The State of Org Design 2026: What Practitioners Told Us

· org-design, operating-model, ai, workforce-planning, future-of-work

Summary

The Organization Design Forum recently published the results of their 2026 practitioner survey, providing a global lens on org design practice, benefits, challenges and opportunities from 207 experienced practitioners representing a multitude of industries and geographies.

I contributed to the ODF 2026 Practitioner Report write-up and analysis of free text (qualitative) questions. What follows is my practitioner take on the findings, not the ODF’s official position.

Two main takeaways. First, the profession has a clear and shared sense of where it needs to go. And second, the gap between that aspiration and where most methodology and tooling sits today is wide.

Here’s what the data shows, and what I feel it asks of us.

  1. The profession knows where it’s heading. Continuous, data-informed, AI-aware design is the clear direction of travel in the survey. The open question is whether frameworks, methodology and tooling can catch up to that aspiration.

  2. The classic Org Design frameworks still hold. The cadence they assume does not. Galbraith’s Star Model, Kates-Kesler and McKinsey 7S dominate the practice. They were cited by more than half of all respondents. While the frameworks remain analytically sound, they were also built for organizations that redesigned every few years, and most organizations now change faster than that. How can we best leverage the fixed time and effort leaders were previously willing to invest in few infrequent big changes, and beneficially apply that same investment across a series of smaller more frequent improvements?

  3. AI is making org design faster without making organizations better designed. Around 40% of practitioners use AI daily for research, synthesis and content. Only 3% report having reimagined an operating model that considers what this new technology means for coordination, collaboration, and human-AI interactions. The productivity gain is real; the structural rethink has barely started.

  4. Practitioners yearn for better org design technology and tooling adoption. Around 60% have experimented with OD-specific technology, yet regular use is far lower. The result is significant quantities of practitioner time being consumed accessing and manipulating data which takes away from the time available for design. While tooling exists, impediments block most from accessing the current connected organizational data that would make continuous design possible.

The Baseline: Classic Frameworks, Built for a Slower World

Respondents were asked to list up to five models or tools from their most recent project. The classic core frameworks dominated. Galbraith’s Star Model was the single most-referenced framework, cited by more than half of those who answered, with Kates-Kesler and McKinsey’s 7S close behind. Proprietary and custom frameworks, capability and value-stream mapping, and operating model approaches followed.

These now classic frameworks are intellectually rigorous and still valid: the Star Model’s alignment logic across strategy, structure, processes, rewards and people holds up as well today as when Galbraith developed it. The issue, as the report itself notes, is that they were conceived for a more stable and predictable organizational context than the one most of us now work in.

In practice that shows up as a deployment problem more than a content problem. The frameworks assume you have time to build a full picture, design a full response, and implement before the environment shifts. Increasingly we don’t. The practitioners I find most effective use a framework like the Star Model less as a template for a once-every-few-years redesign and more as a continuous diagnostic lens. They ask where misalignment is emerging now, and what the smallest targeted adjustment is.

This requires a shift in practice that depends on having a current and reasonably live picture of the operating model, rather than a snapshot that is reconstructed from scratch using interviews and system extracts that are stale by the time they are aggregated.

What you can do: Establish a lightweight operating cadence: a regular rhythm of data review, signal-spotting, and targeted adjustment. The teams doing this well rarely announce a redesign; they help their businesses re-adjust continuously based on need, and it feels like normal operations.

Workforce Planning: What Capabilities and What For

Workforce planning is changing from answering how many headcount and what skills distribution, to a focus on the work and the capabilities required to execute well on it.

These capabilities encode at an organizational level people’s tacit knowledge, domain depth, relationships and judgment built over years. When someone with deep institutional knowledge leaves, the gap frequently surfaces months later as decisions slow and quality slips.

The driver for capabilities stems from a shift in the work. Work that can be fully specified as a set of tasks is increasingly executable by automation and agents. What grows more valuable is the work that resists specification: deep domain knowledge, judgment, contextual intelligence, relationship management, ethical navigation. Understanding which capabilities are needed is much harder than answering how much headcount might be required.

Designing around the dimension of capabilities required to execute on the work, beyond a skills inventory, is one of the frontier challenges for the profession in 2026.

What you can do: Map the work before the people. For a value stream you own, ask what proportion of tasks AI could reliably execute today, what becomes transferable within 12 months, and what the irreducible human core is. Build capability investment outward from that core.

The AI Frontier: Designing Around AI, Not Just With It

This is the most significant opportunity identified in the report: around 40% of practitioners use AI daily, but only 3% report having reimagined an operating model around it.

