The use of Artificial Intelligence is no longer a futuristic concept, it’s an everyday reality as tools like ChatGPT, Microsoft Co-pilot and Gemini are being used for basic workplace tasks such as drafting mails, writing reports, supporting data analysis and generating ideas. Generative AI is the latest in a long history of technologies that raise questions about their impact on the quality of human thought (even writing was criticised by Socrates). While the promise of accelerated productivity is enticing, such concerns are not misplaced – because, when technology is improperly used, it can slow down or even erode cognitive abilities which need to be preserved.
Therefore, a crucial question emerges – how does this affect our own critical thinking?
A 2025 study by Hao-Ping Lee, Advait Sarkar, and colleagues surveyed 319 knowledge workers and collected 936 real-world AI use cases to explore this. They found that while AI accelerates outputs, it can reshape and often diminish critical thinking skills.
Lee et al.’s research focuses on the knowledge worker’s cognitive experience beyond productivity metrics and identified the instances when people used reasoning, judgment, or analysis versus simply accepting AI output. The findings reveal two key emerging trends:
- Execution vs Stewardship of Cognitive Tasks: Knowledge workers report that tasks which are deemed unimportant or secondary are delegated to AI – their engagement is limited to verification and improving output quality, leading to less mental energy being exerted. Essentially, the role of a knowledge worker has shifted from creator to editor.
- Self Confidence and Task Confidence: The study suggests that higher confidence in AI assisted tasks is associated with less critical. An important caveat is that knowledge workers with high self-confidence are more likely to engage in critical thinking and perceive greater cognitive effort in evaluating and applying AI outputs. The study suggests that fostering the knowledge worker’s domain expertise may result in improved critical thinking and promote a balanced and collaborative relationship when working with AI instead of adopting a supervisory role.
Apart from Cognitive offloading on AI, we are facing a double jeopardy with a well-documented decline in deep focus and attention caused by constant digital distractions.
When combined with accelerated reliance on AI, humans have started habitually leaning on digital tools for basic cognitive skills such as remembering important information, navigating our environment and engaging in effortful reasoning tasks. This has led to what researchers refer to as Cognitive offloading or, in simple terms – outsourcing of cognition. Social media and phone usage distracts us from sustained focus, and AI tempts us by providing ready made answers for complex cognitive tasks. This poses a risk to deep knowledge work and a potential competency crisis.
As noted by Bainbridge (1983), a key irony of automation is that by mechanising routine tasks and leaving exception-handling to the human user, you deprive the user of the routine opportunities to practice their judgement and strengthen their cognitive musculature, leaving them atrophied and unprepared when the exceptions do arise.
In the workplace, the gradual erosion of critical thinking (also referred to as cognitive deskilling), is a threat not only for productivity, but also for the employee’s capacity for independent judgement and problem-solving skills – both of which drive innovation. AI models are also known to “hallucinate” and can amplify societal biases. Overconfidence in AI could lead to errors slipping through and exposing us to structural risks and loss of institutional intelligence.
While there is cause for concern, we need not hit the panic button yet. The emergence of Generative AI presents an opportunity for us to learn and adapt alongside to ensure we leverage the benefits of the tool and modify it to circumvent the negative consequences.
As Jensen Huang, the CEO of NVIDIA stated: “Everybody in the world is now a programmer. This is the miracle of AI. To engage with AI is a lot easier now than at any time in the history of computing.”
L&D leaders can use this as an opportunity to address the new reality and promote AI literacy instead of blind trust (or mistrust). Training programs should focus on developing skills in information verification, prompt engineering and demanding reasoning and evidence for promoting critical engagement and active oversight with the tool instead of overreliance on AI.
As self-confidence of knowledge workers directly supports critical thinking, organisations should invest in skill building programs to deepen expertise, so employees can challenge AI and augment the output quality.
While it can be difficult to monitor digital distractions, advocacy for digital hygiene and policies to promote deep work can be introduced to rebuild attention spans by encouraging focus blocks for working and reducing digital clutter.
The research by Lee and Sarkar, when viewed through the lens of our already-distracted work culture, is a crucial wake-up call. Generative AI is a powerful tool, but it is not a substitute for human intellect. For business leaders, the strategic priority is to build a culture that safeguards deep focus and critical analysis, while leveraging AI to take on routine tasks. The future of our organisations will depend on our ability to protect our attention, strengthen human cognitive skills and adapt to this new reality, an adaptation that may well become our greatest competitive advantage.
References:
- Lee, H., Sarkar, A. et al. (2025). The Impact of Generative AI on Critical Thinking: Self-Reported Reductions in Cognitive Effort and Confidence Effects From a Survey of Knowledge Workers.
- Lisanne Bainbridge. 1983. Ironies of automation. In Analysis, design and evaluation of man–machine systems. Elsevier, 129–135.
- Mark, G., Gudith, D., & Klocke, U. (2008). The Cost of Interrupted Work: More Speed and Stress. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems.
- Newport, C. (2016). Deep Work: Rules for Focused Success in a Distracted World. Grand Central Publishing.
