Apple pursues ambitious long-term goals in the healthcare sector with the development of an artificial intelligence agent capable of providing personalized health advice. This initiative, internally known as “Project Mulberry,” represents the company’s largest healthcare endeavor to date.

According to a recent Bloomberg News report, this AI-driven health advisor has evolved from an earlier effort called “Project Quartz,” which focused on AI-powered health coaching. The expanded project aims to create intelligent digital health companions that can analyze user data to deliver tailored health recommendations.

The technology could debut as early as the spring or summer of 2025, coinciding with the iOS 19.4 operating system update. This timeline suggests Apple is accelerating its healthcare strategy to capitalize on the growing intersection of technology and personalized health management.

How Apple’s AI Health Agent Will Function

The core functionality of Apple’s AI health agent will revolve around data collection and personalized insights. The system will gather health metrics from Apple devices—likely including Apple Watch biometric data, iPhone health app entries, and potentially other connected health devices.

Using this information, the AI will create individualized health recommendations. For example, if your sleep data shows irregular patterns, the AI might suggest specific bedtime routines or relaxation techniques based on your personal history and medical best practices.

One notable feature will be comprehensive food tracking capabilities—a domain Apple has previously approached with caution. This move would position Apple in direct competition with established nutrition apps like MyFitnessPal and health coaching platforms like Noom.

Medical Expertise Behind the Technology

The development team isn’t working in isolation. Apple is training its AI health agent using data from doctors already employed by the company, ensuring the system’s recommendations align with proper medical guidance.

Beyond its in-house medical team, Apple is actively recruiting specialists in various health disciplines, including:

• Sleep medicine
• Nutrition
• Physical therapy
• Mental health
• Cardiology

These medical professionals will contribute to the AI’s knowledge base and create video explanations about various health conditions, adding a human element to the digital health experience.

According to a recent PYMNTS Intelligence report titled “Healthcare Firms Going Long on GenAI Investment,” 90% of healthcare executives anticipate positive returns on their generative AI investments.

This confidence has led to increased spending on AI technologies within the healthcare sector, with investment levels exceeding cross-industry averages.

Common AI Applications in Healthcare

In healthcare, AI platforms like “Project Mulberry” have numerous modes of potential practical applications, the main of which are:

24/7 Virtual Health Assistants

NLP-powered healthcare chatbots provide round-the-clock support for patients, handling routine inquiries about appointments, facility information, and provider schedules. These systems free medical staff to focus on complex care needs while ensuring patients always have access to basic information.

Implementation example (pseudocode):

// Simple healthcare chatbot intent recognition
function identifyPatientIntent(userMessage) {
  const appointmentKeywords = ['schedule', 'appointment', 'book', 'visit'];
  const facilityKeywords = ['location', 'hours', 'parking', 'directions'];
  const doctorKeywords = ['available', 'schedule', 'specialist', 'doctor'];
  
  if (appointmentKeywords.some(keyword => userMessage.includes(keyword))) {
    return 'appointment_scheduling';
  } else if (facilityKeywords.some(keyword => userMessage.includes(keyword))) {
    return 'facility_information';
  } else if (doctorKeywords.some(keyword => userMessage.includes(keyword))) {
    return 'doctor_availability';
  }
  
  return 'general_inquiry';
}

Personalized Care Planning

AI systems analyze comprehensive medical datasets to identify patterns and develop individualized treatment plans. These technologies can detect potential health issues before they become serious, recommend preventive measures, and even monitor mental well-being indicators to support psychological health.

Advanced algorithms now sift through clinical information to uncover connections human eyes might miss. When applied to individual health records, these computational tools create bespoke wellness roadmaps. The technology identifies subtle signs of potential conditions before traditional symptoms appear, suggests targeted prevention approaches, and tracks emotional wellness markers to create a holistic health picture.

Improved Accessibility in Healthcare Communication

Natural language processing breaks down communication barriers in healthcare settings by converting text to speech for visually impaired patients or speech to text for those with hearing difficulties. AI can also simplify complex medical terminology into more ‘daily’ language, ensuring patients fully understand their care instructions.

Language technology transforms healthcare conversations by converting written directions to spoken words for those with vision limitations, while simultaneously capturing verbal exchanges as text for hearing-impaired individuals. Beyond simple conversion, these systems distill complex medical jargon into straightforward explanations that patients can grasp without medical training.

Medical Document Management

Healthcare facilities generate enormous volumes of documentation. AI categorization systems automatically classify medical documents by type (lab reports, prescriptions, diagnoses) and enable efficient keyword-based searches, dramatically reducing the time required to locate critical information.

The mountain of paperwork that once threatened to overwhelm medical practices now yields to smart categorization. Digital systems automatically sort clinical documentation—whether diagnostic results, medication orders, or treatment notes—into intuitive structures. Quick search functionality pinpoints exact information within seconds, transforming unwieldy archives into accessible knowledge bases.

Patient Experience Analysis

Healthcare providers use sentiment analysis to process patient feedback from surveys, reviews, and social media. This helps identify service strengths and weaknesses, popular procedures, and satisfaction levels with waiting times and facilities.

Medical facilities now extract meaningful insights from the digital footprints patients leave behind. By examining online reviews, survey responses, and social commentary, healthcare organizations discover which services resonate and which fall short. This unfiltered window into patient perspective reveals everything from staff interaction quality to facility comfort levels.

Challenges for Apple and the Future

Despite its ambitious plans, Apple has faced obstacles in its healthcare initiatives. Last year, the company was forced to remove the blood oxygen feature from its Apple Watch following a patent dispute with medical technology firm Masimo. This setback illustrates the complex regulatory and intellectual property issues surrounding health technology.

The introduction of an AI health agent would represent a significant evolution of Apple’s health ecosystem. By combining hardware (Apple Watch, iPhone), software (Health app), and now AI-driven insights, Apple aims to develop a comprehensive health platform and not just remain a ‘barebone’ device manufacturer.

Project Mulberry could transform how millions of people manage their health, potentially improving prevention, early intervention, and chronic condition management through accessible, personalized guidance.

If you are interested in this topic, we suggest you check our articles:

• AI in Healthcare: 8 Use Cases Making a Positive Impact
• The Role of AI in Maternal Healthcare
• AI in Medical Research: Exploring Its Impact and Innovations

Sources: PYMNTS, NetGeist

Written by Alius Noreika