Is Medical AGI Coming? Can It Help Humans Live to 120?
By the end of the "14th Five-Year Plan," China's average life expectancy had increased to over 79 years, with an average annual growth of 0.26 years over the five-year period. The newly released "15th Five-Year Plan" outline further proposes to increase the average life expectancy to 80 years in the next five years.
With the improvement of economic standards, advancements in medical technology are undoubtedly a direct driving force in extending life expectancy. Currently, cutting-edge technologies represented by artificial intelligence are also accelerating this process.
Recently,"Technology Prophet" Kevin Kelly and Wang Shirui, founder of Future Doctor, held a dialogue to deeply explore the extension of medical AI value boundaries. During the conversation, Wang Shirui predicted: Medical AGI has the potential to extend human lifespan to 120 years.
Can AI help humans live to be 120 years old? This may sound exaggerated, but it has become a direction jointly explored by the medical and technology communities.
All along, Artificial General Intelligence (AGI) has been regarded as the ultimate goal of AI development. It is an intelligent system with general human cognitive abilities, capable of learning, thinking, and solving complex problems like humans. In recent years, from ChatGPT to DeepSeek, and now to "Lobster," every major breakthrough in AI technology has sparked widespread attention across industries. Both the industrial sector and the general public are increasingly accepting new things like AI at an accelerating pace. At the same time, each significant breakthrough is seen as bringing us one step closer to AGI.
However, the realization of AGI must meet two key conditions, namely: an extremely high level of intelligence; and the possession of human-like consciousness. From the perspectives of technical implementation and machine consciousness, these two conditions still present significant challenges. The gap between ideal and reality makes the achievement of AGI remain highly uncertain.
In Wang Shirui's view, compared with general AGI, medical AGI has clear goals and iterative paths and will be realized before general AGI.
What is Medical AGI? As an AI focused on the medical vertical, Medical AGI possesses the professional personality of a doctor, adheres to medical ethics, integrates deeply into real clinical scenarios at the front end to achieve real-time and efficient interaction with both doctors and patients, and at the back end, can lead the full-process self-iteration of clinical guidelines. It is a dedicated AI system adapted to real diagnostic and treatment scenarios and aimed at promoting medical advancement.
In recent years, the continuous advancement of digital technology from informatization to medical AI has significantly transformed the medical service system, particularly by greatly improving the convenience of public access to healthcare. However, long-standing core issues within the industry still persist: high-quality resources such as expert physicians remain scarce, and the capacity for diagnosing and treating complex diseases still needs enhancement. Wang Shirui believes that medical AGI will be the key to solving these problems, helping to break through the scarcity of quality resources and medical technological bottlenecks at their source.
From a macro perspective, the current high level of participation in AI across all sectors of society, including the medical field, combined with the密集出台的利好政策by the state in areas such as medical AI and big data, has created a favorable environment for the technical exploration and application落地of medical AGI.
According to the 57th "Statistical Report on the Development of China's Internet Network" recently released, as of December 2025, the number of generative artificial intelligence users in China has reached 602 million, increasing by 141.7% compared to the end of 2024. AI products are gradually improving the quality of services in areas related to people's livelihood such as healthcare, elderly care, and education through more precise and efficient methods, enhancing the user experience of both online and offline products and services.
However,To achieve the expansion of high-quality resources and break through medical technology bottlenecks, medical AGI cannot be limited to enhancing patient experience or providing emotional value; its foundation must be built on serious medical scenarios. Looking at the numerous medical AI companies participating in the industry, Future Doctor's series of explorations have laid the groundwork for the realization of medical AGI.
All along, the serious diagnosis and treatment adhered to by Medlinker's future doctors have been a route completely different from AI health consultation. Its medical AI strategic direction includes: replicating the diagnostic capabilities of top doctors through AI standardization, and allowing AI to provide breakthrough treatment plans for diseases that even top experts find difficult to tackle.
