Generative Artificial Intelligence (AI) in Personalized Medicine - Global Strategic Business Report

The global market for Generative Artificial Intelligence (AI) in Personalized Medicine was estimated at US$259.2 Million in 2024 and is projected to reach US$919.2 Million by 2030, growing at a CAGR of 23.5% from 2024 to 2030. This comprehensive report provides an in-depth analysis of market trends, drivers, and forecasts, helping you make informed business decisions. The report includes the most recent global tariff developments and how they impact the Generative Artificial Intelligence (AI) in Personalized Medicine market.

Global 'Generative Artificial Intelligence (AI) in Personalized Medicine' Market - Key Trends & Drivers Summarized

Why Is the Intersection of Generative AI and Personalized Medicine Gaining Momentum?

The integration of generative artificial intelligence (AI) into personalized medicine represents a paradigm shift in healthcare, one that is being rapidly propelled by the convergence of computational innovation, genomic science, and patient-centered care models. Generative AI, which includes models capable of creating novel data outputs such as synthetic biomarker profiles, treatment simulations, or drug molecule structures has found a critical role in tailoring medical interventions to the individual level. This trend is being catalyzed by the exponential growth of multi-dimensional healthcare data, including genomic sequencing, electronic health records (EHRs), imaging files, and patient lifestyle data. As a result, AI systems can now generate predictive models that simulate disease progression or treatment outcomes with unprecedented accuracy. Hospitals and research institutions are leveraging these capabilities to refine diagnosis, personalize care plans, and streamline clinical workflows. The digital infrastructure underpinning healthcare delivery is also evolving to accommodate AI applications, supported by increasing interoperability between platforms and regulatory frameworks that promote innovation while ensuring patient safety. Additionally.

How Is Drug Discovery Being Transformed by Generative AI?

One of the most disruptive impacts of generative AI in personalized medicine is observed in the drug discovery and development sector, where AI is fundamentally altering how pharmaceutical products are designed, tested, and approved. Traditional drug discovery is resource-intensive and time-consuming, often requiring over a decade and billions in investment to bring a new drug to market. Generative models especially those built on architectures like variational autoencoders (VAEs), transformers, and diffusion models can rapidly generate and evaluate thousands of potential compounds in silico, dramatically compressing the early stages of R&D. These models are particularly effective in identifying drug candidates that align with a patient's unique genetic mutations or biomarkers, thereby aligning with the core principles of personalized medicine. Further, AI can simulate how different molecules interact with human proteins or predict the likelihood of side effects based on population-specific data, improving drug safety profiles. Startups and pharma giants alike are adopting AI-first pipelines to target niche conditions, such as rare genetic diseases, where conventional drug models are not economically viable. Partnerships between tech companies and pharmaceutical firms have become central to accelerating this trend, often resulting in joint ventures or dedicated AI drug discovery platforms. Intellectual property is also evolving, as AI-generated compounds challenge existing frameworks for patentability. Regulatory bodies are responding with adaptive guidelines, allowing faster validation of AI-developed therapies. Altogether, this technological shift is making the development of personalized therapeutics more agile, cost-efficient, and precise than ever before.

What Role Do Patients and Healthcare Providers Play in Shaping This Market?

The broader adoption of generative AI in personalized medicine is not only a function of technological readiness but also reflects changing behaviors among patients, providers, and healthcare systems. Modern patients, increasingly empowered by access to their own health data through wearables and mobile apps, are driving demand for customized care solutions. They are more inclined to seek out precision treatments that reflect their unique genetic and lifestyle profiles, creating a fertile market for AI-based diagnostic and therapeutic tools. At the same time, healthcare providers are integrating AI-powered decision support systems that generate individualized treatment recommendations, simulate treatment outcomes, and even produce personalized clinical documentation. This enhances clinical productivity and improves patient outcomes, as physicians can make more informed.

What's Fueling the Surge in Global Market Demand for Generative AI in Personalized Medicine?

