A New Turning Point in Bio-Convergence Technology: AI Innovation and Market Restructuring in the Biotechnology Industry by 2026
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Acceleration of AI-Based Biotechnology Commercialization
As of 2026, the biotechnology industry is experiencing an unprecedented wave of change through the full-scale integration with artificial intelligence technology. Notably, following the open-source release of Google’s DeepMind AlphaFold3 at the end of 2024, global bio companies are actively leveraging it for new drug development, fundamentally altering market dynamics. The global AI bio-market size reached $34.7 billion in 2026, marking a 34.2% increase from the previous year, and is projected to grow at an average annual rate of 28.7% until 2030, according to industry forecasts.
At the center of this change is the ‘BioForce H200’, a bio-specific AI chipset developed by NVIDIA, based in California, USA. This chipset has enhanced protein simulation speed by 15 times compared to existing GPUs and improved memory efficiency by 40%. NVIDIA recorded $2.3 billion in revenue from the bio sector alone in the fourth quarter of 2025, accounting for 8.3% of its total revenue. CEO Jensen Huang recently announced, “Bio-computing will be NVIDIA’s next growth engine,” and plans to invest $18 billion in the bio sector over the next three years.
The Korean bio industry is also accelerating the adoption of AI technology in line with these global trends. Samsung Biologics, headquartered in Songdo, Incheon, established an AI-based new drug development center in Boston, USA, in December 2025, and built an integrated solution linking AlphaFold3 with its own ‘Samsung BioAI’ platform. This facility has the capability to discover 50 new drug candidates annually and can reduce the development period by an average of 2.3 years compared to existing methods, according to the company. Samsung Biologics’ fourth-quarter revenue in 2025 increased by 18.7% year-on-year to 1.234 trillion won, with AI-based services accounting for 12% of the total.
Competitor Celltrion is also expanding its AI investments. Located in Yeonsu-gu, Incheon, Celltrion announced the launch of an ‘AI-Based Biosimilar Development Program’ in collaboration with the University of Cambridge, UK, in January 2026. This program is expected to reduce the development period of existing biosimilars by an average of 18 months and increase the development success rate from 23% to 41%. Chairman Seo Jeong-jin stated, “We plan to expand our market share in the global biosimilar market from the current 7.2% to 12% by 2028 through AI technology.”
Fundamental Changes in the New Drug Development Paradigm
The introduction of AI technology is transforming the fundamental approach to new drug development beyond mere efficiency improvements. Traditionally, new drug development required an average of 12-15 years and $2.6 billion in costs, but analysis suggests that utilizing AI technology can reduce this to 8-10 years and cut costs to around $1.8 billion. The impact of AI is particularly pronounced in the Target Identification stage, with the speed of discovering candidate substances improving by an average of 5.7 times compared to traditional methods, according to industry reports.
Roche, headquartered in Basel, Switzerland, is one of the leading companies driving this change. Roche entered into a strategic partnership with Google in 2025 to establish the ‘Roche AI Drug Discovery Platform’ based on AlphaFold3, with 17 new drug candidates currently being developed through this platform. Three of these substances have already entered Phase 1 clinical trials, reducing the development period by 30% compared to traditional methods. Roche’s R&D investment in 2025 increased by 22% year-on-year to $14.7 billion, with AI-related investments accounting for 35% of the total.
Johnson & Johnson (J&J), headquartered in New Jersey, USA, is also actively engaged in AI-based new drug development. In September 2025, J&J signed a tripartite cooperation agreement with Microsoft and OpenAI to establish ‘J&J Innovation Labs’. This lab operates the ‘Janssen GPT-Drug’ platform for new drug development using conversational AI, where researchers can input questions in natural language, and AI suggests optimal molecular structures. Currently, 23 new drug projects are underway through this platform, with the average development period reduced by 28% compared to traditional methods, according to the company.
