Merck Announces $1 Billion Strategic AI Partnership with Google Cloud

On April 22 local time, Merck & Co. and Google Cloud jointly announced a multi-year strategic collaboration agreement valued at up to $1 billion, under which an Agentic Platform will be deployed across Merck’s research and development, manufacturing, commercial, and functional departments. Additionally, Google Cloud engineers will collaborate with Merck teams to implement Google Cloud’s most advanced AI technologies, including Gemini Enterprise.

Under the agreement, this collaboration will combine Merck’s scientific research and data leadership with Google Cloud’s leading AI and cloud platform capabilities, aiming to achieve data digitization. Notably, this partnership represents Merck’s largest and most in-depth initiative in the field of artificial intelligence.

One highlight of this deal lies in its collaboration model.

Generally, collaborations between traditional pharmaceutical companies and technology firms typically follow a client-vendor relationship, wherein the pharmaceutical company purchases software and the technology firm provides services. However, under the agreement, Google Cloud engineers will work alongside Merck’s team to jointly deploy AI systems. In other words, Merck aims to have Google’s engineering team directly embedded within its operations, integrating Google’s technological capabilities with Merck’s organizational synergy.

Another distinctive feature lies in the scope of coverage. The agreement explicitly deploys AI across Merck’s R&D, manufacturing, commercial, and corporate functions, which can be understood as a company-wide systemic initiative. As Dave Williams, Chief Information and Digital Officer at Merck, stated, “We are in one of the most important product launch cycles in our company’s history. AI agents and generative tools will help our teams reengineer processes at scale globally, bringing scientific breakthroughs to patients faster.”

Furthermore, the duration of the partnership is also noteworthy. In an interview, Williams stated that the collaboration is expected to last at least ten years, representing a long-term strategic alignment. Thomas Kurian, CEO of Google Cloud, defined it as “a fundamental shift in the technology supporting the pharmaceutical value chain.”

From the perspective of specific application scenarios, this $1 billion investment covers multiple aspects.

First, in the R&D domain, both parties will deploy Gemini Enterprise to integrate it into the end-to-end R&D workflow, including computer-simulated experiments and clinical study report writing. Previously, Merck & Co. had already achieved initial results in this area by announcing a collaboration with McKinsey and its AI division, QuantumBlack, to develop an internal generative AI platform aimed at accelerating the drafting of clinical study reports. This initiative reduced the time required to produce first drafts of clinical study reports from 180 hours to 80 hours, while cutting error rates by 50%.

On the production side, predictive analytics and intelligent automation are leveraged to optimize manufacturing processes, thereby reducing deviation rates and increasing output.

In terms of commercial implementation, the agreement stipulates data-driven personalized patient engagement to enhance drug accessibility and patient adherence. Functionally, AI automation can improve internal operational efficiency.

In fact, Merck & Co. has over a decade of history in the research, development, and application of data science, AI, and machine learning, but the true acceleration began in 2022.

In November 2022, Merck & Co. entered into a research collaboration with BigHat Biosciences, an AI-driven antibody discovery company, to design candidate antibodies using BigHat’s technology platform that integrates high-throughput wet-lab experiments with machine learning. At the time, Juan Alvarez, Vice President of Biologics Discovery at Merck Research Laboratories, stated that this partnership expanded Merck’s strategy for applying AI/ML in its drug discovery capabilities.

In September 2023, Merck & Co. initiated a collaboration with the Danish AI immunology company Evaxion Biotech on vaccine projects. In September 2025, Merck formally exercised its option to acquire Evaxion’s preclinical vaccine candidate, EVX-B3.

In June 2025, Merck & Co. disclosed that its internal generative AI platform, GPTeal, had achieved substantial results. In the same month, Merck partnered with Variational AI to leverage its Enki platform for generative AI-driven drug design targeting two specified small-molecule targets. In August, Merck further collaborated with Turbine to utilize AI-driven simulated cell and tumor models for the development of therapies for refractory cancers.

At the start of 2026, Merck & Co. further accelerated the pace of its AI-related business development deals. In January, it reached a companion diagnostic and commercialization agreement with Guardant Health and became a founding participant in Illumina’s “Billion Cell Atlas” project. In February, it partnered with the Mayo Clinic to combine Merck’s AI/ML capabilities with the Mayo’s clinical, imaging, and genomic datasets. In March, it expanded its collaboration with Tempus, focusing on AI-driven precision medicine and biomarker discovery, and signed a collaboration agreement with Infinimmune valued at up to $838 million.

Each of the aforementioned collaborations targeted a specific technological gap or pipeline need; by contrast, the current partnership with Google Cloud appears more systematic. This systematic approach is also rooted in prior developments.

Just as Eli Lilly has its GLP-1 product tirzepatide, Merck & Co.’s flagship product Keytruda (commonly known as “K drug”) achieved approximately $31.64 billion in sales in fiscal year 2025, accounting for nearly half of the company’s total revenue. Since surpassing Humira to become the world’s top-selling drug in 2023, Keytruda’s cumulative sales have exceeded $100 billion.

Multinational corporations (MNCs) are increasingly moving to mitigate the risks associated with reliance on a single blockbuster product, and Merck & Co. is no exception. With the core patents for Keytruda set to expire in 2028, the window of opportunity to fill the resulting revenue gap is rapidly narrowing. Dave Williams explicitly highlighted this context in his official announcement: “We are in one of the most important product launch cycles in the company’s history.” This indicates that the push into AI also carries strategic considerations aimed at “accelerating innovation and bridging the revenue gap.”

If we do a rough calculation, Merck & Co.’s revenue in 2025 was approximately USD 65.011 billion. A USD 1 billion investment accounts for about 1.5% of its annual revenue. If the systematic deployment of AI can indeed shorten the time to market for the next blockbuster drug after Keytruda by 6–12 months, the incremental revenue generated could far exceed USD 1 billion.

In the AI strategic race among multinational corporations (MNCs) during 2025–2026, all major industry giants were present. If judged solely by individual deal sizes, initiatives such as Eli Lilly’s collaboration with NVIDIA to build an AI supercomputing infrastructure, AstraZeneca’s ambitious $80 billion revenue target, and Sanofi’s “all-in” AI strategy driven by its internal platform may appear more high-profile. However, Merck & Co. distinguishes itself through its extensive coverage, deeper penetration, and its approach of leveraging external partnerships to drive internal transformation.

According to the company’s disclosure, following this collaboration with Google Cloud, AI tools will be deployed to 75,000 employees worldwide. This means that Merck & Co. is gaining not only access to AI tools but also the opportunity to internalize Google’s technological capabilities into its own organizational competencies. Such a model of “technology transfer + joint capability building” remains rare in the pharmaceutical industry.

Meanwhile, the signal sent by this deal is clear: the deployment of AI in the pharmaceutical industry has long moved beyond the experimental phase to become a “strategic imperative,” evolving into a core infrastructure. Once the clinical data for the first batch of AI-discovered molecules meet their endpoints in 2026, the gap between market consensus and actual value will narrow further.