Nine Bold Visions for Healthcare: How AI Could Transform Healthcare by 2035

1. Biometric Guardians: The Rise of Wearables in Disease Prevention

Image source: Wearable Technology Market

By 2035, continuous-monitoring wearable devices could be pivotal to preventive care, tracking biometric and lifestyle data in real time. The global wearable medical devices market, valued at $42.7 billion in 2024², is projected to reach $195.57 billion by 2030³, as demand for real-time, personalized health insights increases.

Rather than waiting for noticeable symptoms, future AI-powered wearables will interpret subtle biomarker shifts. For instance, algorithms can already detect congestive heart failure from a single ECG heartbeat with high accuracy⁴. Imagine a device that constantly tracks sweat chemistry, microRNA markers, glucose, and inflammation levels. If an AI model spots a cortisol spike pointing to an impending autoimmune flare-up, it could send an app alert:

We see early signs of heightened inflammation. In previous episodes, these three targeted interventions reduced severe flare-ups by 40%. If symptoms intensify, we’ll connect you with a specialist.

Alumni Ventures portfolio companies are advancing this evolution. Epicore Biosystems develops microfluidic sweat patches that measure hydration and electrolyte balance. In time, their technology could expand to use the hormones, proteins, and metabolites found in sweat to provide a more direct look into our state of health. Levels combines continuous glucose monitors (CGMs) with AI-driven metabolic insights, while Oura, (over 2.5 million rings sold⁵), tracks heart rate variability, sleep, recovery, and even early illness indicators.

Image source: Epicore Biosystems, Creators of the Gx Sweat Patch, Raises $10M

2. The Age of Full-Body Scans and Digital Twins

A decade from now, annual full-body imaging may become standard preventive practice. Companies like Q Bio and Ezra, both in the Alumni Ventures portfolio, offer advanced body scanning systems that capture a comprehensive view of internal organs. Q Bio uses AI-driven software to synthesize imaging and lab results into a bio-digital twin, mapping subtle changes such as tiny lesions, arterial plaques, or growth–before they become severe. Ezra offers a full body scan that in one hour looks for potential cancer and 500+ conditions in up to 13 organs.

Currently, these scans remain expensive and often aren’t covered by insurance, but costs are declining. As insurers realize the long-term benefits of early detection, full-body imaging could shift from a niche option to a core preventive tool. The broader AI medical imaging market is projected to grow from $1.3 billion in 2024 to over $14 billion by 2034⁶, highlighting the shift toward proactive scanning.

Ultimately, faster and more affordable body imaging with ever-improving AI analysis promise a future where detailed internal monitoring is as routine as annual blood work, enabling clinicians to check changes in your bio-digital twin and intervene before problems worsen.

Image source: Q Bio

3. Blueprints of You: Hyper-Personalized Preventive Care

Source: BioSpace – Artificial Intelligence in Precision Medicine Market to Reach $37.6 Bn by 2034

Detecting potential issues early is one step; acting with precision is another. By 2035, AI models could continuously integrate your genetic predispositions, diet logs, microbiome data, lifestyle habits, and imaging results into a dynamic health profile. This profile would guide clinicians in prescribing diet tweaks, exercise regimens, and even medication or supplement poly pills 3D-printed and calibrated to match your biomarkers.

Alumni Ventures portfolio companies are moving in this direction. Bionic Health combines physician consultations with AI to interpret over 200 biomarkers, track biological age, and provide coaching. Jona Health uses microbiome profiling to deliver precision nutrition guidance. As these solutions unify diverse data streams, they could generate proactive alerts for rising blood pressure, recommending a mild diuretic or anti-inflammatory therapy, precisely dosed to the individual’s metabolism.

Physicians remain essential for oversight, but mature AI could substantially reduce hospitalization rates by catching risks early and personalizing treatments — bringing medicine closer to proactive, minimally invasive care. The market for AI in precision medicine is projected to grow 35% annually, potentially reaching $30+ billion by the mid-2030s⁷.

Image source: Jona Health

4. Micro Marvels: AI and Nanorobotics for Targeted Therapies

By 2035, we might see early deployments of tiny medical robots or nanorobotics delivering hyper-targeted therapies or performing delicate microsurgeries well beyond today’s capabilities. Though it once sounded like science fiction, research labs have already shown proof-of-concept for magnetically guided⁸ nanobots that deliver drugs to specific sites in small animals and remove clots in vessels too small for surgeons to reach with microscopic surgery tools.

Bionaut Labs, an Alumni Ventures portfolio company, is developing remote-controlled micro-robots to treat neurological conditions inside the brain. Recent animal trials demonstrated microrobots made of algae-based cells that can deliver nanoparticles of antibiotics directly to infection sites in mice lungs, saving all test subjects from a lethal pneumonia strain⁹. Researchers at Rice University¹⁰ and Karolinska Institutet in Sweden have developed nanorobots that can drill into cancer cells and antibiotic-resistant bacteria¹¹.

Looking ahead, advanced AI-models could be used to help design, test, and coordinate clusters of such bots¹².

Cluster A, is dissolving arterial plaque in the right coronary vessel. Cluster B, is delivering a micro-dose of chemo to that 2 mm tumor in the pancreas.

While significant engineering and safety hurdles remain, successful nanorobotics could unlock less invasive, more precise therapy in areas surgeons currently struggle to reach. The nanorobot healthcare market was valued around $7 billion in 2023 and could grow 8-10% annually through 2030¹³.

