Table of Contents
Story highlights
- 47% of US employees say their company has built-in AI tools
- AI users most often use AI for writing, research, and problem solving
- Coding and automation users report the biggest productivity gains
Reported organizational adoption of AI increased sharply in the second quarter of 2026. 47 percent of U.S. employees now say their company has integrated AI tools to improve productivity, efficiency or quality, up from 41 percent last quarter. Compared to previous quarters, one in five employees remain unsure whether their company has integrated AI tools.
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The individual use of AI in the workplace has also increased steadily over the past year. More than half of the US workforce (52%) now uses AI in their role, with 30% using it frequently (a few times a week or more). Fifteen percent use it daily.
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Employees most often use AI for writing, research, and problem solving
Among AI users, the most common uses of AI are writing and editing (51%), searching or research (49%), and general support or problem solving (39%).
These applications can be used for many roles and types of work. They point out that the most common role of AI in the workplace remains knowledge support: helping employees create, revise, search for information, and solve common questions or problems.
More technical or specialized applications are less commonly cited, including coding assistance and automation, each cited by 16% of AI users. Slightly higher proportions use AI for data science or analysis (18%) and for creating presentations or slides (17%).
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Frequent users use AI more broadly, including for specific tasks
Frequent AI users are more likely than infrequent users to use AI for all types of measured tasks and applications. Some of the biggest gaps exist in broad, general uses. In particular, frequent users use AI more often than infrequent users for general support or problem solving, writing and editing, knowledge or information management, and email or communications management.
The relative differences are particularly large for more technical or specialized applications. Frequent users are almost three times more likely than infrequent users to use AI for coding assistance (22% vs. 8%) and for automation or process automation (21% vs. 8%). They are also more than twice as likely to use AI for task, planning or project management (21% vs. 9%).
In summary, heavy users do not simply use AI more often for the most common applications. They also use it for tasks where there is a clearer connection between the tool and a specific function of their job.
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Reported productivity gains are highest for task-specific AI applications
The AI applications that employees use most often are not the ones most associated with productivity improvements.
Employees who use AI for coding support and automation or process automation receive the highest productivity ratings. More than three-quarters of workers who use AI in each of these ways (77%) say AI has had an extremely or somewhat positive impact on their productivity. Ratings are almost as high among employees who use AI for creating presentations or slide decks (76%) and for data science or analytics (75%).
Employees who use AI for general applications also give positive reviews, but at a lower level. 68% of employees who use AI for writing and editing say it has improved their productivity, as do 65% of those who use it for searching or research.
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The broader pattern observed in the study is that employees who use AI at work most often start with writing or researching applications, while more technical or task-specific applications are associated with the highest productivity ratings.
Greater diversity of AI usage is associated with higher reported productivity
Employees who use AI for a wider variety of tasks are also significantly more likely to report that AI has a positive impact on their personal productivity.
45% of employees who use AI for one or two purposes say it has had a somewhat or extremely positive impact on their productivity. For those who use it for three or four purposes it is 66%, for those who use it for five or six purposes it is 78% and for those who use it for seven or more purposes it is 90%.
This correlation alone does not prove that adding more AI applications will have a greater impact. Employees who see greater value in AI may be more likely to find additional opportunities to use it, and some jobs and organizations may offer more opportunities for AI use than others.
Still, employees who use AI in more diverse ways are significantly more likely to report significant productivity gains. The greatest value will be seen among employees who go beyond limited or occasional use and use AI in multiple parts of their work.
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Implications
Enterprise AI adoption increased sharply in the second quarter, having previously lagged behind the growth rate of individual AI usage in the workplace. More employees now say their organization has built-in AI tools, while fewer say it doesn’t.
The consistent proportion of employees who don’t know whether their organization has integrated AI suggests that this quarter’s increase reflects real growth in adoption, not just greater employee awareness. Yet one in five workers remains uncertain, indicating a continued lack of clarity for a key portion of the workforce.
Writing, research, and problem solving remain the most common entry points, and all measured uses are associated with at least some reported productivity gains. However, employees who use AI for more technical or task-specific applications, including coding, automation, analysis and presentation creation, score the highest.
The results also show that the business value of AI does not just depend on accessibility or casual use. Employees who use AI in more diverse ways also report significantly greater benefits. This suggests that companies may get more out of AI by helping their employees apply it to a broader range of job-related tasks, rather than just using it as a general writing or search tool.
This pattern is consistent with Gallup’s broader AI in the workplace research, which has found that organizational integration and manager support are closely linked to greater employee acceptance. Access may make it easier for employees to get started, but the next stage of artificial intelligence in business will likely depend on helping them apply AI in their work in a more targeted, consistent and practical way.
Discover how you can help employees use AI more effectively to increase productivity.
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https://www.gallup.com/workplace/712736/organizational-adoption-jumps-six-points.aspx
