Workers Say AI Saves 11 Hours a Week - Over One Quarter of the Workweek - But Lack of Context is Eating the Gains, New Report Finds

Glean

Mountain View, CA - June 10, 2026 - Glean’s Work AI Institute, a first-of-its-kind research collaborative with leading AI experts at top universities like Stanford University, UC Berkeley, and Harvard, focused on how AI is changing the way people and organizations work, today released its inaugural Work AI Index, revealing a growing disconnect at the center of enterprise AI: workers are using AI, workers feel more productive, but most companies still are not seeing the promised business impact.

Based on a survey of 6,000 full-time digital workers across the U.S., U.K., and Australia, insights from AI leaders, and analysis of millions of anonymized, aggregated workplace AI interactions, the report finds that 87% of digital workers use AI at work and 75% say it makes them more productive. Yet only 13% say AI has significantly improved their organization’s performance. Workers say AI automation saves them roughly 11 hours a week - over one quarter of the workweek - but much of that time is being lost to hidden human labor, tool-switching, rework, and unverified AI-generated output.

The findings challenge one of the most common assumptions behind enterprise AI strategies: that more AI usage automatically creates more business value. Instead, the report shows that adoption metrics can mask deeper problems - and that spending a greater share of time inside AI tools is associated with worse outcomes, not better ones. Outputs look more polished. Dashboards move up and to the right. Employees feel faster. But without the right context and operating discipline, the gains leak out through rework, cleanup, and unverified output.

The result is a new productivity paradox: AI is making individual work feel faster, while pushing more burden onto employees to supply context, check quality, and stitch together disconnected tools. The Work AI Index identifies two emerging workplace behaviors draining the “AI dividend”: botsitting, the unrecognized work required to make AI usable, and botshitting, the act of shipping AI-generated work that employees have not verified, do not fully understand, or cannot confidently stand behind.

Key findings from the Global Work AI Index

AI is becoming a more central teammate at work. Workers say AI already automates 27% of their work output, and 57% say they want it to automate even more. Sixty-one percent (61%) say AI helps them more with their day-to-day work than their manager does, 52% say it is easier to collaborate with AI than with human coworkers, 55% have sent a digital twin to a meeting on their behalf, and 29% are comfortable with AI being involved in firing decisions.
The AI dividend is being taxed by hidden labor. Workers spend 6.4 hours per week botsitting, or 37% of their AI time, feeding AI context, supervising outputs, debugging errors, cleaning up AI-generated work, and switching between tools. This is higher than the 36% of AI time they spend actually using AI to do work.
The hidden labor is becoming a quality-control problem. 69% of AI users admit to botshitting, including 41% who say they sometimes deliver work they could not explain if asked and 28% who have blamed AI for mistakes they caused.
The workers getting the most value from AI are also the most likely to work around the rules. Among high AI achievers (people who say that AI has improved their productivity and work quality), 54% use unapproved tools or use approved tools in noncompliant ways, 38% downplay AI’s help to their manager, and 36% hide how much AI helps them.
AI tool sprawl is making employees the integration layer. 77% of AI users juggle multiple AI tools each week, 33% use four or more, and 60% rerun the same prompt across multiple tools because the first output was not good enough.
Context-poor AI is driving fatigue, cleanup, and risky workarounds. 53% of workers say important information they need is not accessible from their AI tools. Workers using context-poor AI are more likely to feel worn out by AI (50% vs. 18%), clean up after AI at least weekly (35% vs. 24%), ship AI work they cannot explain (54% vs. 26%), and use unapproved AI tools (53% vs. 21%).
The companies pulling ahead are redesigning work. In transformative organizations, 90% of workers say their employer provides enough AI training and support, compared with 52% at other organizations; 84% say their employer formally rewards AI skills, compared with 48%; and 90% say their employer treats AI as a chance to redesign work, compared with 54%.

“Too many companies are treating AI adoption like a vanity metric - more seats, more prompts, more usage” said Dr. Rebecca Hinds, Head of the Work AI Institute at Glean. “But adoption alone doesn’t equal transformation. If employees are spending the productivity dividend on botsitting and botshitting, companies haven’t eliminated work - they’ve created a new layer of overhead. The organizations that win will be the ones that ground AI in real enterprise context, apply the right guardrails, and measure success by business outcomes, not activity.”

The report suggests the next gap in enterprise AI is not adoption, but the human infrastructure around it. The organizations pulling ahead are not pushing employees to spend more time in AI tools; they are redesigning how work gets done around AI. That means grounding AI in enterprise context, training employees on when to use it and how to verify it, treating workarounds as signals that official tools are falling short, and building governance into daily decisions rather than leaving it on the shelf as policy.

“The next phase of enterprise AI will not be won by the companies that buy the most tools or drive the highest usage numbers,” Hinds added. “It will be won by the companies that make AI part of how work actually gets done, grounded in the right context, measured against real outcomes, and governed in a way that helps employees move faster without lowering the bar for quality.”

The full Work AI Index is available here.

Methodology

The Work AI Index is based on a survey of 6,000 full-time digital workers across the United States, United Kingdom, and Australia, conducted between December 2025 and January 2026. The sample includes 3,000 respondents in the U.S., 1,500 in the U.K., and 1,500 in Australia. Digital workers are defined as full-time workers who perform most of their work on a computer or digital tools. The report also incorporates insights from AI leaders and analysis of millions of anonymized, aggregated workplace AI interactions from the Glean Work AI platform.

About Glean

Glean is the enterprise AI platform that helps everyone work smarter with AI. Glean Assistant gives every employee a powerful enterprise AI assistant that connects to and understands company data via Glean’s Enterprise Graph, and Glean Agents empowers everyone to create, use, and manage AI agents using natural language. Powered by Glean’s search and agentic engine, Glean’s agents automate work across the organization at scale, while ensuring permissions enforcement, full referenceability, governance, and security. With model choice, APIs for customization, and a broad ecosystem of connectors and MCP servers, Glean delivers scalable, turnkey implementation of a complex AI ecosystem on one horizontal platform.

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