A new global survey reveals a troubling tension at the heart of workplace AI adoption: while employees are saving significant time using generative AI tools, nearly half worry the technology is eroding their critical thinking skills and making them intellectually dependent. The findings highlight what researchers call an emerging "AI paradox" where productivity gains are colliding with workforce capability risks.

The Pulse of Work in 2026 study, conducted by GoTo in partnership with Workplace Intelligence and surveying 2,500 global employees and IT leaders, found that 39% of workers say overdependence on AI is weakening their skills and making them "less intelligent." The concern is especially pronounced among younger workers, with 46% of Gen Z employees expressing this fear.

What Are Workers Actually Experiencing With AI at Work?

The survey uncovered a striking set of statistics that paint a picture of cognitive outsourcing at scale. Beyond the core finding about intelligence concerns, workers reported troubling levels of dependence on AI systems:

• Functional Dependence: 30% of employees say they feel unable to function without AI tools in their daily work.
• Confidence Erosion: 28% say they trust AI more than their own judgment, and 29% believe AI is already doing their job better than they can.
• Career Anxiety: 41% believe AI overreliance could damage their long-term career prospects, rising to 50% among Gen Z workers.
• Pressure to Adopt: 60% of employees feel pressured to use AI to improve productivity, even without proper training or guidance.

One of the most striking findings involves what researchers describe as "workslop," low-quality AI-generated content that creates hidden workloads. The study found that 43% of workers knowingly submitted AI-generated content they suspected contained errors, inaccuracies, or fabricated information. Additionally, 77% said reviewing AI-generated work takes longer than reviewing human-produced work, and 66% reported that correcting AI output creates additional workload.

"What stands out in these findings is the emotional tension behind AI adoption at work. People are clearly benefiting from AI in terms of productivity, but at the same time many workers seem to be questioning themselves more, whether they still trust their own judgment, whether they're thinking critically enough and whether they're becoming too dependent on technology," said Pepi Sappal, Founder of Fair Play Talks.

Pepi Sappal, Founder of Fair Play Talks

Why Is AI Training and Governance Failing Employees?

The research reveals a significant gap between AI adoption speed and organizational readiness. While companies are rapidly deploying AI tools, they are not investing adequately in training and governance frameworks. The study found that 80% of employees believe workers are not being properly trained to use AI tools responsibly, and 69% say they are unfamiliar with how AI can be practically applied in their specific roles.

This training deficit appears to be driving much of the misuse. The survey found that 70% of employees admit using AI for sensitive or high-stakes tasks, including legal or compliance work (41%), tasks requiring emotional intelligence (37%), safety-related decisions (31%), strategic decision-making (29%), and ethical or personnel decisions (28%). Nearly one in four IT leaders reported that AI-related mistakes have already negatively affected customers, clients, or company finances.

"Many CEOs turn to layoffs to demonstrate quick AI returns; however, this disposition is misplaced. Workforce reductions may create budget room, but they do not create return. Organizations that improve ROI are not those that eliminate the need for people, but those that amplify them by aggressively investing more in skills, roles and operating models that allow humans to guide and scale autonomous systems," stated Helen Poitevin, Distinguished VP Analyst at Gartner.

Helen Poitevin, Distinguished VP Analyst at Gartner

How to Build Responsible AI Adoption in Your Organization

Experts emphasize that organizations need to fundamentally rethink their approach to AI deployment. Rather than prioritizing speed and cost-cutting, companies should focus on building sustainable practices that preserve human capability while capturing AI's benefits:

• Implement Comprehensive Training Programs: Develop structured training that teaches employees not just how to use AI tools, but when and why to use them, emphasizing critical thinking and judgment over automation.
• Establish Clear Governance Frameworks: Create policies that define which tasks are appropriate for AI assistance and which require human decision-making, particularly for sensitive, high-stakes, or ethically complex work.
• Invest in Human Capability Development: Rather than reducing headcount, allocate resources to upskilling employees in areas where human judgment, creativity, and emotional intelligence remain irreplaceable.
• Monitor and Measure Quality: Implement systems to catch and correct low-quality AI output before it reaches customers or affects business decisions, reducing the hidden workload of correction.
• Create a Culture of Critical Thinking: Establish workplace norms that encourage employees to question AI outputs, maintain independent judgment, and develop their own problem-solving skills rather than defaulting to automation.

The broader context for these findings comes from a separate Gartner survey of 350 global business executives. That research found that approximately 80% of organizations piloting or deploying autonomous business capabilities reported workforce reductions. However, those reductions did not translate into improved return on investment (ROI). The survey found that workforce reduction rates were nearly equal among companies reporting higher ROI and those experiencing only modest gains or negative outcomes.

Gartner forecasts that AI agent software spending will reach $206.5 billion in 2026 and $376.3 billion in 2027, up from $86.4 billion in 2025. Despite this massive investment, the research suggests that long-term success depends not on eliminating human workers, but on amplifying their capabilities.

"Long term, autonomous business will create more work for humans, not less. Lasting structural factors such as demographic decline and high-stakes, trust-dependent consumer moments will ensure human talent remains central to running, governing and scaling autonomous business," explained Helen Poitevin.

Helen Poitevin, Distinguished VP Analyst at Gartner

The research suggests that organizations are at a critical inflection point. The productivity gains from AI are real and substantial, but they come with hidden costs to workforce capability, confidence, and long-term career development. Companies that recognize this tension and invest in responsible AI adoption, comprehensive training, and human capability development are more likely to achieve sustainable ROI. Those that pursue quick wins through cost-cutting and rapid deployment without governance frameworks risk creating workplaces where employees feel less intelligent, less confident, and less equipped to handle the complex decisions that ultimately drive business success.