I have always believed that business performance depends above all on “work design“, or how work is actually done by people. In a way, this is the foundation of what I have called People Centric Operations: designing the organization not around structures or tools, but around the flows of information, decision-making, and collaboration that support the activities of knowledge workers (People Centric Operations: adapting work and operations to knowledge workers).
You may think I’m stating the obvious, but it’s something I’ve noticed frequently in my career: few managers and ultimately almost no one is interested in how work is done. We know the mission and the job description, but no one knows what people actually do to achieve it, their daily tasks, whether imposed or hidden, in all their detail. Yves Morieux said as much in his (excellent) book: “No one really knows what others do in an organization“. (How to Manage Complexity without Getting Complicated). I would even add that not only do they not know what others do, but they also don’t know how they do it either. And what’s more, they don’t care.
When we don’t know what people do or how they do it, we have to admit that it’s very difficult to improve things.
But the approach I proposed, however relevant in principle, comes up against a limitation: the increasing complexity of modern organizations or, worse, their complication. Workflows are multiplying, tools are fragmented, processes overlap, and at a certain point, the people-centric intention, however sincere, is no longer enough.
The Moderna case I mentioned recently (HR and IT merger: Moderna redesigns its organization for and with AI) was, if not a revelation, then at least an illustration of the need to go further and enter a new dimension. The company goes beyond the usual, overused phrase of wanting to “put people back at the center” and is rebuilding its organization around a flow-based approach, using AI to orchestrate work in real time.
In short:
- Business performance depends on work organization that focuses on information flows, decision-making, and collaboration rather than traditional structures or tools (People Centric Operations).
- The traditional approach is reaching its limits in the face of increasingly complex organizations; AI makes it possible to overcome these limitations by dynamically orchestrating tasks and supporting operational agility.
- Moderna is a good example of this paradigm shift: the business has adopted an organization based on flows and collaboration between human skills and technological capabilities, merging HR and IT.
- This transformation is redefining managerial roles, governance, and performance indicators, placing fluid communication, adaptability, and employee experience at the heart of the system.
- Inspired by industrial logic (flows, orchestration, modular configuration), this approach aims to intelligently industrialize knowledge work without betraying the human element, making AI a partner in co-construction.
Think of the organization as a series of flows, not as business silos
When we talk about the digital workplace, I have always criticized the user experience offered by the tools that make it up, whether they are collaboration tools or business tools. Yes, enormous efforts have been made to improve the UI and UX of each application, but the user does not reap the benefits.
Each application improves its own vertical experience within its silo, while the employee’s journey through the tools is cross-functional and therefore cuts across the tools (What (digital) workplace experience for your employees ?).
Some people design silo interfaces, while others experience a journey that cuts across silos.
I applied this logic to the work environment, and Moderna applied it to the design of the organization and work.
In the Moderna case, many people focus on the most striking aspect, namely the merger of the HR and IT departments, without wanting to dig deeper. But that is only the consequence, the tip of the iceberg. The real lesson we can learn from this is that the company is abandoning traditional functional logic in favor of viewing its organization as a series of tasks to be continuously orchestrated. The focus is no longer on “who owns the task” but rather “what human and technological configuration will produce the best result with speed and accuracy”.
In this logic, the merger of HR and IT teams under the responsibility of a Chief People and Digital Technology Officer embodies this desire to bring together those who shape the culture and those who design the technological infrastructure (Why Moderna Merged Its Tech and HR Departments) or, to rephrase it in my own words, the skills and talents, the framework in which they are exercised, and the tools that support the work.
AI then becomes the glue, the invisible orchestrator that enables us to move from a fixed process logic to a dynamic of continuous adjustments where human and artificial intelligence do not replace each other but collaborate. Humans, through their ability to invent, adapt, understand context, and find solutions, and AI, through what is the essence of technology and what it has always done better than humans, namely speed and scalability.
From People Centric Operations to People Centric Operations 2.0: scaling people without betraying them
The ambition of People Centric Operations remains the same: to organize work so that it truly serves people and not the other way around, based on the principle that I have made my own, which is that when a process is not experienced as a service, it serves neither the employees nor the business and therefore, ultimately, neither the customers.
