Story highlights
- 47% of US employees say their organization has integrated AI tools
- AI users most often use AI for writing, research, and problem solving.
- Coding and automation users report biggest productivity gains
Organizational adoption of AI is reported to have sharply increased in Q2 2026. 47 percent of U.S. employees now say they are integrating AI tools into their organizations to improve productivity, efficiency, and quality, up from 41 percent last quarter. One in five employees are unsure whether their organization has integrated AI tools, the same as in previous quarters.
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Personal use of AI at work has also steadily increased over the past year. More than half (52%) of U.S. workers now use AI in their jobs, and 30% use it frequently (several times a week or more). 15% use it daily.
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Employees use AI most often for writing, research, and problem-solving
Among AI users, the most common uses for AI are writing and editing (51%), searching or research (49%), and general assistance or problem solving (39%).
These applications can be used across different roles and types of work. They suggest that AI’s most common workplace role remains knowledge support, helping employees create and revise drafts, find information, and address common questions and issues.
More technical or specialized applications, such as coding assistance and automation, are less frequently reported, but each was cited by 16% of AI users. A slightly higher percentage are using AI for data science or analytics (18%) and for creating presentations or slide decks (17%).
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Frequent users use AI more extensively, including for specialized tasks
Frequent AI users are more likely than infrequent users to use AI across all types of tasks and applications measured. Some of the biggest gaps are in widespread general use. In particular, frequent users are more likely than infrequent users to use AI for general assistance and problem solving, writing and editing, knowledge and information management, and email and communication management.
The relative differences are especially large for more technical or specialized applications. Frequent users are nearly three times more likely to use AI for coding assistance (22% vs. 8%, respectively) and automation or process automation (21% vs. 8%) than infrequent users. They are also more than twice as likely to use AI for task, scheduling, and project management (21% vs. 9%).
In other words, frequent users aren’t just using AI more frequently in their most common applications. I also use the tool for tasks where there is a clearer connection between the tool and a specific function of the job.
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Reported productivity gains are highest with the use of task-specific AI
The AI applications that employees use most often are not the ones most strongly associated with increased productivity.
Employees who use AI for coding assistance, automation, and process automation have the highest productivity ratings. More than three-quarters (77%) of workers using AI in each of these ways say it has had a very or somewhat positive impact on productivity. Ratings are nearly as high among employees who use AI to create presentations and slide decks (76%) and those who use it for data science and analytics (75%).
Employees who use AI for common applications also provide positive reviews, but at lower levels. 68% of employees who use AI for writing and editing say they are more productive, as do 65% of employees who use AI for search and research.
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A broad pattern found in this study is that when employees use AI at work, they most often start by creating or researching an application, while more technical or task-specific applications are associated with the highest productivity ratings.
Diverse uses of AI reportedly lead to increased productivity
Employees who use AI for a greater variety of tasks are much more likely to report that AI is having a positive impact on their personal productivity.
Among employees who use AI for one or two purposes, 45% say AI has had a somewhat or very positive impact on productivity. This rises to 66% for those who use it for three to four purposes, 78% for those who use it for five to six purposes, and 90% for those who use it for seven or more purposes.
This relationship alone does not prove that adding more AI applications will have a greater impact. Employees who see more value in AI are more likely to find ways to get more out of it, and some jobs and organizations may have more opportunities to use AI than others.
Still, employees who use AI in more ways are far more likely to report significant increases in productivity. The strongest value will emerge among employees who apply AI to multiple parts of their work, beyond limited or occasional use.
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what it means
Adoption of AI in organizations, which had previously lagged behind the growth rate of personal AI use in the workplace, increased sharply in the second quarter. More employees now say their organization has integrated AI tools, but fewer employees say their organization does not have AI tools integrated.
The stable percentage of employees who don’t know whether their organization has integrated AI indicates that this quarter’s increase reflects an actual increase in adoption, not just increased employee awareness. Yet one in five employees are still unsure, pointing to a continued lack of clarity around key parts of the workforce.
Writing, research, and problem solving remain the most common entry points, and all measured applications were reported to be associated with at least some productivity gains. But the highest ratings are among employees who use AI for more technical or task-specific applications, such as coding, automation, analysis, and presentation creation.
The findings also show that the business value of AI is not just about accessibility or occasional use. Employees who use AI in more ways also report significantly higher value. This suggests that organizations could get more out of AI if employees are supported to apply it to a broader range of job-related tasks, rather than just treating it as a general-purpose writing or search tool.
This pattern is consistent with Gallup’s extensive workplace AI research, which found that organizational integration and manager support are closely tied to enhanced employee recruitment. Access may help employees get started, but the next stage of artificial intelligence in business will depend on employees being able to more specifically, consistently, and pragmatically apply AI to their work.
Learn how to help your employees apply AI more effectively to increase productivity.
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