As AI increasingly supports report writing, data analysis, document summarization, and the automation of repetitive tasks, office workers have more opportunities to complete their work faster. Tasks that once took several hours can now be completed in significantly less time with the assistance of technology.
However, improvements in speed do not necessarily mean employees experience less pressure.
As productivity expectations rise, businesses may set higher targets, assign additional responsibilities, or require employees to take on more complex tasks. In this context, a new question emerges: If employees fulfill all their responsibilities with the help of AI but are unwilling to take on work beyond their assigned duties, should this still be considered Quiet Quitting?
The development of AI is bringing new perspectives to the concept of Quiet Quitting. The issue is no longer simply whether employees are willing to do more than what is required. It also concerns how businesses evaluate performance, distribute the value created by technology, and foster employee engagement in the workplace.
What Is Quiet Quitting, and Why Has It Attracted Attention?
Quiet Quitting does not mean that employees actually resign or terminate their employment contracts.
The term describes a situation in which employees remain in their jobs but limit their contributions to their formally assigned responsibilities, rather than continuously taking on additional tasks or spending more time working outside regular hours.
The concept gained popularity on social media in 2022, as employees became increasingly concerned about work-life balance, mental well-being, and the meaning of work.
However, Quiet Quitting does not always indicate a lack of responsibility.
An employee who performs well during regular working hours, does not frequently work overtime, and declines requests outside their agreed scope of responsibilities is not necessarily disengaged. This may simply reflect their decision to establish reasonable professional boundaries.
Conversely, if employees perform only the minimum required work, no longer care about shared outcomes, limit collaboration, or show little interest in contributing ideas for improvement, these behaviors may indicate declining engagement with the organization.
This distinction is important because businesses need to differentiate between employees who actively protect their personal time and those who have genuinely become disconnected from their work.
According to Gallup's State of the Global Workplace 2025 report, global employee engagement declined from 23% in 2023 to 21% in 2024. Gallup estimated that this decline corresponded to approximately $438 billion in lost productivity worldwide.
Although low engagement rates cannot be directly interpreted as Quiet Quitting rates, these findings show that declining employee engagement remains a significant challenge for organizations.
How Is AI Changing the Way Employees Perceive Their Work?
1. Completing Work Faster Does Not Necessarily Mean Having Less Work to Do
One of the most prominent benefits of AI is its ability to reduce the time spent on repetitive tasks.
Employees can use AI to prepare document drafts, summarize information, process data, or assist in creating reports. This allows them to devote more time to activities requiring critical thinking, creativity, and decision-making.
However, how businesses use the time saved can significantly influence the employee experience.
If every productivity improvement leads to additional assignments, employees may feel that using AI effectively only increases their workload and responsibilities.
For example, an employee who previously needed three hours to prepare a report may now complete it in just one hour with AI assistance. If the two hours saved are immediately filled with new tasks without adjusting priorities or expectations, the benefits of technology may become less apparent to the employee.
According to Microsoft's 2025 Work Trend Index, 53% of surveyed leaders believed productivity needed to increase, while 80% of surveyed employees and leaders reported lacking sufficient time or energy to complete their work.
These figures reflect a gap between organizations' growing productivity demands and the limits of human capacity.
In this context, Quiet Quitting may be understood as a response to continuously increasing work expectations rather than simply a refusal to make an effort.
2. AI Is Changing the Standards for Evaluating High-Performing Employees
In the past, in some workplaces, employees who frequently worked overtime, handled numerous tasks, or responded to work-related requests outside regular hours might have been regarded as highly dedicated.
However, as AI supports many routine activities, the amount of time spent on a task no longer fully reflects the value an employee creates.
Someone who uses AI effectively may complete work faster than colleagues while maintaining the same level of quality. Conversely, spending more time working does not necessarily lead to better results.
This creates a need to reconsider how employee performance is evaluated.
Businesses should place greater emphasis on output quality, problem-solving abilities, critical thinking, and contributions to shared goals, rather than relying solely on working hours or the number of tasks completed.
If performance evaluation systems continue to prioritize visible signs of busyness, employees may have little incentive to openly share improvements that help them work more efficiently.
Therefore, the emergence of AI is making the boundaries between fulfilling responsibilities, working efficiently, and being disengaged increasingly complex.
3. Fear of Being Replaced by AI May Reduce Employee Engagement
AI not only creates opportunities to improve productivity but also raises concerns about the future of employment.
As certain tasks become automated, employees may question the value of their expertise, their ability to maintain their current positions, or the skills they need to develop for the future.
If businesses implement AI without clearly explaining their objectives, employees' roles, and workforce development plans, feelings of uncertainty may increase.
A 2025 study involving 395 employees working in information technology and IT support services in India identified relationships between certain forms of AI anxiety, technostress, and Quiet Quitting intentions.
These findings do not mean that AI directly causes employees to lose motivation in every workplace. However, the study suggests that psychological factors and the way organizations implement technology should be considered alongside productivity benefits.
When employees do not understand whether AI will support or replace their roles, they may become less proactive, hesitate to propose initiatives, or focus solely on completing mandatory tasks.
4. Employees Are Using AI to Maintain Work-Life Boundaries
From another perspective, AI can also become a tool that helps employees manage their workloads more effectively.
By automating repetitive activities and supporting information processing, employees can reduce the time spent on low-value tasks, limit overtime, and devote greater attention to important work.
In such cases, employees' unwillingness to extend their working hours does not necessarily reflect declining engagement.
They may remain proactive, responsible, and productive while maintaining clear boundaries between their professional and personal lives.
This is an important distinction for businesses to recognize.
Working more efficiently to create additional time for rest does not mean reducing one's responsibility toward work.
