There is a cost buried inside almost every enterprise that never appears on a balance sheet. Yet it compounds quietly, year after year, consuming thousands of hours of skilled employee time and quietly undermining the productivity gains that digital transformation was supposed to deliver.
It’s called ‘the coordination tax’ – and it may be one of the most significant, least addressed drains on enterprise performance today.
What Is the Coordination Tax, and Why Does It Matter?
The coordination tax is the cumulative cost, in time, attention, and energy, of aligning people around shared work. Status update meetings. Approval chains. Re-briefing stakeholders who missed a previous conversation. Chasing sign-offs from legal. Figuring out who owns what, and by when.
None of this is productivity itself – it is the overhead of organising the work. And in large, complex organisations, that overhead is enormous. It’s the administrative fog through which all ‘real work’ must trudge, like a marathon runner forced to stop every mile to explain what a marathon is.
Asana’s most recent Anatomy of Work report found that workers spend a significant proportion of their working week on what the company terms “work about work” – coordination activities that consume time without directly advancing business outcomes.
McKinsey research on knowledge worker productivity has similarly found that internal communication and coordination are the activities that consume most of skilled workers’ time.
“There’s a coordination tax to get human beings aligned.”
– Arnab Bose, Chief Product Officer at Asana.
It is a deceptively simple observation, but it points to something most organisations have simply accepted as an unavoidable cost of doing business.
Why Does Cross-Functional Work Create Hidden Productivity Costs?
The coordination tax compounds as organisations scale, and it accelerates as work becomes more cross-functional. This is where operational failure most often originates. Missed deadlines, misaligned expectations, and costly rework are almost never the result of capability failure. They are the result of coordination failure.
The shift to hybrid and distributed working has made this worse. Everyday coordination that once happened organically now requires deliberate, explicit effort. Every handoff must be documented. Every decision must be communicated.
The Microsoft Work Trend Index has consistently shown that meeting frequency and collaboration overhead have risen sharply in the post-pandemic enterprise, with no corresponding increase in reported productivity.
How Can AI-Powered Work Management Platforms Help?
This is where the conversation is shifting – and where the most credible progress is being made. AI-powered work management platforms are beginning to address the coordination tax in ways earlier generations of productivity software simply could not.
The mechanism is the work graph – a structured, dynamic record of how an organisation’s work has been done. Not a document archive or knowledge base. A live data model of tasks, projects, portfolios, approvals, feedback loops, and outcomes.
“That kind of data is catnip for agents,” says Bose, “because agents can go ahead and look through that history of the work graph and get a really good sense for – this particular type of campaign brief document worked really well for the historical 2023 or 2022 campaign.”
When AI agents can draw on that record, they can operate with the institutional context that previously required a human to gather, brief, and maintain. The coordination tax doesn’t disappear, but a significant portion of it gets absorbed by the system rather than by people.
What Happens to Workers When the Coordination Burden Is Lifted?
The productivity argument for reducing the coordination tax is not simply about doing the same work faster, but about redirecting human attention to work that requires human judgment.
This is what some are beginning to call the human dividend of AI-assisted work management – the recapture of skilled time from administrative overhead and its redeployment towards strategic thinking, creative direction, and high-stakes decision-making. That means fewer ‘quick sync meetings’ lasting two hours, and more time doing the work you’ve been discussing.
The World Economic Forum’s Future of Jobs report points to exactly this dynamic: as AI absorbs routine cognitive tasks, the premium on uniquely human capabilities – judgment, creativity, relationship management – rises sharply.
What are the Risks of AI Adoption?
There is a cautionary note worth sounding. AI adoption without the right coordination infrastructure does not solve the coordination tax – it adds a new layer to it.
Organisations that deploy AI tools without grounding them in organisational context find themselves managing a different kind of overhead: reviewing reams of generic output, editing content that lacks institutional voice, and still spending the same time on alignment because the AI has not reduced the confusion – it has simply generated more material to be confused about.
“You’re getting this high velocity, massive reams of text,” warns Bose, “but it’s not actually moving your business forward.” Which is, if we’re honest, sounds eerily like certain meetings we’ve all attended.
Less Talk, More Action
The coordination tax has been accepted as a cost of doing business for so long that most organisations have stopped noticing it. Forrester’s research on enterprise AI ROI consistently highlights the gap between AI investment and realised business outcomes. The evidence points to coordination infrastructure, not model capability, as the primary differentiator between organisations that realise value and those that do not.
The question is no longer whether AI can reduce the coordination tax. The evidence suggests it can.
The question is which organisations will build the infrastructure to make that possible, and which will keep paying a bill they can no longer afford to ignore.
FAQs
What is the coordination tax in the workplace?
The coordination tax is the cumulative time and energy employees spend aligning people around work – through status updates, approval chains, and cross-functional briefings – rather than doing the work itself.
Why is the coordination tax a problem for enterprise organisations?
As organisations grow more complex, the overhead of coordinating across teams, vendors, and approval layers compounds, consuming skilled employee time and driving up the hidden cost of getting work done.
How does AI reduce the coordination tax?
AI agents embedded in work management platforms can automate routine coordination tasks, such as drafting briefs, routing approvals, and surfacing risks, by drawing on an organisation’s historical work data to act with context rather than guesswork.
What is a work graph and how does it help with coordination?
A work graph is a live data model of an organisation’s tasks, projects, portfolios, and outcomes that gives AI agents the institutional context they need to coordinate work accurately and consistently.
What is shared memory in AI work management tools?
Shared memory means that when one employee coaches or corrects an AI agent, that learning is retained and applied for every other team member who uses the same agent – eliminating the need for individuals to repeatedly re-train the same tool.
