The speed problem is not where you think it is The speed problem is not where you think it is Teams have better tools than ever. Drafts happen instantly. Research takes minutes. Execution is cheaper. Yet work feels heavier. Delivery drifts. Decisions drag. People stay busy but the company does not move with the same force. This is not a productivity gap. It is an attention gap. Most organisations keep paying for work in a currency they do not track. The hidden cost of coordination The hidden cost of coordination Work did not slow down. Coordination did. The old model assumed effort plus tools equals output. That model depended on work being mostly linear. A task moved from one person to the next. Decisions stayed close to the work. The cost of alignment was low enough to ignore. Modern work is not linear. It is interdependent. Every meaningful task touches other tasks. Every decision leaks into adjacent teams. Execution is no longer the bottleneck. It is the overhead created around execution. When coordination becomes the dominant cost, you can feel busy while making little progress. What AI changed What AI changed AI did not create this. It exposed it. When you lower the cost of producing work, you increase the volume of work that needs to be evaluated, aligned, and approved. A fast draft creates more drafts. A quick analysis creates more options. A new tool makes it easier to generate more work than the organisation can metabolise. Speed on production multiplies demand on attention. That demand does not show up in dashboards, but it shows up in the calendar, the inbox, and the decision queue. The attention tax The attention tax Attention is a shared budget inside a company. Every message, meeting invite, review request, comment thread, and status check takes a withdrawal. None of them look expensive alone. Together they become the largest unpriced cost in the system. Most organisations track headcount, hours, output, and utilisation. They do not track cognitive load. They do not track context switching. They do not track decision latency caused by too many people being pulled into too many loops. So they scale systems that quietly drain attention, then act surprised when momentum disappears. Why work feels heavier even when tasks are easier Why work feels heavier even when tasks are easier A team can execute faster and still feel slower because the system forces constant reassembly of context. Work arrives through scattered channels. Priorities shift mid week. Decisions get bounced for consensus. Feedback arrives late and changes the definition of done. People spend more time preparing to work than doing the work. The work itself becomes the smallest part of the job. This is why many teams feel like they are always catching up while still hitting most of their deadlines. They are paying an attention tax that turns simple work into heavy work. Decision congestion Decision congestion One common failure is decision congestion. Too many decisions are shared and too few are owned. Responsibility becomes blurry under the label of collaboration. People are included to reduce risk, but inclusion becomes the risk. Decisions circulate, gathering comments, waiting for alignment, returning for more context, then stalling again. Teams do not hesitate because they lack information. They hesitate because authority is unclear. When nobody owns the decision, everyone becomes responsible for commenting. Commentary grows and action shrinks. AI amplifies this pattern because it increases the number of plausible paths. The system produces options faster than the organisation can choose between them. Choice becomes the bottleneck. Context collapse Context collapse Another failure is context collapse. Work jumps across tools and threads. The same topic is discussed in chats, calls, docs, and comments. Meaning does not settle. People keep reconstructing the story because the system never holds it in one place long enough to become stable. AI summaries help, but they sit on top of a broken structure. If the organisation treats context as disposable, people keep paying to rebuild it. The output looks like activity. The cost looks like fatigue. Priority fog Priority fog A third failure is priority fog. Everything is important, so nothing is finished. Work starts easily and ends slowly. Teams operate in permanent mid state. Projects remain open because the system rewards motion, visibility, and responsiveness more than closure. This is not a discipline issue. It is a measurement issue. When the organisation treats responsiveness as performance, attention follows noise. People learn that the safest move is to stay available rather than to finish. Why individual advice does not fix a system problem Why individual advice does not fix a system problem Most productivity advice targets the individual. Better focus. Better routines. Better time management. That misses the point. If the system is designed to fragment attention, the individual cannot win. You can train people to concentrate, but you cannot concentrate your way out of a meeting culture that treats every discussion as necessary. You cannot plan your day out of a decision process that has no owners. You cannot manage your time out of an organisation that changes priorities by the hour. This is a design problem, not a motivation problem. What fast organisations protect What fast organisations protect The companies that feel fast do not run at a higher speed. They run at a lower cognitive cost. They protect attention the way serious engineering teams protect uptime. They reduce the number of decisions that require group input. They define ownership clearly. They reduce channel sprawl. They treat meetings as expensive. They treat context as an asset that must stay intact. They do fewer things at the same time, so the things they do actually move. A different way to think about productivity A different way to think about productivity Productivity is no longer mainly about execution capacity. It is about attention allocation. If you want to understand why teams feel slow, stop asking how long tasks take. Start asking how many times the organisation forces people to switch context before a task can be completed. Start asking how long decisions sit idle because nobody owns them. Start asking how often work gets reopened because the definition of done is unstable. Once you see the attention tax, you see why modern teams can adopt faster tools and still feel stuck. AI is making work cheaper to produce. It is also making it easier to flood organisations with unfinished thinking. The companies that adjust will not feel faster. They will feel lighter. They will move with less friction because they stop spending attention on work that does not compound. The rest will keep buying speed, then paying for it in attention.

This story contains new, firsthand information uncovered by the writer.

The Attention Tax: Why Modern Teams Feel Slower Even With AI

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