Specifically, in terms of patient services, to ensure the rigor and authority of diagnosis and treatment, Future Doctor has established a four-level triage system based on AI-human collaboration: AI preliminary screening and structured consultation, multidisciplinary team (MDT) intervention, specialist intelligent matching, authoritative expert review, decision-making, and signing. This process enables the platform to provide patients with precise diagnostic recommendations and optimal treatment plans, while directly taking responsibility for treatment outcomes.
Behind the service positioning and model of future doctors lies a set of AI technology support systems that have been refined over many years:
First is the technical architecture that simulates human brain cognition, which initially adopts a fast and slow dual-system solution.
MedGPT, the AI medical cognitive system independently developed by future doctors, adopts a three-layer architecture that simulates human brain cognition, rather than relying solely on massive data training. In the three-layer architecture, the fast system is analogous to the cerebral cortex performing semantic tasks, invoking general models to quickly respond to user needs and handling understanding and communication; the slow system is analogous to deep reasoning in the prefrontal cortex, responsible for invoking corresponding knowledge, algorithms, and experience databases for in-depth verification and solving complex medical problems; the ACC layer is analogous to the anterior cingulate cortex, responsible for reconciling conflicts between the fast and slow systems and reducing AI hallucinations.
The three-layer architecture aims to construct a technical pathway for medical AI from the biological mechanism level, making the AI reasoning process closer to the thinking path of a real doctor.
Secondly, the continuous evolution of medical AI under the dual flywheel cycle.
MedGPT Builds a Dual-Flywheel Cycle Aligned with the Clinical Decision-Making System: The small flywheel is driven by clinical guidelines and standardized diagnosis and treatment pathways, ensuring the accuracy and consistency of diagnosis and treatment; the large flywheel enhances the underlying capabilities of the model through practical experience and supplements capability gaps to meet individual needs by studying expert consensus and replicating expert wisdom, generating higher-quality diagnostic and treatment recommendations.
Medlinker Group Has Built Deep Trust and Cooperation with Experts in the Field of Internet Healthcare Over the Years. On the Future Doctor Platform, More Than 10,000 Doctors Currently Interact with Patients, Generating 20,000 Authentic Treatment Feedback Entries Weekly. This Creates a Virtuous Cycle of Doctor Feedback, Algorithm Updates, and System Enhancements, Continuously Improving Medical AI Capabilities. It Is Reported That the Accuracy of MedGPT Is Steadily Increasing Every Month.
Finally, there is a medical AI evaluation system that fits real diagnosis and treatment scenarios.
Current mainstream evaluations of global medical AI are mostly based on standardized tests, and OpenAI's HealthBench primarily focuses on communication skills assessment, which is far from the core requirements of serious medical treatment for safety, effectiveness, and personalization.
In the past, MedGPT ranked first in multiple mainstream evaluations, but Future Doctor (Medlinker) did not stop there. To fill the international gap, Future Doctor collaborated with 32 top experts in China to establish the world's first "Clinical Safety-Effectiveness Dual Benchmark (CSEDB)" system for evaluating the clinical applicability of medical AI. This system covers 30 core indicators, breaks the static question-answering model, and includes open-ended questions and simulates real, complex diagnosis and treatment scenarios.
Research Results on the CSEDB Evaluation System by Future Doctors Have Been Published
In December 2025, the above research results were published in "npj Digital Medicine," a top journal under Nature. MedGPT ranked first globally in the evaluation. CSEDB has promoted the assessment of medical AI from standardized tests to real clinical decision-making, paving a feasible path for constructing future AGI evaluation standards in healthcare.
Moreover, the sustainability of the business model is crucial for the long-term development of medical AGI.
Unlike the traffic value-added model of Internet healthcare, Future Doctor has proven through practice that providing free health consultations via medical AI actually weakens medical trust. Reasonable pricing and professional endorsements are what enable the formation of a commercial closed loop with participants such as hospitals and insurance companies. Wang Shirui revealed that Future Doctor has established a business model based on the value of medical AI services and will achieve profitability by 2025.
