AI boosts output but often expands workload and accountability demands.

Multiple AI tools can overwhelm cognition and reduce performance.

Digital work lacks stopping cues, driving endless cycles of refinement.

Protecting cognitive health is essential in an AI-accelerated workplace

A few years ago I wrote about digital-induced amnesia—the erosion of memory that occurs as we outsource thinking to our devices. I later reflected on technostress, the strain that occurs as those tools grow more complex.

Lately the phenomenon feels less theoretical.

A recent study published in Harvard Business Review by Julie Bedard and colleagues at Boston Consulting Group (BCG) describes something workers themselves have begun calling “AI brain fry.” The researchers surveyed nearly 1,500 full-time employees across industries in the United States and found that a meaningful share reported symptoms of acute cognitive fatigue linked to heavy AI use, particularly when managing multiple AI systems simultaneously (Bedard et al., 2026). Workers described mental fog, headaches, slower decision-making, and the strange sense that their thinking had become crowded.

They define it as mental fatigue that occurs when interacting with AI exceeds cognitive capacity.

What stands out is not just the symptoms, but the context in which they appear. As an epidemiologist, I’m interested in patterns, and “AI brain fry” appears to reflect a convergence of forces rather than a single cause.

Acceleration of productivity expectations

The United States has long been described as one of the most individualistic and competitive societies in the world (Hofstede, 2001). Productivity occupies a central place in our cultural imagination. We measure output, celebrate efficiency, and often equate accomplishment with personal worth.

Artificial intelligence has entered that landscape with astonishing speed, assisting with everything from drafting to analysis.

Researchers studying the “brain fry” phenomenon observed precisely this dynamic. Workers reported that AI did not simply reduce workloads. In many cases it expanded what the researchers called the sphere of accountability, meaning that employees suddenly felt responsible for producing more work, monitoring more outputs, and managing more information in the same amount of time (Bedard et al., 2026).

The technology that promised efficiency often expands both pace and responsibility instead.

The bottomless bowl of digital productivity

Many modern technologies are designed without natural stopping points.

Social media platforms perfected this design through the infinite scroll, a design pattern intentionally created to keep users continuously engaged with new content (Alter, 2017; Harris, 2016). Each new piece of information appears seamlessly below the previous one, eliminating the natural pause that once occurred when a page ended.

Behavioral scientists sometimes describe such systems as bottomless bowls. Like the famous study in which diners consumed significantly more soup when their bowls were secretly refilled from the bottom, people continue engaging with content when no visible endpoint signals completion (Wansink, Painter, & North, 2005).

Increasingly, digital work environments carry the same logic. Emails accumulate, messages continue, and AI tools generate endless variations of work.

When work is structured this way, the brain struggles to answer a simple question that earlier generations of workers encountered more naturally:

We often respond by continuing. Another pass at the document. Another prompt to refine the output. Another dataset to explore. Gradually the workday expands, not because we consciously intend it to, but because the environment never signals that the work has reached a natural endpoint.

The novelty-seeking brain

The brain is fundamentally responsive to novelty. New information activates dopamine pathways associated with curiosity, anticipation, and reward (Bunzeck & Düzel, 2006). Organisms that explored new stimuli were more likely to discover food sources, detect threats, and adapt to changing environments.

Digital environments provide novelty in nearly perfect doses. A new notification appears. A message arrives. An AI system generates an unexpected insight or phrasing. Each moment offers a small surge of curiosity.

This dynamic explains a familiar behavior: opening email or messaging apps even when dozens—or hundreds—of unanswered messages already sit waiting. Completion is not necessarily what the brain is seeking.

It is responding to novelty.

What is neurologically engaging can also be cognitively exhausting.

When multitasking feels productive

Complicating matters further is the way the brain interprets rapid task switching.

A well-known Stanford study examined frequent multitaskers and found that heavy media multitaskers performed worse than those who worked more sequentially when it came to filtering distractions, organizing information in memory, and sustaining attention (Ophir, Nass, & Wagner, 2009).

Perhaps most striking was the disconnect between performance and perception. Multitaskers often felt highly productive and synchronized with the pace of their work even as objective measures of performance declined.

The mind easily confuses activity with progress.

Cognitive health as a public health concern

Workplace well-being conversations have focused on mental health. An equally important dimension is cognitive health.

Cognitive health refers to the brain’s ability to sustain attention, process information clearly, remember details, and make sound decisions. These functions depend on sleep, rest, physical movement, social interaction, and opportunities for sustained reflection (World Health Organization, 2022).

The result is rarely dramatic collapse. More often it appears as a gradual thinning of cognitive bandwidth—the mental resources required for deep thought. In a knowledge-based economy, that erosion has implications not only for individuals but for organizations and societies.

It is important to emphasize that none of this suggests that artificial intelligence is inherently harmful. In fact, the same BCG study found that when AI is used to eliminate repetitive or tedious tasks, workers often report lower levels of burnout and greater engagement.

The issue is how we integrate these tools into daily routines. Several emerging practices appear to support healthier cognitive engagement with these tools:

Creating deliberate stopping points

Because digital environments rarely signal completion, individuals and organizations benefit from defining clear boundaries for work. Periods of intense digital engagement should be balanced with slower forms of thinking—walking, reading, conversation, and reflection—that allow the brain to consolidate information. Even in an AI-rich environment, conversation remains one of the most powerful tools for refining ideas and maintaining cognitive resilience.

A mindful approach to technological progress

New technologies have always reshaped how we think—the printing press, the telephone, the internet. Artificial intelligence represents another such transition.

In public health we often say that awareness is the first step toward prevention.

The goal is not to retreat from technology. It is to remain fully human while participating in it.

And that begins by protecting the most remarkable technology we already possess—the human brain.

Alter, A. (2017). Irresistible: The rise of addictive technology and the business of keeping us hooked. Penguin Press.

Bedard, J., Kropp, M., Hsu, M., Karaman, O.T., Hawes J., Keller G.R. (2026). AI brain fry: Managing cognitive overload in the age of artificial intelligence. Harvard Business Review.

Bunzeck, N., & Düzel, E. (2006). Absolute novelty is encoded in the human substantia nigra/ventral tegmental area. Neuron, 51(3), 369–379.

Harris, T. (2016). How technology hijacks people’s minds—from a magician and Google design ethicist. Medium.

Hofstede, G. (2001). Culture's consequences: Comparing values, behaviors, institutions and organizations across nations. Sage Publications.

Ophir, E., Nass, C., & Wagner, A. D. (2009). Cognitive control in media multitaskers. Proceedings of the National Academy of Sciences, 106(37), 15583–15587.

Wansink, B., Painter, J. E., & North, J. (2005). Bottomless bowls: Why visual cues of portion size may influence intake. Obesity Research, 13(1), 93–100.

World Health Organization. (2022). Brain health: Optimizing brain health across the life course.

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