Many practitioners use AI for org design work. It provides a real productivity improvement by enabling faster research, quicker synthesis, and proposal drafting, but it operates inside the existing model. Adding AI doesn’t question the structure itself.

Designing an organization around AI is a different exercise. Ask yourself:

Along the same lines, only a minority of practitioners are leveraging AI to build or test organizational models. This field is in its early stages, but the survey is clear that respondents themselves name AI and digital technology as the single most significant force reshaping the practice, and a priority for their own development. The 3% reimagining operating models aren’t necessarily further ahead technically; they’ve made a different choice of treating AI as an operating model question, not just a technology implementation one.

What you can do: Audit one value stream end-to-end. For each step, ask whether it’s done by a human, an agent, an automation, or a combination. If you can’t answer that for your own processes, that’s the first gap to close.

Continuous Design: Clear Aspiration, Missing Infrastructure

Achieving the promise of structure and capabilities actually supporting the current strategy.

The survey found strong consensus that org design is moving from a one-off event toward an ongoing, embedded capability. Many practitioners have long strived to enable more continuous, self-adjusting organizations. However, most org design practices are still largely built for big-bang events: large transformation programs, annual reviews, slide-based proposals that move through governance before anything changes. By the time a design is approved, the strategy that prompted it has often moved on.

The survey increasingly suggests that this is less a methodology failure than a data and tooling one. You can’t design continuously if the information you’re designing with sits in several disconnected systems that no one has synthesized. The common pattern: strategy lives in a deck, the org chart in an HR system that doesn’t reflect the flow of work, work and capacity is in spreadsheets, costs in finance, skills in a separate platform with none of them integrated, none giving a connected view of whether the current structure actually supports the current strategy.

This is where tooling is a significant challenge. Around 60% of practitioners have tried OD-specific technology, but regular use is much lower. The tools exist, but sustained adoption and connected data aren’t generally widespread. Closing that gap is what would make continuous design practical rather than aspirational.

What you can do: Start small. Pick one unit and connect four things: its strategic priorities, the teams delivering against them, the work in flight, and the costs. A live, connected view of even one unit is usually enough to show what’s possible across the organization.

Leadership Buy-In: The Design Is a Fraction of the Work

The survey confirmed anecdotal conversations: practitioners’ time is rarely focused into the design work itself. The top challenges in 2026 are leadership buy-in and commitment, implementation and adoption, with significant difficulties in delivering excellent designs within time, budget and capacity constraints.

The intellectual work of design is demanding, but the larger effort is usually navigational: building shared understanding with senior leaders, managing the politics of restructuring, holding momentum through implementation, and demonstrating that the design is working. A specific theme in survey responses singles out that leaders who weren’t involved in a change early enough or exposed to the reasoning behind it, and so resist outcomes they don’t understand. Implementation stalls when the rationale isn’t visible.

What shifts the dynamic is moving from presenting proposals to reasoning with data. When leaders can see the strategic coverage, the capacity distribution and the cost implications, and can test the alternatives themselves, they engage with the logic rather than relitigating the recommendation. The best org design work I’ve been part of was done with the business, not for it.

Strategy-Structure Connectivity: The Most Expensive Gap

In most organizations the connection between strategic intent and structure lives in the heads of a few people. It isn’t documented, isn’t visible to those who need to act on it, and dissolves when those people move on or situations change. A persistent failure point is spending months on a strategy and equally long on a redesign, then discovering years later that the two were never fully aligned.

The fix is better connection. When strategy, structure, work and people sit in the same connected view, the relationship between them becomes visible and testable: propose a structural change and you can see which priorities gain or lose resourcing; when strategy shifts, you can model the implications before committing.

Bringing it Together

The 2026 report points to three interconnected needs.

  1. The classic frameworks’ concepts hold, but they need to be continuously implementable so that they run against live data, not reconstructed from scratch for each design initiative.
  2. Workforce planning needs to organize people around what they’re accountable for and the capabilities to deliver it with depth of domain expertise, not just skills in a system.
  3. The Org Design profession needs to understand how AI reshapes teaming and structure, not just how it speeds up the existing work.

The profession knows where it’s heading. The question the report leaves us with is whether our methodology and tooling are evolving fast enough to get us there.

Exciting times ahead.

Martin Foster is Head of Org Design at TeamForm and a co-author of the ODF’s 2026 Practitioner Report. He works with enterprise organizations in Australia and globally on operating model design and implementing continuous org design practices that are supported by robust modern tooling.

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