Therefore, in an era where cutting-edge technologies generally rely on "burning cash" for R&D as the primary model, the self-sustaining capability accelerates the arrival of the medical AGI age by enabling this long-term marathon to enter a positive cycle.
From the perspective of the development path of future doctors, medical AGI already has the technical and model foundation. As the AI technology base centered on serious diagnosis and treatment continues to mature, medical AGI can move faster from concept to reality.
From a legal and ethical perspective, AI can never replace human doctors. After the birth of AlphaGo, the peak showdowns between human Go champions remained spectacular; in the medical field, where life is at stake, human judgment and leadership are even more indispensable. However,This does not affect medical AGI from becoming an inevitable trend in the development of medical AI, because the core value of medical AGI goes far beyond improving就医便捷度and serving as a doctor's assistant—it can fundamentally accelerate the progress of医学.
Every major breakthrough in human medicine has gone through a long exploration cycle.Countless medical workers have been striving in succession, often taking decades or even centuries, to achieve a cognitive disruption and a shift in the medical paradigm.
Take the common diabetes as an example. As early as 1500 BC in ancient Egypt, there were already relevant records. Before the discovery of insulin, the most well-known treatment for diabetes and reducing mortality was the "starvation therapy." Over a long period of time, countless medical scientists attempted to unravel the mystery of diabetes until the discovery of insulin in the 1920s, which was successfully used in the treatment of diabetic patients. In the following 100 years, insulin underwent multiple iterations to achieve the current high level of accessibility.
At the same time, the development of medicine is an endless process.In addition to updating medical knowledge to address the changing disease spectrum, even for the same disease, its treatment methods are constantly being improved. Taking diabetes treatment as an example, the medical community’s exploration of better solutions has never stopped. Pre-diabetes intervention, intelligent drugs and devices, multi-target treatments, and more are all mainstream directions. The goal is gradually shifting from blood glucose control to functional cures.
Similar cases are abundant in the medical field. Nowadays,Medical AGI has become an important opportunity to shorten the aforementioned long cycle.
In recent decades, clinical guidelines have become the core vehicle for advancing evidence-based medicine. As a crucial bridge connecting medical research and clinical practice, clinical guidelines transform the best medical evidence into actionable diagnostic and treatment recommendations.
The core value of medical AGI lies in revolutionizing the paradigm for updating clinical guidelines, putting medical advancements on the fast track.
On the one hand, medical AGI can significantly shorten the update cycle of clinical guidelines.There are approximately 35,000 disease-related diagnosis and treatment guidelines worldwide. Under the traditional model, each guideline is updated every 3 to 5 years, with processes such as project initiation, patient recruitment, and result integration often taking several years. However, medical AGI can compress project initiation from months to 24 hours, with patient data feedback completed in as little as 72 hours and at most 2-3 months, potentially shortening the guideline update cycle from 3-5 years to within 3 months, achieving dynamic, real-time optimization.
On the other hand, medical AGI can significantly improve the quality of clinical guideline updates.The core of evidence-based medicine is to make medical decisions by combining the best evidence, clinical experience, and patient values. However, the development of guidelines often faces challenges such as assessing the level of evidence and defining the effectiveness of interventions. Medical AGI can scientifically evaluate medical evidence and intervention outcomes by quantifying the extent to which guidelines optimize the gold standard of diagnosis and treatment and the probability of their impact on human healthspan, precisely addressing these issues, which is also its core development goal.
With the technological revolution brought by the Industrial Revolution, human life expectancy achieved a leapfrog breakthrough in the 20th century: from 32 years of global average life expectancy in 1900 to 73 years in 2023. So, what is the underlying logic behind the prediction that medical AGI will help human life expectancy break through 120 years?
