce that they too need this position on the executive committee. However, a governance decision that primarily responds to an external signaling logic, rather than a specific internal problem, rarely starts on the right footing.
The second observation, which is more structural, concerns the very nature of AI in a pharmaceutical company. Artificial intelligence is not a department. It is a capability that spans functions with radically different logics, regulatory constraints, and time horizons. AI applied to molecule discovery involves long research cycles, rigorous scientific validation, and a culture of proof. AI applied to clinical trials touches on questions of compliance, data quality, and relationships with health authorities. AI applied to medical-marketing raises questions of information control, editorial responsibility, and relationships with healthcare professionals. Asking a single executive, no matter how competent, to arbitrate directly across these three worlds is like giving them an authority they can only exercise superficially over each of them.
The third observation, and probably the most important for an executive committee, is the dilution of responsibility. When a Chief AI Officer is appointed without their real scope of authority being clarified with respect to the scientific director, the chief information officer, the medical director, and the other committee members, creating the position clarifies nothing: it adds another actor to an already complex decision-making system. AI projects continue, in practice, to be driven by the business lines that have operational control over them. The Chief AI Officer then becomes either a coordination role without real decision-making power, or a function in permanent tension with peers who have not lost their prerogatives on paper but see them challenged in practice. In both cases, the observed result is the same: more confused governance than before the creation of the position, and a highly compensated executive who finds themselves, within a few months, in a position of informal authority without the levers necessary to deliver the expected impact.
This analysis does not mean that AI requires no dedicated governance. It means that this governance is not necessarily resolved by creating a new executive committee position. In several organizations we have observed, the question that actually moved things forward was not "who is going to advocate for AI", but "how must our current executive committee evolve in its way of deciding, arbitrating, and prioritizing, to integrate a technology that simultaneously affects several of its members". This question, which is much less comfortable, is also much more structuring.
Impacts for Leaders
For general management and executive committees in the pharmaceutical sector, this analysis has several concrete implications.
The first concerns the decision sequence. Before considering a recruitment, the question to ask is that of the governance assessment: where are AI-related decisions currently being made in our organization, who arbitrates them in case of disagreement between functions, and is this arbitration mechanism sufficient given the acceleration of the subject? In many cases, the answer reveals that the problem is not the lack of an owner for the subject, but the lack of an effective cross-functional arbitration mechanism between departments that are each already moving forward on AI within their scope.
The second implication concerns the role of the CEO themselves. In organizations where AI integration is going best, it is not a new executive who drives the subject: it is the CEO, or failing that, an existing executive committee member who has recognized cross-functional authority, who personally takes responsibility for moving this file forward at the board level. This does not mean that this executive must become an AI technical expert. It means they must understand the issues well enough to ask the right questions of their scientific director, chief information officer, and medical director, and to make decisions when their priorities clash.
The third implication concerns those cases, less frequent but real, where creating a dedicated role actually makes sense. This mainly happens in two scenarios: when the company reaches a size and diversity of AI initiatives such that an operational coordination mechanism becomes necessary in addition to, and not in place of, the business lines; or when the company makes AI a major strategic differentiator, to the point of turning it into a driver for transforming the economic model itself, and not just a tool for performance improvement. In these configurations, the position created is generally not a "Chief AI Officer" in the sense of a general AI strategy leader, but a much more precisely defined role, with explicit authority and clarified relationships with other executive committee members. The difference between the two situations is not just semantic: it determines whether the created position will strengthen or weaken governance.
Laroze Partners Perspective
Our conviction, built from what we observe in the executive committees we support, is that the question of the Chief AI Officer is rarely the right question to ask first. It is a recruitment question, which logically comes after a governance question, and many organizations reverse this order out of impatience or mimicry.
The right sequence starts with an honest assessment: does our current executive committee have the capacity, in its composition and way of operating, to integrate AI into its strategic decisions? Do the members currently leading AI initiatives, each within their scope, have the means to coordinate their priorities without requiring permanent arbitration from the CEO? Is there a real shared understanding within the committee of the challenges, risks, and opportunities related to this technology, or is everyone moving forward with their own, more or less informed, interpretation?
It is precisely on this type of question that we help general management prepare, before even considering recruitment. When the assessment reveals that reinforcement is indeed necessary, the goal is then to understand what type of profile, with what past experiences, will be able to integrate into this governance without weakening it, and earn the trust of peers who may not have welcomed this recruitment with enthusiasm. This is where the Laroze Pattern® comes in, a method of strategic analysis of career paths, leadership behaviors, and performance dynamics, which allows us to evaluate how a leader has, in the past, managed similar governance situations: did they know how to build their influence within an already occupied decision-making system, or did they need an exclusive mandate and a protected scope to succeed?
Our role, in this type of situation, is not to push for the creation of a position. It is to help leaders ask the right questions about their own governance before looking for an answer externally. In a significant number of cases, this reflection leads to a different conclusion than the one initially considered: not a new position, but an evolution of the mandate of an existing executive committee member, or a targeted reinforcement of an already established function. And in cases where recruitment remains the right answer, it occurs under much better conditions, with a clear mandate and an organization ready to welcome it.
The temptation to create a Chief AI Officer position responds to a real need: that of not undergoing a major technological transformation without leadership. But responding to this need with a reflex creation of a new executive committee position, without first questioning the existing governance capacity, often adds complexity where the challenge is, on the contrary, to simplify decision-making. The organizations that succeed in their AI transformation in the coming years will not necessarily be those that recruited a Chief AI Officer first. They will be those whose executive committees have collectively succeeded in making artificial intelligence a strategic decision subject in its own right, carried by clear governance rather than by a new silo.
Are you wondering how best to integrate AI into your executive committee’s governance, with or without creating a position? Let's discuss your specific situation to identify the most suitable answer for your organization.