But to achieve this on the scale of a business like Moderna, we need to move beyond the artisanal approach of the original concept as I presented it, and this is precisely what AI offers: not a substitute for humans, but an infrastructure capable of streamlining information flows, contextualizing decisions, and reducing friction in interactions.
Unlike an “AI-centric” vision where machines dictate how organizations are run, the People Centric 2.0 model puts AI at the service of humans. AI does not impose, it enlightens. It does not make decisions for teams, but gives them the means to act more effectively by adapting to the realities on the ground.
After all, AI is just a new colleague.
Middle management: from controller to facilitator of human-AI flows
Such a transformation inevitably raises questions about the role of humans in the system, particularly managers and middle managers.
They are not becoming obsolete, but are instead becoming the guarantors of workflow quality within their areas of responsibility.
They are moving from a role of controlling execution to one of facilitating interaction between employees and between employees and tools. Their mission is to streamline exchanges, prioritize actions according to context, and ensure consistency between business objectives and the reality of the work.
AI is an integral part of execution, not decision-making.
Reinventing the distribution of responsibilities
The HR-IT merger at Moderna inevitably raises the question of the distribution of power and responsibilities. Historically, each department managed its own scope, tools, and decisions. However, in a flow model, value is created through the circulation of information and the ability to make quick adjustments.
The success of such a transformation therefore requires a fundamental review of governance. The priority is not given to function but to quality, workflow efficiency, and impact on collective performance.
By bringing culture and technology closer together, Moderna is redefining its decision-making processes, with agility taking precedence over authority and a kind of territoriality of power.
Learning to measure what matters
Changing the model also means rethinking how we measure performance. Traditional indicators of individual productivity or efficiency are no longer enough. What becomes key is a team’s ability to share information, reduce friction, and adjust priorities in real time.
Moderna will only be able to evaluate the success of its approach by observing the fluidity of flows, the responsiveness of its teams, and the quality of the perceived work experience, rather than by looking at dashboards that measure quantities rather than flows.
The risk of a boomerang effect unless collective intelligence takes over
Integrating AI into operations is not without risk. I said earlier that technology has always brought only two benefits, speed and scale, and that when you digitize a dysfunctional organization, you dysfunction faster and on a larger scale.
Poorly designed automation can therefore amplify existing dysfunctions without eliminating any of them: it can rigidify poorly designed flows, reinforce control mechanisms at the expense of autonomy, and even unnecessarily complicate processes.
Simply “augmenting” individuals with AI will not be of much help if we do not transform work to reap the full benefits (AI in the workplace: going beyond augmentation to actually transform).
But this is precisely where human and collective intelligence must take back control (Does AI spell the end of collective intelligence?). In a people-centric model, AI is not a black box to which we delegate the governance of flows, but a working partner, a co-pilot that learns and adapts through contact with teams.
Every irritant detected, every discrepancy observed, every unmet need becomes an opportunity for mutual learning between users and the machine. By integrating effective feedback loops, valuing feedback from the field, and giving employees an active role in co-designing flows, AI can become a real lever for collective intelligence.
The transformation will only be successful if the organization fosters ongoing dialogue between humans and technology. The key to truly people-centric orchestration lies in continuous collaboration, where everyone learns from each other.
Working together to find the right mix
The real question is not whether AI will replace humans, but how to continuously determine which combination of human intelligence and technological capabilities produces the best result, in the right context, with the right level of quality and agility. Moderna’s primary goal is not “just” to use agents to automate what already exists.
This search for the “best mix” is not set in stone. It depends on the nature of the tasks, the maturity of the teams, and changes in the business and tools. It must be a living process, based on active collaboration between people and machines.
In this logic, AI becomes an adaptive partner, supporting teams in managing complexity while leaving them in control of the decisions that matter. Moderna is experimenting with this model by integrating AI as a workflow orchestration infrastructure, but the real value will only emerge from its ability to continuously adjust the balance between automation, assistance, and human judgment, as closely as possible to the reality of the work.