Without recognizing this difference, businesses may unintentionally undervalue employees who are using technology effectively.
What New Forms Can Quiet Quitting Take in the Age of AI?
In traditional workplaces, Quiet Quitting is often discussed in terms of employees limiting overtime, declining additional assignments, or reducing their participation in activities beyond their core responsibilities.
In AI-enabled workplaces, behaviors associated with employee engagement may become more difficult to identify.
An employee may continue completing tasks on time, maintaining output quality, and meeting assigned performance targets with AI assistance, while no longer showing interest in improving processes, sharing knowledge, or helping solve broader organizational problems.
Conversely, an employee who refuses overtime but actively proposes ways to apply AI, supports colleagues, and contributes innovative ideas may still be highly engaged with their work.
This suggests that businesses should not evaluate Quiet Quitting solely through working hours, task completion speed, or employees' willingness to accept additional assignments.
Instead, organizations need to consider factors such as accountability, collaboration quality, initiative, trust, and employees' perceptions of the meaning of their work.
In particular, AI may help employees maintain performance on routine tasks even when their psychological engagement has declined. This is a possibility that requires further research and monitoring, rather than assuming that employees who frequently use AI or complete tasks quickly are engaging in Quiet Quitting.
Why Doesn't AI Adoption Necessarily Solve Employee Engagement Problems?
A common assumption is that when technology reduces repetitive work, employees will have more time for meaningful tasks and consequently feel more satisfied.
This may happen, but it is not an automatic outcome.
If employees' lack of motivation stems from unfair performance evaluation systems, limited career development opportunities, relationships with managers, or organizational culture, introducing AI tools is unlikely to fully resolve the problem.
According to a Gallup analysis published in 2026, employee engagement in the United States reached 31% during the first half of the year, unchanged from 2025, even as workplace AI adoption continued to expand.
The research also indicated that simply providing access to AI is insufficient to improve the employee experience. Organizations with clear AI integration plans and active managerial support generally reported higher engagement levels.
Specifically, engagement reached 48% among employees who said their managers actively supported AI use, compared with 30% among those who did not report receiving such support.
This represents an observed association in survey data, not proof that managerial support alone caused the entire difference.
Nevertheless, the findings suggest that how AI is implemented and managed may be just as important as the technology itself.
If businesses focus only on whether employees use AI without considering their experiences, development opportunities, and work expectations, the risk of disengagement may persist.
What Should Businesses Do to Maintain Employee Engagement in the Age of AI?
Evaluate Performance Based on Value Created
Businesses should gradually shift their focus from monitoring how busy employees appear to evaluating actual results.
Criteria such as work quality, problem-solving ability, goal achievement, and contributions to overall organizational performance should be clearly defined.
This helps reduce situations in which employees feel compelled to constantly appear busy to demonstrate their competence.
At the same time, businesses need to distinguish between fulfilling assigned responsibilities effectively and making contributions beyond the formal scope of work, avoiding the tendency to turn voluntary efforts into default expectations.
Be Transparent About AI Use and Productivity Expectations
When implementing AI, businesses should clearly explain why the technology is being introduced, which tasks it can support, and how employees' roles may change.
If AI helps save time, organizations should establish reasonable principles for allocating the additional capacity created.
Some of this capacity can be used to improve work quality, learn new skills, develop initiatives, or reduce pressure during peak workload periods.
More importantly, raising productivity expectations should be accompanied by realistic assessments of employees' workloads and available resources.
Invest in Skills and Career Development Opportunities
AI may change the skills businesses need in the future.
Therefore, rather than simply requiring employees to use new technology, organizations should help them understand how AI works, learn to verify its outputs, and develop capabilities that are more difficult to replace, such as critical thinking, communication, creativity, and decision-making.
When employees see opportunities for career development, they may have stronger reasons to actively participate in the transformation process.
Build an Environment That Encourages Communication and Feedback
Employee engagement cannot be fully assessed through performance metrics alone.
Businesses need to maintain regular conversations to understand the difficulties employees face, how they perceive their workloads, and what concerns they have as AI becomes integrated into work processes.
This feedback should be taken seriously, rather than automatically interpreting employees' reluctance to accept additional tasks as a lack of dedication.
An environment where employees can openly discuss expectations, responsibilities, and work boundaries may help organizations identify problems earlier.
Distribute the Benefits of AI-Driven Productivity Fairly
When AI helps businesses improve productivity, the important question is not only how much additional value the organization can generate, but also how those benefits are distributed.
Businesses can use productivity gains to improve product quality, enhance services, invest in training, recognize employee contributions, or create a more sustainable working environment.
If all the benefits of technology are converted into higher work demands, employees may struggle to perceive the positive value of digital transformation.
Conversely, when employees see that productivity improvements benefit both the organization and its workforce, they have stronger reasons to trust and actively participate in AI adoption.
Quiet Quitting Has Not Disappeared, but the Way We Understand It Needs to Change
AI is bringing significant changes to how people perform their jobs and how businesses evaluate performance.
Tasks that once required considerable time can now be completed more quickly. Skills previously considered essential may need to be supplemented or replaced by new capabilities. At the same time, expectations regarding productivity and work responsibilities are also evolving.
In this context, Quiet Quitting should not be understood simply as employees being unwilling to do more than what is required.
What businesses need to consider is whether employees are genuinely engaged with their work, understand the value of their contributions, and have opportunities to develop in a new technological environment.
An employee who completes work efficiently with AI while maintaining reasonable professional boundaries is not necessarily unmotivated. Conversely, an employee who consistently meets performance targets but no longer cares about shared organizational goals may be experiencing disengagement.
In the age of AI, the challenge for businesses is not only to help employees work faster, but also to create an environment where productivity, fairness, and work motivation can develop together.
