The organizational chart hasn’t fundamentally changed since 1855. Geographic divisions. Product lines. Functional hierarchies. Matrix structures. We’ve been reorganizing the same boxes for 170 years, and if we’re honest, most reorganizations are expensive exercises in moving deck chairs while fundamental problems remain untouched.

That model is breaking down, and AI is accelerating its collapse.

Why Traditional Structures Are Failing

I’ve spent two decades inside organizations wrestling with this problem, and the numbers tell a story that’s hard to ignore. 90% of executives say moving to skills-based organizations will require transformation for all functions. The half-life of skills is now less than five years. Nearly 40% of existing skill sets will be transformed or become obsolete by 2030.

Traditional structures can’t keep pace. Geography means nothing when AI enables distributed work. Product silos collapse when agents operate across your stack. Functional hierarchies bottleneck when decisions need hours, not weeks. Matrix organizations create confusion when work flows at AI speed.

Here’s what really happens: every management layer adds translation overhead. Context gets lost. Priorities shift. Decisions that should take hours take weeks because they traverse organizational altitude. You can’t reorganize your way out of this every 18 months.

The Emergence Of Skills-Based Organizations

What’s replacing the traditional model is fundamentally different. Companies are moving from confining work to standardized jobs to creating portfolios where skills flow to projects and teams form based on capabilities actually needed.

Unilever is organizing work into projects and tasks rather than permanent roles. Employees flow through an internal talent marketplace where work finds people rather than people being confined to org chart boxes. Patrick Hull, their VP of future of work, says they’re moving to outputs and skills rather than years with a job title.

This isn’t semantic. It’s structural. In the traditional model, you hire a marketing manager who owns responsibilities regardless of whether they match priorities or actual capabilities. Work gets stuck because the org chart says this box owns that function. I’ve seen brilliant people with exactly the right expertise sit idle while teams struggle with problems those people could solve, simply because the org chart didn’t give them permission.

In a capabilities model, you ask different questions. What skills does this project need right now? Who has those skills? How do we get those capabilities pointed at this problem today, not after a six-month reorganization?

According to Deloitte, 77% of executives say flexibly moving skills to work is critical to navigating future disruptions. But this isn’t just a new reporting structure. It’s a complete reimagining of how work flows.

How Leading Companies Are Restructuring

McKinsey calls this shift “agentic networks.” Instead of org charts based on hierarchical delegation, companies are building work charts based on exchanging tasks and outcomes. A human team of two to five people can supervise 50 to 100 specialized AI agents running end-to-end processes that previously required entire departments.

The constraint isn’t coordination anymore. It’s knowing what needs to happen and having authority to direct resources toward it.

Amazon took a different path. Andy Jassy mandated each organization increase the ratio of individual contributors to managers by at least 15%. This isn’t cost cutting. It’s about decision speed. When AI handles coordination, summarization, and routing, what are all those managers managing? The honest answer: each other.

DBS Bank in Singapore restructured around customer journeys rather than products. According to Harvard Business Review (HBR), they eliminated silos and created cross-functional squads with end-to-end accountability for specific customer experiences. The result was faster innovation and better outcomes because people with relevant skills could collaborate directly without navigating hierarchical boundaries.

What Skills-Based Actually Requires

This requires infrastructure most organizations don’t have. Skills taxonomies that map to real capabilities, not HR’s outdated job categories. Talent marketplaces that surface the right people for emerging problems. Measurement systems tracking contribution to outcomes, not time in seat.

In the old model, your skills are trapped in your job description. You’re a demand planner with deep pricing expertise that could help the commercial team. That knowledge sits unused because pricing isn’t your function. The waste is staggering.

In a skills-based model, the system knows you have pricing expertise. When a pricing problem emerges, you get pulled in. Not permanently. Just to solve that specific problem, then move to the next place your expertise creates value.

Schneider Electric’s Open Talent Market lets employees dedicate 10% of time to projects outside their core role. According to MIT Sloan Management Review, within two years over 13,000 employees participated, completing more than 2,800 projects that would have languished waiting for formal resource allocation.