Image source: Bionaut

5. Virtual AI Biologists and Cloud Labs: Scaling Scientific Discovery

AI is shifting from a data analysis tool to an active research platform, merging robotics, machine learning, and automation to perform, direct, and optimize biological experiments at scale. By 2035, virtual biologists might dramatically expand R&D capacity, testing more hypotheses, refining experiments faster, and even uncovering overlooked breakthroughs that traditional labs might miss¹⁴.

This approach is illustrated by Alumni Ventures portfolio company Emerald Cloud Lab (ECL), which runs automated lab facilities where scientists design, execute, and analyze a wide range of lab capabilities remotely¹⁵. Carnegie Mellon University recently partnered with ECL to open a $40 million cloud lab that uses AI and robotics around the clock, accelerating discovery¹⁶.

As AI agents gain autonomy, they’ll propose new experiments at unprecedented throughput, potentially accelerating drug discovery, disease research, and other biological innovations. The lab automation market is projected to grow to grow from $6.5 billion in 2025 to $16B by 2035¹⁷, underscoring the growing demand for automated lab research.

Image source: Emerald Cloud Labs

6. Scalpel 2.0: The Rise of Autonomous Surgical Robots

By 2035, surgical robotics may advance from human-guided systems to semi- or fully autonomous platforms that handle routine procedures with a surgeon supervising. Today’s da Vinci Surgical System enhances a surgeon’s precision but still requires direct control. Yet autonomy is emerging. In 2022, the Smart Tissue Autonomous Robot (STAR) successfully performed laparoscopic surgery on pig intestines without human guidance, achieving notably high precision¹⁸.

Alumni Ventures portfolio company Andromeda Surgical is developing AI-guided autonomous robots to enhance surgical safety and consistency. Its first system, focused on endourology, aims to bring every surgeon to an expert level.

Transitioning to fully autonomous operations demands rigorous safety validation and regulatory approvals. However, if approved, these future systems could deliver standardized, high-quality surgery worldwide. World-class surgery practices might license their techniques to robotic platforms used in remote hospitals, reducing wait times and extending advanced procedures to underserved regions. The global surgical robotics market, around $10 billion in 2023, is forecast to reach $28-30 billion by 2031¹⁹, reflecting ongoing demand for safer, more precise procedures.

Image source: The Future of Robotics in Surgery

7. Rewiring the Mind: AI and Brain Computer Interfaces

Mental healthcare traditionally depends on self-reporting or observable symptoms. By 2035, AI-based platforms could read neural and physiological signals early, spotting indicative patterns leading to severe depression or manic episodes before clinical crises emerge. Minimally evasive brain-computer interfaces (BCIs) might then deliver real-time interventions, such as targeted neural stimulation or alerting a monitoring system just as symptoms begin.

Early-stage BCIs, like those from Precision Neuroscience (raised $102M Series C in December²⁰), are already mapping brain signals more precisely. Meanwhile, AI-driven mental health solutions —including chatbots and predictive analytics — have seen a surge in adoption, with the global market projected to grow from $1 billion in 2023 to over $10 billion by the 2030s²¹.

In more advanced scenarios, if sensors detect the onset of PTSD flashbacks or increasing opioid addiction cravings, the device might moderate relevant brain circuits — much like a pacemaker prevents arrhythmias. Ethical and date privacy questions loom large, but for patients struggling with debilitating mood disorders, spinal injuries, addictions, and motor impairments, these innovations may offer life-changing benefits.

Image source: Precision Neuroscience

8. Healthcare Admin Automations: Cutting Costs, Not Care

While futuristic breakthroughs capture headlines, AI’s largest near-term impact may be reducing administrative inefficiencies that cost the U.S. healthcare system hundreds of billions annually. Complex billing, scheduling, health record logs, insurance authorization, and supply chain demands drive up costs and contribute to provider burnout.

Startups are increasingly using AI and data analytics to streamline these processes. Alumni Ventures portfolio company Clarium Health deploys an AI-driven platform offering real-time visibility into hospital supply chains, optimizing inventory and saving millions in costs. In early deployments at major health systems, it has demonstrated over $10 million in average annual customer cost savings and cut hospital supply resolution times by 50%.

Recent estimates suggest automation in healthcare administration could save the U.S. system $200–$360 billion per year²² and free healthcare workers to spend more time helping their patients. Hospitals are also implementing AI-powered predictive models to help hospital command centers forecast patient flow, help schedule staff, and route urgent cases, improving efficiency while enhancing patient care.

Image source: PWC: When the walls come tumbling down: the hospital of the future

9. From Lab to Patients: Accelerating Drug Development

Developing a new drug often requires a decade of work, but AI is speeding up the timeline. Models can quickly generate promising compounds, predict toxicity, and improve trial design. Though lab work and human testing remain necessary, AI can accelerate participant selection and identify early signs of a drug’s success or failure, reducing wasted time and expense.

AI is also influencing regenerative medicine, guiding tissue growth and repair. Machine learning can optimize stem-cell differentiation and biomaterial design, enhancing the viability of lab-grown tissue for transplants. Notably, some AI-driven drug projects have advanced from concept to Phase I in under 30 months²³, whereas typical development can take four or more years. By shortening discovery and fine-tuning clinical trials, AI could drastically reduce time-to-market for new therapies. Analysts project the AI in pharmaceutical R&D sector, around $1 billion to $2 billion in 2024, could exceed $35 billion by 2034²⁴.

By accelerating the path from discovery to approval, AI-powered technologies could upend the pace and process drug trials, delivering breakthrough treatments more efficiently, cutting costs, and unlocking innovation for rarer or orphan diseases that often struggle to attract traditional pharma investment.