What’s the first thing that comes to mind when you think of artificial intelligence (AI)? 

Using ChatGPT to draft work emails, whipping your resume into shape, and data analysis? Or creating stunning visual art from simple, sometimes outlandish, text prompts?

Sure. But beyond bettering your workflow and leisure time, AI has also revolutionized almost every aspect of our approach to health and wellness. From medical innovation to early disease detection to digital health tools, here are 4 ways AI has helped create a healthier world. 

#1: Promoting and maintaining wellness 

AI-powered wearable technology has made it possible for us to track and monitor:

• Fitness (e.g., step counts, VO2 max values, and daily calorie expenditure)
• Mood 
• Sleep (quantity and quality)

This promotes proactive management of a healthy lifestyle. 

AI-powered digital health tools could also benefit those at risk or with chronic health conditions. By combining AI and behavioral science, such tools could provide 24/7 personalized coaching through text messages or in-app reminders to users that align with clinical guidelines, improving health outcomes. 

An example is Hello Heart’s mobile app and heart health monitor. In a 2024 study published in the Journal of the American Heart Association (JAHA), researchers found that more than 100,000 people who used digital therapeutic company Hello Heart’s mobile app for 5 years experienced reductions in several major risk factors for heart disease, including:

• Blood pressure
• Total cholesterol
• Low-density lipoprotein cholesterol (“Bad” cholesterol)
• Weight 

#2: Early detection of diseases 

Early disease detection is crucial in reducing mortality from disease, reducing healthcare costs, and improving patients’ quality of life. 

AI could enable early disease detection by detecting subtleties in standard diagnostic tests—such as MRI and CT scans, electrocardiograms, and echocardiograms—that are invisible to the naked eye. 

This would flag patients who should undergo further confirmatory testing (when they would have been missed otherwise).

Case in point: an AI (deep learning) model called Composer. In a 2024 study published in npj Digital Medicine, Composer helped UC San Diego Health reduce its sepsis mortality rate by 17% by detecting it in patients roughly 4 to 6 hours before a clinician would be able to diagnose it. 

How? By analyzing roughly 150 variables such as patients’ demographics, vital signs, and medications. 

#3: Medical innovation and pharmaceutical development

The process of developing a new medication usually takes 10 to 15 years. That’s a long time. 

AI could potentially accelerate this process, bringing immense benefit to patients in urgent need of new treatment options where no applicable feasible treatments currently exist by:

• Analyzing large medical datasets, such as electronic health records or lab results, to help scientists identify the biological and genetic causes of diseases—facilitating medication choice

• Using structure-based design to predict how different pharmaceutical molecules will interact with the target, enhancing the precision of medication development 

• Designing novel pharmaceutical molecules that are entirely different from compounds designed by medicinal chemists, which typically only provide slightly improved safety or efficacy

#4: Improving healthcare and patient care operations 

AI has streamlined many healthcare operations, improving patient quality of care:

• Chatbots: Assist with patient questions, appointment scheduling, and referrals 
• Claims management: Automate claims data extraction and input, provide real-time updates and monitoring, stay on top of follow-ups and denials, and analyze claims 
• Bedside manner: Create draft notes for doctors based on patient-doctor interactions, allowing doctors to focus on talking to their patients and helping them “feel heard” instead of writing their notes (e.g., Ambient AI)
• Optimize hospital staffing and resources: Predict future resource needs, analyze patients’ health data, and identify high-impact patterns and trends in staffing