Reviewing history,The core of the doubling of human lifespan is attributed to two key pathways:
First, the advancement of medical technology has promoted the chronic transformation of major diseases.The treatment of diabetes mentioned earlier is also a typical case. The insulin-centered treatment approach has transformed diabetes from an once-incurable disease into a long-term controllable chronic condition. In recent years, with breakthroughs in precision medicine methods such as targeted therapy and immunotherapy, a trend toward the chronicization of certain cancers has also begun to emerge.
Second, the promotion and popularization of vaccines and the establishment of public health service systems have achieved effective control over infectious diseases.
Regarding the prediction of a 120-year lifespan, it similarly follows the logic of these two pathways. With the empowerment of medical AGI, the development of medical technology and healthcare service systems is expected to achieve a qualitative leap.
Technically, medical AGI is expected to build an efficient iterative "Alpha Clinical" system, forming a technical closed loop with AlphaFold and AlphaGenome, and accelerating medical progress.
The Root of Medical Technology Breakthroughs: Exploring and Decoding Biological Mechanisms. The application of AI in the life sciences has demonstrated immense potential. AlphaFold, developed by Google DeepMind, achieves highly accurate predictions of protein 3D structures, while AlphaGenome focuses on deciphering the non-coding "dark matter" of the human genome. These technologies lay the foundation for analyzing disease mechanisms and developing targeted therapies.
Medical AGI can form a closed loop with such cutting-edge technologies, enabling AI to understand the occurrence and development patterns of diseases at the biological mechanism level, simulate the clinical thinking of doctors, and more precisely explore disease prevention and treatment plans. It cracks the biological code for extending lifespan, which is exactly the path that Wang Shirui and Future Doctor adhere to.
In this technological closed loop, the core hallmark of medical AGI is to help humanity "create medicine," rather than merely learning existing medical knowledge to become "more like a doctor."
At the level of medical service systems, medical AGI can further optimize the allocation of high-quality medical resources and extend the focus of services from treatment to prevention.
On the one hand, medical AGI scales up the replication of excellent doctors' diagnostic and treatment decision-making capabilities through technical means, greatly improving the efficiency of diagnosing and treating complex diseases. This addresses the uneven geographical distribution of high-quality resources, making high-quality diagnosis and treatment more accessible across China and even globally. On the other hand, medical AGI achieves precise disease prevention and early screening based on big data, combined with personalized health management plans, reducing the occurrence of diseases at the source.
Whether it is accelerating medical progress from a technical level or achieving high-quality integration of prevention and treatment from a service system level,The long-term value of medical AGI follows the core logic of extending human lifespan: reducing diseases at their source and better addressing existing ones. This also transforms the vision of a healthy 120-year lifespan from what seemed like an exaggerated imagination into an attainable expectation.
Health and longevity have always been an eternal theme pursued by humanity. From the perspective of the current demographic landscape, extending healthy life expectancy holds significant importance for social development. It can, to a certain extent, offset the socioeconomic impacts brought about by the declining birth rate and alleviate the pressure of a shrinking labor force. Therefore, prolonging human healthspan has become not only an individual pursuit but also a crucial task for social governance that is vital for sustainable social development and a challenge faced globally.
In Kevin Kelly's view, the practice of future doctors has already pushed medical innovation to a deeper level, creating solutions that we do not yet know or have ventured into. This is the true frontier and the core mechanism driving medical progress. Future doctors are at the center of this transformation. "What we are discussing and doing now touches the most fundamental and foundational aspects of civilization—pursuing health, longevity, inner peace, and satisfaction with life, rather than creating anxiety and fear."
At present, various participants in the medical AI field have conducted extensive exploration in functions and application scenarios such as efficiency improvement and assistance, laying the foundation for the advanced implementation of AI in the medical field. Looking at the broader picture,The realization of medical AGI and the vision of a 120-year lifespan have set new goals for medical AI. To achieve such ambitious objectives, new architectures, products, and functionalities based on AI will inevitably emerge in abundance, significantly expanding the boundaries of medical AI; AI's role in healthcare will undoubtedly unlock greater imaginative potential and developmental possibilities.