AI in Healthcare: The Silent Revolution

AI IN PERSONALIZED MEDICINE

Dr. Jack Gilbert explains how AI is playing a crucial role in personalized medicine by analyzing complex, longitudinal data from multiple sources. Gilbert explains that his company, BiomeSense, combines various data streams—such as microbiome data, blood chemistry, and brain scans—using AI to help predict patient outcomes. 

“We’re using these dense longitudinal observations over time and AI to identify intersections between the data layers to predict the likelihood of recurrence", Gilbert shares. He highlights how this approach allows for personalized healthcare, especially in predicting cancer recurrence or other disease outcomes. 

In addition, he discusses the role of AI in dietary recommendations. “We can predict what specific foods generate beneficial compounds, and tailor dietary recommendations accordingly,” he adds, showing how AI can be used to fine-tune personalized healthcare plans. 

Rising Use of AI in Healthcare

AI AS A SUPPORT TOOL

Dr. Gilbert emphasizes that AI should be seen as a co-worker, not a replacement for human expertise. In the context of healthcare, he explains that while AI can assist in managing complex data, human oversight remains critical. 

“Patients trust human clinicians more than machines—especially during vulnerable moments,” says Gilbert, stressing the importance of the human element in healthcare decision-making. He notes that even the most advanced AI models require human clinicians to validate and interpret results effectively. 

“Generative AI works best when paired with structured data and ethical safeguards,” Gilbert adds, pointing out the need for strong ethical standards when using AI in healthcare. AI, he suggests, works best when it complements human expertise. 

“We’re using these dense longitudinal observations over time and AI to identify intersections over time between the data layers and predict the likelihood of recurrence of illnesses.” - Jack Gilbert 

THE INVISIBLE REVOLUTION: AI IN DOCUMENT WORKFLOWS

Serafin Bäbler brings attention to a less sophisticated but highly impactful application of AI: document workflows. In healthcare and insurance, there is a huge volume of unstructured documents that need to be processed, including medical reports, claims, referrals, and more. 

Bäbler explains how AI can be used to streamline this process. “AI’s strengths…are the ability to capture, classify, and extract data from these formats, turning all these documents into actionable information", he states. AI can classify, extract, and prioritize documents in real time, dramatically reducing the time spent on manual document handling. 

He further emphasizes the importance of this revolution in healthcare operations. “AI can reliably analyze documents and classify them automatically, prioritizing high-priority cases in real time”, Bäbler shares, highlighting how this automation can reduce delays and improve the efficiency of care delivery. 

“This is where AI can unlock huge potential. AI's strengths in our reviews are the ability to capture, classify, and extract data from these formats, turning all these documents into actionable information. With AI, not just faster, but if you do it right, more reliable, and in any case, much more scalable and time and resource independent.”- Serafin Bäbler 

AUTOMATING DOCUMENT PROCESSING

Bäbler gives a great example from SPS’s work with Sanitas, a Swiss health insurer. SPS helped automate the inbound document management system for Sanitas, improving efficiency across multiple channels. 

“We didn’t just automate what we saw; we really simplified the process before we went into the IT phase,” Bäbler explains. By rethinking and simplifying processes first, SPS was able to make the AI implementation more efficient and aligned with business goals. 

Best Advice 

Dr. Gilbert and Bäbler offer several strategic recommendations for healthcare leaders looking to adopt AI: 

1. Pick a manageable use case: Start with something like claims handling, referral routing, or contract management that’s impactful and solvable. 
2. Align your tech landscape: Choose partners with proven integrations to make the implementation smoother. 
3. Define success metrics early: Whether it’s cost reduction, faster turnaround times, or better customer satisfaction, having clear metrics is crucial. 
4. Human oversight is essential: Even with AI, human expertise is vital, especially in regulated areas. 

“Having defined success metrics helps to align the AI project with your organizational goals,” Bäbler advises. “Start small, think big, and scale smart.” 

CONCLUSIONS

AI is transforming healthcare, improving both patient care and system operations. It’s already helping doctors make better decisions, personalize treatments, and streamline daily tasks. By analyzing data like medical records and lifestyle habits, AI helps predict health risks and tailor treatment plans, leading to earlier and more effective care. 

Beyond treatment, AI also reduces paperwork by automating data processing, saving time and minimizing errors. While powerful, AI is a tool to support—not replace—healthcare professionals. As technology evolves, AI will play an even greater role in making healthcare more efficient and effective.