AI Is Making Your People Faster. It's Making Your Teams Slower.
The 2026 State of Teams report puts a number on it: a $161B 'fragmentation tax' eating into AI productivity gains. Speed without coordination isn't productivity - it's chaos with a faster clock.
New research puts a number on a problem operations leaders have felt for a while but couldn't quite name.
The 2026 State of Teams report surveyed executives and knowledge workers across the Fortune 500 and landed on this: 89% of executives say AI has accelerated speed. Only 6% say they can point to specific ROI across their organisations.
That gap isn't a tool problem. It's a coordination problem.
The report calls it the "fragmentation tax" - the cost of duplicative work, misaligned priorities, and coordination chaos that eats into AI productivity gains before they reach the business. Estimated at $161 billion a year across the Fortune 500. And growing.
The Real Bottleneck Isn't Execution. It's Coordination.
Here's what that looks like in practice.
A manager gets a 40-page AI-generated brief by 10 AM. The designer has produced a dozen concepts before lunch. The engineer has shipped more code in a morning than the team used to see in a week.
On paper, that's a productivity miracle.
In reality, no one knows which brief is current. The design concepts don't match the code. Three teams are racing toward three different launch dates. One VP of Information Security in the report described it as: "We are an orchestra without a conductor."
The report surfaces something important here: knowledge workers spend 80% of their time on collaborative work. But only 24% of AI implementations focus on teams. Almost every AI investment is aimed at individual output - the one metric that's easiest to measure and least connected to organisational results.
Speed without coordination isn't productivity. It's chaos with a faster clock.
The Capability Gap Is Widening Inside Your Organisation
The fragmentation problem isn't just about tools not talking to each other. It's about people not operating at the same level.
55% of executives in the study say AI has widened performance gaps across teams. The "AI haves" - those with better training, cleaner data, and more sophisticated workflows - are pulling ahead fast. Their peers are left stitching together mismatched outputs and hoping leadership approves.
The report calls this an unorchestrated human-AI workgroup. Without a layer that gives managers visibility into what's actually happening across the team - who's doing what, at what pace, toward which goal - AI tools amplify the gap rather than close it.
77% of executives expect AI to create flatter, more cross-functional teams. 61% believe the future is more horizontal. Without a clear view of how work is distributed and delivered across those horizontal structures, coordination is set to get worse before it gets better.
What Top Teams Actually Do Differently
The report identifies three things that separate teams who benefit from AI from those who pay the fragmentation tax.
- They give AI full context. AI tools performing in silos produce siloed outputs. Top teams connect their AI to shared goals, shared timelines, and shared accountability structures - so outputs are aligned, not just fast.
- They design clear workflows for people and agents together. Not 'what can AI do' but 'how do humans and AI move work forward, together, step by step.' The handoffs are defined. The ownership is clear. The orchestration layer exists.
- They build cultures where human-AI collaboration is visible. When one person's AI-assisted output floods a team that isn't equipped to absorb it, their win becomes everyone else's bottleneck. Top teams make collaboration - not just individual output - the unit of success.
The result: top teams cut the fragmentation tax nearly in half.
What This Means for Operations Leaders
If you're leading a delivery team, a GBS function, a BPO operation, or a shared services centre - this report is describing your environment.
Your challenge isn't that people aren't working. It's that you can't see how work is actually moving across the team. Where it's accelerating. Where it's stacking up. Whether the pace of individual output is converting into team-level results.
The report's prescription - shared context, defined workflows, team-level visibility - is exactly what operations intelligence is built to deliver. Not monitoring individual keystrokes. Not generating activity reports for HR. But giving operations leaders a real picture of how work is flowing, where coordination is breaking down, and which teams are genuinely performing versus generating noise.
58% of executives in the study admit they don't know how to measure AI's ROI. That's not a measurement problem. That's a visibility problem. You can't measure what you can't see, and right now most leaders can't see their teams - only their tools.
The Fragmentation Tax Is Optional
Every enterprise will pay some coordination cost. But $161 billion a year across the Fortune 500 is a signal that the cost has become structural.
The fix isn't a new AI tool. It's the layer between the tools and the outcomes - the one that shows leaders where the work actually is, how the team is actually performing, and what's getting in the way of results that matter.
AI gave your people speed. Operations intelligence gives your organisation direction.
The teams that build that layer now will cut their fragmentation tax. The ones that don't will keep funding it.
JC360 is a Workforce and Operations Intelligence platform built for enterprise teams in GCC/GBS, BPO, IT Services, Financial Services, and Healthcare RCM. 270+ KPIs. Real-time visibility into productivity, transactions, capacity, and worktime utilisation across your entire delivery footprint.