The growth in the generative AI in personalized medicine market is driven by several factors directly tied to technological evolution, end-user expansion, and systemic transformation. First, the availability of large-scale, high-resolution datasets from genomics, transcriptomics, proteomics, and patient histories creates the ideal training environment for generative models, enhancing their ability to produce clinically relevant insights. Second, the decreasing cost of whole-genome sequencing and molecular diagnostics has significantly expanded the user base, making personalized care accessible to a broader population. On the technological front, rapid advancements in cloud infrastructure, edge computing, and large language model (LLM) architectures have made it feasible to process vast biomedical datasets in real time. End-use sectors such as oncology, neurology, and immunology are increasingly integrating generative AI to target disease subtypes with personalized treatment pathways, leading to better clinical efficacy and reduced adverse effects. Additionally, pharma and biotech companies are investing heavily in AI collaborations to accelerate pipeline development and reduce R&D overhead. Clinical trial optimization is another critical driver, with AI-generated virtual cohorts being used to simulate outcomes and reduce dependency on large-scale patient recruitment. Government grants, venture capital flows, and public-private initiatives are reinforcing this trend, especially in innovation hubs across the U.S., China, Germany, and South Korea. Regulatory environments are also evolving to accommodate AI-based submissions, offering faster turnaround times and greater flexibility in trial designs. Lastly, growing patient preference for individualized care plans, coupled with clinician trust in AI-generated outputs, is fueling adoption across healthcare ecosystems. Collectively, these drivers point to a robust and expanding global market for generative AI applications in personalized medicine.

Key Insights:

• Market Growth: Understand the significant growth trajectory of the On-Premise Deployment segment, which is expected to reach US$565.0 Million by 2030 with a CAGR of a 21.0%. The Cloud-based Deployment segment is also set to grow at 28.2% CAGR over the analysis period.
• Regional Analysis: Gain insights into the U.S. market, valued at $68.1 Million in 2024, and China, forecasted to grow at an impressive 22.4% CAGR to reach $141.0 Million by 2030. Discover growth trends in other key regions, including Japan, Canada, Germany, and the Asia-Pacific.

Why You Should Buy This Report:

• Detailed Market Analysis: Access a thorough analysis of the Global Generative Artificial Intelligence (AI) in Personalized Medicine Market, covering all major geographic regions and market segments.
• Competitive Insights: Get an overview of the competitive landscape, including the market presence of major players across different geographies.
• Future Trends and Drivers: Understand the key trends and drivers shaping the future of the Global Generative Artificial Intelligence (AI) in Personalized Medicine Market.
• Actionable Insights: Benefit from actionable insights that can help you identify new revenue opportunities and make strategic business decisions.

Key Questions Answered:

• How is the Global Generative Artificial Intelligence (AI) in Personalized Medicine Market expected to evolve by 2030?
• What are the main drivers and restraints affecting the market?
• Which market segments will grow the most over the forecast period?
• How will market shares for different regions and segments change by 2030?
• Who are the leading players in the market, and what are their prospects?

Report Features:

• Comprehensive Market Data: Independent analysis of annual sales and market forecasts in US$ Million from 2024 to 2030.
• In-Depth Regional Analysis: Detailed insights into key markets, including the U.S., China, Japan, Canada, Europe, Asia-Pacific, Latin America, Middle East, and Africa.
• Company Profiles: Coverage of players such as Ada Health, Antidote AI, BenevolentAI, BioSymetrics, and more.
• Complimentary Updates: Receive free report updates for one year to keep you informed of the latest market developments.

Some of the 42 companies featured in this Generative Artificial Intelligence (AI) in Personalized Medicine market report include:

• Ada Health
• Antidote AI
• BenevolentAI
• BioSymetrics
• Berg Health
• BioAge Labs
• Blackford Analysis
• Brightseed
• CloudMedx
• Deep Genomics
• Enara Bio
• Exscientia
• GNS Healthcare
• Helium Health
• Insilico Medicine
• IBM Watson Health
• Kheiron Medical
• LifeOmic
• Lunit
• Medtronic AI

This edition integrates the latest global trade and economic shifts as of June 2025 into comprehensive market analysis. Key updates include:

• Tariff and Trade Impact: Insights into global tariff negotiations across 180+ countries, with analysis of supply chain turbulence, sourcing disruptions, and geographic realignment. Special focus on 2025 as a pivotal year for trade tensions, including updated perspectives on the Trump-era tariffs.
• Adjusted Forecasts and Analytics: Revised global and regional market forecasts through 2030, incorporating tariff effects, economic uncertainty, and structural changes in globalization. Includes segmentation by product, technology, type, material, distribution channel, application, and end-use, with historical analysis since 2015.
• Strategic Market Dynamics: Evaluation of revised market prospects, regional outlooks, and key economic indicators such as population and urbanization trends.
• Innovation & Technology Trends: Latest developments in product and process innovation, emerging technologies, and key industry drivers shaping the competitive landscape.
• Competitive Intelligence: Updated global market share estimates for 2025, competitive positioning of major players (Strong/Active/Niche/Trivial), and refined focus on leading global brands and core players.
• Expert Insight & Commentary: Strategic analysis from economists, trade experts, and domain specialists to contextualize market shifts and identify emerging opportunities.
• Complimentary Update: Buyers receive a free July 2025 update with finalized tariff impacts, new trade agreement effects, revised projections, and expanded country-level coverage.