Insights & Analysis
May 8, 2025
How AI Is Redefining Organisational Structure, Not Just Job Roles
The real disruption isn’t automation, it’s reorganisation
1. The Wrong Conversation
Much of the public discourse around AI and work still revolves around a narrow question: Which jobs will be replaced?
But this frame misses the bigger shift underway.
Yes, generative AI and intelligent agents are transforming how tasks get done. But the deeper disruption is structural: how AI changes workflows, decision rights, power dynamics, and the very architecture of the organisation.
The question isn’t just what work gets done. It’s how work gets organised, and who gets to do it.
2. The Rise of “Boundaryless” Work
Historically, organisational design has served a coordination function. It answers questions like:
Who owns which processes?
What’s the reporting line?
Where does expertise reside?
AI, especially in the form of multi-agent systems, is now challenging those answers in three ways.
1. AI Agents Cut Across Functions
Agentic AI systems are increasingly capable of planning and executing tasks that span departments. Consider an AI agent that:
Pulls product performance data
Analyses customer reviews
Generates marketing copy
Pushes a test campaign live
That’s market research, analytics, content, and marketing ops all in one loop. Who “owns” that flow? What team does it sit under?
As Gartner notes, agentic AI will increasingly act as a digital coworker, capable of collaborating across silos and making decisions autonomously
2. Decision Layers Flatten
AI doesn’t just speed up execution, it collapses time and hierarchy. Where a task once required layers of review, coordination, or escalation, AI enables near-instant recommendations, forecasts, or actions.For example:
OpenAI’s Operator platform runs agents that plan, act, and coordinate across internal systems—delivering outputs that previously required cross-functional meetings and human orchestration .
BBVA’s use of thousands of internal GPTs has decentralised decision-making, allowing employees at every level to generate insights or content without central approval bottlenecks
3. Expertise Gets Rewritten
In a GenAI-enabled team, the most effective contributor isn’t always the subject matter expert. It might be the person who knows how to prompt, verify, and deploy AI outputs most effectively.
That’s a challenge to traditional notions of expertise, tenure, and status.
It also opens the door to “horizontal upskilling” where skills like workflow design, critical reasoning, and AI interfacing become more valuable than deep vertical specialisation.
3. Leading Through Structural Disruption
If AI is breaking down organisational boundaries, leaders need to rebuild systems around a new kind of agility. Here’s how:
✅ 1. Map the Invisible Workflows
Start by identifying where AI is already reshaping collaboration. Look at:
Which teams are deploying agents or assistants?
Where is AI bridging previously siloed tasks?
Which workflows are getting faster, but less transparent?
This gives you a heatmap of emerging shadow structures: the informal systems AI is creating beneath the org chart.
✅ 2. Shift from Roles to Capabilities
Traditional org design defines people by roles. But AI amplifies capabilities: pattern recognition, synthesis, rapid iteration.
Consider creating dynamic project pods built around:
AI literacy
Domain fluency
Orchestration skill
This encourages flexible, cross-functional collaboration based on who can move value fastest; not who reports to whom.
✅ 3. Reframe Authority and Accountability
As AI agents make more decisions, leaders must clarify:
Where does AI have agency?
When must a human intervene?
Who owns outcomes when AI acts?
These aren’t just technical questions, they’re governance imperatives. And they require new thinking about what it means to lead in an AI-enabled environment.
✅ 4. Invest in Cross-Functional Fluency
AI adoption often stalls at the interface between teams. Eg. when marketing hands off to tech, or legal needs to review outputs.
Forward-thinking organisations are investing in translators: people who can bridge business, data, and process. These “AI integrators” will become critical nodes in the new structure.
The Org Chart Is Going Fluid
We’re entering a phase where the formal structure of companies will start to diverge from how work actually gets done.
AI is accelerating that divergence. It’s creating:
Faster workflows that bypass legacy hierarchy
Agents that span domains without permission
Teams that rely more on orchestration than ownership
For leaders, the takeaway is clear:
You don’t need to fear job loss. You need to manage structure loss.
The companies that win won’t just adopt AI tools. They’ll rebuild the way their organisations work with more fluidity, more cross-functionality, and more human-machine partnership at the core.
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