Recently, at a busy health tech conference I was eyeing the latest AI-powered gadgets, apps and medical wearables promising to revolutionize personal health, and struck up a conversation with a fellow attendee, Sarah—a schoolteacher in her early 40s, recently diagnosed with high blood pressure and type 2 diabetes. She pulled out her phone, showing me a dizzying array of health apps: one tracking her sleep, another logging her meals, a third monitoring her heart rate. “Honestly,” she sighed, “I thought all this tech would make things easier. But now, I’m just overwhelmed. Every app tells me something different. How do I know what to trust or even where to start?”

Sarah’s question struck a chord, and it gets to the heart of a growing problem: cognitive overload in the age of AI.

The Modern Health Paradox: More Data, More Decisions, More Stress

We now live in an era where AI and health tech offer unparalleled access to data. From genome reports to smartwatch alerts about irregular heartbeats, we are drowning in metrics. Paradoxically, this abundance of information can make health decisions harder, not easier. 

Cognitive overload happens when the amount of information we face outpaces our brain’s ability to process and make decisions. This concept is central to Cognitive Load Theory (CLT), developed by educational psychologist, John Sweller in the late 1980s, which emphasizes the limitations of working memory.

Excessive cognitive load can lead to anxiety and cognitive fatigue, which in turn can result in avoidance behaviors, particularly in environments saturated with data as a study in Information Processing & Management highlighted.

AI and health technologies promise personalized health insights. However, they can also contribute to cognitive overload. A narrative review published in JMIR Medical Informatics discussed how the use of Electronic Health Records (EHRs)and the complexity and volume of data has increased cognitive load among clinicians, leading to burnout and affecting their performance and well-being.

In healthcare, this isn’t just a problem for clinicians, like physicians and nurses. Patients like Sarah, armed with wearables and health apps, are bombarded with data—steps, calories, heart rate, sleep cycles, and more. Instead of feeling empowered, many end up paralyzed by too many choices and conflicting advice.

What AI Adds (and Complicates)

AI is supposed to help by sifting through mountains of data and highlighting what matters. But if not designed thoughtfully, it can add to the noise, leaving us more confused than ever.  AI tools promise personalization. They can predict what’s best for you based on your genetics, microbiome, or heart rate variability. But they also introduce decision fatigue—the mental exhaustion from making repeated choices, a concept derived from the strength model of self-control pioneered by psychologist Roy Baumeister. Baumeister’s studies showed that self-control and decision-making draw from a limited pool of mental energy. As this resource is used up, people become more likely to make impulsive, avoidant, or poor decisions.

Why Does Cognitive Overload Happen?

Neuroscience shows that our brains have a limited “working memory”—the mental workspace where we juggle information and make decisions. When overloaded, we’re more likely to make poor choices, procrastinate, or give up altogether.  In fact, a landmark study by Iyengar and Lepper found that people offered too many choices (like 24 flavors of jam) were less likely to make a purchase than those offered just six.

Cognitive overload is rooted in how the brain processes information. Our brains evolved to focus on a handful of important signals, not a firehose of data. The prefrontal cortex—the region responsible for decision-making and self-control—can only handle so much input before it gets overwhelmed. Neuroscientific research shows that our working memory—the mental “scratchpad” we use to hold and manipulate information—is limited. According to a classic study by Miller in 1956, we can typically juggle only 7 ± 2 pieces of information at once. More recent research suggests that number might actually be closer to four.

When faced with too many choices, our brains default to shortcuts: we ignore information, rely on habits, or defer decisions.

This is why Sarah, and so many others, feel stuck. The endless stream of health metrics and AI-generated suggestions can create a kind of “analysis paralysis,” where making any decision feels daunting. Even worse, people start to ignore health advice and continue with lifestyle habits that maybe detrimental to their health. 

Simplifying Health in the Age of Overload: 5 Frameworks

To combat overload, we need simplicity by design, not just more data. The good news? Neuroscience and behavioral research offer practical ways to help our brains cut through the noise and make smarter health choices. Here are 5 science-backed frameworks to help make health decisions manageable:

1. The Three-Question Rule

Before acting on any health data or recommendation, pause and ask:

• Is this information relevant to my current health goal?
• Is it actionable, or just interesting?
• Do I understand what this means, or should I ask for clarification?

This simple filter helps your brain focus on what truly matters, reducing unnecessary mental clutter.

2. Chunking: Group Information into Meaningful Units

Our working memory can only hold about 4-7 pieces of information at once. “Chunking”—grouping related data together—makes it easier to process. For example, instead of tracking ten health metrics, focus on three key areas (like sleep, activity, and blood pressure) that align with your goals.

3. Decision Trees: Break Complex Choices into Simple Steps

Visualize your options as a series of yes/no questions. For example, if your goal is to lower blood pressure, ask: “Does this recommendation help me achieve that?” If yes, consider it; if not, set it aside. This narrows your choices and makes decision-making less overwhelming. 

4. One Change at a Time: The Power of Incrementalism

Resist the urge to overhaul your routine based on every new data point or AI suggestion. Pick one evidence-based habit—like walking 20 minutes a day—and stick with it for a few weeks before adding something new.

5. Leverage Trusted Summarization Tools and Human Support

Look for AI tools that don’t just dump data but summarize and contextualize it. Even better, share your reports with a healthcare provider or coach. Social support and expert guidance reduce cognitive load and boost confidence in your decisions. 

Sarah’s story is all of ours. In the age of AI, we’re drowning in health data, but we don’t have to let it sink us. By applying these science-backed frameworks, we can simplify our choices, reduce stress, and make healthier decisions—one step at a time.

AI and health data aren’t going away—in fact, they’ll only get more advanced. But we must learn to use technology as a guide, not a tyrant. Our brains weren’t built for a deluge of daily data. They thrive on clarity, simplicity, and rhythm.

So, if you’re feeling overwhelmed by health tech, take a breath. Shrink the choices. Choose a framework. And remember: your brain, not your smartwatch, is your most powerful health tool.

What questions do you have about health tech and how it can help or hurt your health and well-being? Please share with me in the comments. 

Photo by Nate Neelson on Unsplash