Meanwhile, Illumina, headquartered in San Diego, California, is strengthening its market position through a ‘Precision Medicine Platform’ that combines next-generation sequencing (NGS) technology with AI. Illumina’s latest sequencer, ‘NovaSeq X Plus’, features an AI-based base calling algorithm that improves accuracy to 99.9% compared to previous models and reduces analysis time by 40%. Illumina’s fourth-quarter revenue in 2025 was $1.23 billion, up 16.8% year-on-year, with AI-based service revenue accounting for 22% of the total.
These changes are significantly impacting the competitive landscape of the bio-technology market. AI-native biotech startups are emerging as new competitors in the new drug development market traditionally led by large pharmaceutical companies. Particularly, AI-native biotechs like Exscientia, based in London, UK, and Generate Biomedicines, based in Boston, USA, are gaining industry attention by building pipelines on par with existing pharmaceutical companies.
Market Restructuring and Investment Trend Analysis
With the commercialization of AI bio-technology in full swing, related investments are rapidly increasing. In 2025, global venture investment in the AI biotech sector totaled $8.9 billion, a 47% increase from the previous year, accounting for 31% of total biotech investments. The increase in investment in the Asia-Pacific region is particularly notable, with Korea attracting $1.2 billion, China $2.3 billion, and Japan $800 million, making it the third-largest after the USA ($3.4 billion) and Europe ($1.9 billion).
The Korean government is also actively supporting AI bio-technology development through the K-Bio Grand Challenge program. Of the 340 billion won allocated for the 2026 budget, 40%, or 136 billion won, will be invested in AI convergence bio-technology development, with the goal of increasing Korea’s share in the global AI bio-market from the current 2.1% to 5.5% by 2030. The Ministry of Science and ICT stated, “AI bio-convergence technology is a key driver of the Fourth Industrial Revolution era,” and announced plans to create a public-private joint investment fund of 15 trillion won.
Thermo Fisher Scientific, headquartered in Waltham, Massachusetts, USA, is expanding its AI-based research equipment portfolio in response to these market changes. The ‘Orion AI Lab’ system, launched in December 2025, is an integrated solution that automates the entire process from experiment design to data analysis with AI, improving research efficiency by an average of 65%. This system has already been adopted by 127 research institutions worldwide, with 340 orders received in the first quarter of 2026 alone, projecting an expected revenue of $2.7 billion.
However, despite the rapid advancement of AI bio-technology, several challenges remain. The biggest issue is the delay in approval by regulatory agencies due to the ‘black box’ nature of AI models. The US FDA released ‘AI-Based New Drug Approval Guidelines’ in November 2025, but there is still a lack of standardized methodologies to verify the reliability and reproducibility of AI-generated data. The European Medicines Agency (EMA) has also expressed similar concerns and is requiring more rigorous clinical trials for AI-based new drugs.
Data security and privacy issues are also emerging as important concerns. AI bio-technology utilizes large amounts of genomic data and personal medical information, raising ongoing concerns about data leakage or misuse. Particularly, as companies like China’s BGI Genomics and Wanmeng Sequencing rapidly grow in the global market, discussions on data sovereignty are becoming active in the USA and Europe. The US Congress passed the ‘Bio Data Security Act’ in December 2025, taking measures to restrict the collection of genomic data by Chinese companies within the USA.
Despite these challenges, the long-term outlook for AI bio-technology is very bright. According to a recent report by McKinsey, it is expected that more than 1,000 new drug candidates will be discovered annually through AI technology by 2030, a threefold increase from the current level. Additionally, the AI-based precision medicine market is projected to grow to $217 billion by 2030, accounting for 15.3% of the overall healthcare market.
In conclusion, as of 2026, the bio-industry is undergoing fundamental changes through integration with AI technology. With the speed and efficiency of new drug development improving dramatically, a new environment is being created where new treatments can be delivered to patients more quickly. Asian countries, including Korea, are actively participating in these global trends and are strengthening their bio-competitiveness, with innovation and growth in this field expected to continue over the next few years. However, international cooperation and standardization efforts will need to be pursued in parallel to address challenges such as regulation, data security, and ethical issues.
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*The content of this article is intended for general informational purposes only and does not constitute investment advice or recommendations. Investment decisions should be made at the individual’s discretion and responsibility.*
