Accelerating a Healthier Future Through AI | Global Conference 2025

Workforce Crisis & AI Adoption

• The American Medical Association (AMA) reports a critical shortage of primary care physicians, nurses, and resources exacerbated by aging demographics and a chronic disease explosion.
• Physician adoption of AI tools doubled in the last two years, rising from 38% to 66% in a single survey cycle.
• Ambient dictation and administrative automation are the primary drivers of this rapid uptake, aimed at reducing "pajama time" (after-hours charting).
• Jesse (AMA) highlights that 30-40 companies currently offer ambient scribe technology, with the market rapidly consolidating through strategic partnerships with Electronic Health Record (EHR) vendors.

Implementation at UCLA Health

• Jonice (UCLA Health) notes the system currently operates ~30 AI tools, with the highest impact in radiology, cardiology, neurology, and administrative surveillance.
• Pilot programs for ambient listening across 300 clinics resulted in reduced after-hours note time, improved note accuracy, and higher patient satisfaction due to increased eye contact.
• UCLA Health employs 45,000 staff and created a dedicated AI infrastructure including a Chief AI Officer, a steering committee, and a strategy council to manage vendor integration and prioritize investments.
• The system is using AI to automate routine ICU surveillance (e.g., verifying breathing tube placement) to free clinical staff for higher-acuity tasks.

Precision Medicine & Oncology (Tempus AI)

• Tempus leverages AI to process complex genetic sequencing data, helping physicians navigate rapidly evolving mutation guidelines and identifying relevant clinical trials.
• The company offers modular "agents" that allow providers to query natural language for patient-specific treatment guidelines or trial matches without accessing multiple external sources.
• Tempus is launching patient-facing apps to consolidate data from multiple vendors, wearables, and mood surveys, aiming to empower patients to own their data.
• The organization emphasizes an agnostic approach, integrating with Epic, Cerner, and other platforms to accommodate varying levels of system sophistication.

Consumer Health & Wearables (Aura)

• Aura reports that ~25% of users utilize their wearable ring specifically for managing chronic illnesses, including cardiovascular disease, diabetes, POTS, and chronic fatigue syndrome.
• Tom (Aura) emphasizes the value of AI's "infinite patience and empathy," providing users with 24/7 access to health insights that relieve pressure on an overburdened healthcare workforce.
• The core utility of wearables lies in establishing individual baselines for biometrics, enabling "algorithmic care" that detects deviations from a user's personal normal rather than relying solely on population averages.
• Continuous data from wearables can uncover early disease patterns through multimodal analysis, potentially predicting illness before standard clinical biomarkers show anomalies.

Systemic Challenges & Interoperability

• Prior authorization is identified as the number one pain point for community physicians; while CMS mandates electronic prior authorization, fragmented third-party payer systems have made the process more cumbersome rather than less.
• Lack of interoperability leads to costly redundancies, such as patients traveling for care requiring repeat imaging (e.g., MRIs) because previous results are inaccessible.
• There is a growing need for a "platform approach" where AI agents sit on top of horizontal, best-of-breed services rather than requiring custom, $10M+ implementations for every vendor.
• The "Hippocratic AI" example illustrates early success in automating narrow, high-volume tasks like nurse call centers, demonstrating that standardized procedures can be learned and executed by AI at scale.

Patient Trust, Safety, and Regulation

• UCLA Health discloses the use of AI chatbots and ambient transcription in patient records to ensure transparency and manage expectations regarding data usage.
• Jesse notes that consumers are already using external tools like ChatGPT for medical advice, creating a regulatory gap where systems must compete with unvetted advice while ensuring safety.
• The panel agrees that regulatory frameworks will likely evolve to become risk-dependent, allowing for less human intervention in low-risk decisions while maintaining human oversight for high-risk processes like chemotherapy.
• A major safety goal for AI is increasing system reliability; currently, healthcare systems adhere to guidelines correctly only ~80% of the time due to human error and fragmentation.

Future Outlook & Clinical Trials

• The panel predicts a shift toward "citizen science," where patients participate in research via wearables and apps, facilitating faster recruitment for clinical trials in understudied conditions.
• AI is expected to reduce drug development timelines by optimizing trial design, identifying appropriate patient populations, and utilizing digital twins for predictive modeling.
• The vision of the future involves a "portable AI" or digital twin that travels with the patient, aggregating data from all providers to inform personalized care decisions regardless of location.
• Tom highlights that behavioral change remains the hardest hurdle in chronic care; AI offers the minute-to-minute interaction necessary to build habits and improve medication adherence.