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State of the Global Workplace 2026 - The Human Side of the AI Revolution
The technology works. Large language models can draft legal contracts, write code and synthesize research at speeds no human team can match. But those gains are not showing up in the bottom line.
The technology works. Large language models can draft legal contracts, write code and synthesize research at speeds no human team can match. But those gains are not showing up in the bottom line.
So, if the technology isn't the problem, what is?
Gallup's data points to an answer the corporate world has largely ignored: the manager. In organizations investing in AI, the strongest predictor of employee adoption, aside from technical integration, is whether their direct manager actively champions it. Even the most sophisticated neural network cannot overcome an indifferent team leader.
OpenAI would likely agree. In its 2025 enterprise report, the company states: "The primary constraints for organizations are no longer model performance or tooling, but rather organizational readiness and implementation."
The relationship between realized technological gains and great management is not new. A decade ago, researchers at Stanford, Harvard Business School and MIT found that differences in management practices accounted for about 30% of the variation in total factor productivity, the most common measure of the impact of technology on productivity.
For decades, organizations worldwide have struggled to manage people effectively. Now, the financial stakes are far higher. Winning the AI revolution will depend not just on the technology you deploy but also on how well you lead the people using it. This report establishes a global baseline for management effectiveness in the AI era.
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