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Managers Using AI Daily Report The Highest Coordination Burden, New Study Finds

Despite 86% AI adoption, managers lose an average of 16.5 hours each week to meetings, re-explaining work and searching for information, suggesting AI has yet to solve management's coordination problem.

Allwork.Space - PressbyAllwork.Space - Press
July 31, 2026
in Press
Reading Time: 3 mins read
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Managers Using AI Daily Report The Highest Coordination Burden, New Study Finds

Despite 86% AI adoption, managers lose an average of 16.5 hours each week to meetings, re-explaining work and searching for information, suggesting AI has yet to solve management's coordination problem.

HELSINKI, Finland (July 28, 2026) In Parallel, the company building the shared context for modern work by connecting meetings, decisions and organisational knowledge to enterprise AI, today released findings from its inaugural Coordination Tax Index, revealing that managers using AI most heavily also spend the most time coordinating work. The findings suggest that while AI has improved individual productivity, it has yet to solve the structural management challenges that consume more than two working days each week for the average manager.
Managers reported losing an average of 16.5 hours every week, which is equivalent to approximately $64,600 per manager each year, to status meetings, repeatedly explaining the same context and searching for information that already exists. The report describes this hidden organisational cost as the coordination tax – the time organisations spend keeping people, decisions and work aligned before meaningful work can happen.
The findings also challenge assumptions about AI adoption, which reached 86% among the managers surveyed. Daily AI users reported spending an average of 20.3 hours every week on coordination activities, compared with 9.1 hours among managers who do not use AI. Rather than suggesting AI creates additional work, the findings point to a different conclusion. Today’s AI isn’t falling short because models lack capability, but because they lack the shared organisational context needed to understand what teams have already decided, discussed or committed to. While AI has become highly effective at helping individuals complete tasks, it remains far less effective at helping organisations coordinate work across teams, systems and functions.
“Everyone expected AI to eliminate busywork. Instead, we’re seeing organisations invest in increasingly capable AI while managers continue spending enormous amounts of time simply keeping work aligned,” said Markku Mäkeläinen, CEO and co-founder of In Parallel. “Our customers tell us they didn’t invest in AI just to work faster. They invested because they expected it to reduce the time spent chasing information, rebuilding context and coordinating work. That’s what managers are really asking for, and AI becomes far more valuable when it understands what the organisation already knows.”
The research also found managers consistently underestimate the scale of the problem. While respondents believed coordination consumed around 21% of their working week, their own itemised responses showed it actually accounted for 41%. Nearly half of that time was spent in status meetings, with the remainder divided between re-explaining context and searching for information scattered across documents, chat platforms, emails and meeting notes.
To reduce the coordination tax, In Parallel has developed an AI context layer that connects organisational knowledge, meeting decisions, project history and ownership information into shared context that both people and AI can understand. By giving AI access to the information that already exists across an organisation, the company helps managers spend less time searching for information, reconstructing decisions and coordinating work, allowing teams to move more quickly from decision to action.
“The next generation of enterprise AI won’t be defined by better models alone,” said Kristian Luoma, co-founder of In Parallel. “It will be defined by how well AI understands the organisation it’s working inside. Companies already have the knowledge they need to make better decisions. The challenge is making that knowledge available to every person, and every AI system, at exactly the moment it’s needed.”
The report also found managers believe AI assistants with access to shared organisational context could save an average of 4.4 hours every week, or 27% of the coordination tax. This suggests that context – not model capability – is becoming the next frontier for enterprise AI.
The inaugural Coordination Tax Index surveyed 247 managers across the United States, the United Kingdom, Canada, Australia and Germany. To learn more about the Coordination Tax Index and download the full report, visit https://in-parallel.com/coordination-tax/. To learn more about In Parallel’s enterprise solutions, visit in-parallel.com.
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