The Coordination Challenge Nobody Talks About

The hardest part isn’t technology. It’s the loss of clarity that hierarchies provided.

In traditional org charts, you know who you report to, what you’re responsible for, and who’s responsible for what around you. Those boundaries create inefficiency but also psychological safety. You know your lane.

In a skills-based model, your lane keeps changing. This week you lead a pricing initiative. Next week you contribute to a supply chain project. The month after, you’re back to demand planning while helping a team think through market entry. That fluidity creates opportunity but also real anxiety.

Am I doing the right work? Who evaluates my performance when I’m contributing to six projects across four departments? What’s my career path if jobs dissolve into skills?

Organizations succeeding at this learn you can’t just tear down structure. You need clear frameworks for how work gets assigned. Transparent criteria for what good contribution looks like.

New forms of recognition not tied to climbing a ladder that no longer exists.

How Companies Are Actually Making This Work

Companies getting this right aren’t announcing grand reorganizations. They’re quietly testing in single business units, building skills taxonomies, creating talent marketplaces, and measuring what happens when capabilities flow to opportunity.

Mastercard created “skills graphs” mapping actual workforce capabilities. According to Fortune, instead of relying on job titles or old resumes, they use AI to understand what people can actually do based on project contributions, skills assessments, and peer validations. When new work emerges, they quickly identify who has relevant capabilities regardless of department or official role.

W.L. Gore has operated without traditional hierarchy for decades. As Corporate Rebels documents, they have no fixed job titles or bosses. People commit to projects based on skills and interests. Leaders emerge based on ability to attract followers to important work, not appointments from above. They maintain this at over 10,000 employees globally, proving skills-based organizing scales.

The Cultural Shift Required

This raises questions most organizations haven’t grappled with. How do you build culture when teams are fluid? How do you develop people when roles keep changing? How do you maintain institutional knowledge when expertise moves around?

Companies figuring this out are learning important things. Culture comes from shared purpose and values, not from sitting near the same people for years. When people understand what the organization is trying to achieve and why it matters, culture strengthens as teams become more fluid.

Development happens through exposure to harder problems and diverse challenges, not promotions up a hierarchy. When people work on genuinely different challenges with different teams, they build broader capabilities faster than climbing a functional ladder.

Institutional knowledge gets captured in systems and AI, not just in long-tenured employees’ heads. Organizations that systematically document learnings and use AI to surface relevant expertise move faster than those dependent on institutional memory trapped in hierarchies.

What This Means for You

Are you still reorganizing boxes, or fundamentally rethinking what an organization chart is for?

Most companies are in the reorganizing boxes phase. Moving divisions, changing reporting lines, renaming functions. That’s not wrong, but it’s not enough.

Organizations that will win are asking different questions. Not “who reports to whom” but “how do capabilities flow to opportunity.” Not “what’s the right structure” but “what enables fastest learning and execution.”

The practical path starts small. Pick one business unit with a real problem and leaders willing to experiment. Map actual skills, not job titles. Create a lightweight way for work to find people based on capabilities. Measure what happens to cycle time, quality, and engagement.

You’ll learn quickly whether your organization can handle fluid teams. You’ll discover which leaders thrive without positional authority. You’ll see whether your culture can sustain motivation without traditional career ladders.

The Real Question

The org chart served us well for 170 years. It brought order to industrial-age complexity. But we’re not organizing industrial work anymore. We’re organizing knowledge work accelerated by AI, where the challenge isn’t coordination but adaptation, the constraint isn’t execution but judgment, and the opportunity isn’t efficiency but creating entirely new forms of value.

That requires different infrastructure. Different leadership capabilities. Different ways of thinking about what an organization is and how it creates value.

The future of organizational design isn’t better boxes. It’s better flow of capabilities to opportunities, faster learning, and more adaptive structures that reshape themselves as circumstances change.

The question is whether you’re ready to build it, and whether you’re willing to start before you have all the answers.