A very industrial inspiration
I firmly believe that a business always draws inspiration from deep within its DNA when faced with a major challenge. This can be a good thing, as it ensures consistency, but it can also be a bad thing, as it closes the door to ideas from other sectors.
Moderna is at the crossroads of two worlds: that of knowledge workers and that of industry in the traditional sense. A vaccine is designed, but then it has to be produced, and that requires an industrial and logistical approach.
The world of knowledge workers and businesses suffers from a bias: they live in a world of intangible flows that blinds them to the very notion of operational excellence and improvement.
“Peter Drucker noted that during the twentieth century, the productivity of manual workers in the manufacturing sector increased by a factor of fifty as we got smarter about the best way to build products. He argued that the knowledge sector, by contrast, had hardly begun a similar process of self-examination and improvement, existing at the end of the twentieth century where manufacturing had been a hundred years earlier.“
The New Yorker – Slack Is the Right Tool for the Wrong Way to Work
This inspired me to reflect on the concept of People Centric Operations (The open space is not a factory but sometimes you should look at it that way, Knowledge workers, the excluded from operational excellence?and Just because work is invisible, it doesn’t mean that it can’t be improved).
Here, the vocabulary chosen (orchestration, flow) leads me to believe that Moderna’s industrial DNA has inspired the approach in a way, but in an intelligent way.
The idea is very reminiscent of developments in industrial production, particularly with the emergence of flexible production systems, just-in-time, and more recently Industry 4.0.
First, there is the transition from a structured model to a fluid model.
In industry, we have moved from rigid chains, where each position had a defined function, to systems where machines, operators, and algorithms collaborate according to the needs of the moment. Moderna applies the same logic to knowledge work: tasks are no longer assigned to a “function”, but human skills and AI capabilities are dynamically assembled.
Then there is orchestration as a driver of performance.
In both cases, it is orchestration, i.e., the ability to sequence, distribute, and adjust tasks according to objectives and constraints, that replaces the traditional hierarchical organization. It is less the function than the contribution to the value chain that counts.
We also have the primacy of configuration over structure.
The business becomes a configurable system, like a modular production line. These are no longer fixed positions, but activatable resources, human or otherwise, combined on demand. Moderna is thus adopting a vision of programmable organization, where workflows are orchestrated as they would be in an API-driven factory (Will We See the First Programmable Organizations In 2025?).
And finally, we have the role of AI as “conductor”.
In industry, AI and sensors are already driving smart production lines. At Moderna, AI is also becoming a real-time arbitration tool, capable of reallocating tasks, suggesting combinations, and continuously measuring performance. It plays a role similar to that of a MES (Manufacturing Execution System), but applied to human organization.
I would even go so far as to say that when, on the one hand, we rethink work as a flow and, on the other, this forces us to rethink how we measure performance, it inevitably brings to mind Goldratt’s throughput, but that’s a topic that deserves its own article in due course.
I don’t think a 100% tech business could have taken this approach unless, as I always advocate, it stole ideas from sectors that have nothing to do with it.
In any case, Moderna is not just modernizing its organization, it is changing its design framework. We no longer think in terms of role or departments, but in terms of flows, tasks, and dynamic configurations. It is a form of intelligent industrialization of knowledge work with all the challenges that this entails in terms of governance, skills, and meaning.
Bottom line
The evolution towards People Centric Operations 2.0 does not call into question the initial ambition. On the contrary, it reinforces and adds to the requirements. In a world of ever-increasing complexity, staying focused on the work of individuals requires powerful orchestration levers, and AI, when well integrated, can play this role.
But success will not come from a tool or a silo reorganization, but from the ability of businesses to fundamentally rethink their governance, their culture, and the way they distribute power and responsibilities as close as possible to the workflow.
Moderna is paving the way, but success is not guaranteed. However, it shows that it is possible to reconcile technology and people, provided we never lose sight of the fact that it is people, not machines, who remain at the heart of performance.
Image credit: Image generated by artificial intelligence via ChatGPT (OpenAI)
