In response, pharma companies are investing heavily in AI to discover drugs faster and navigate industry challenges more effectively through AI implementation. Those that aren’t investing risk falling behind competitors.

We analyzed the activity of the top 50 global pharma companies by market cap, together with their subsidiaries. Using CB Insights data on investments, acquisitions, partnerships, and earnings transcripts, we examined each entity’s AI activity and then ranked them based on their preparedness to evolve with the rapidly changing AI landscape.

Please click to enlarge.

Key takeaways

• This year’s pharmaceutical AI readiness rankings show tight competition as supply chain concerns drive companies to build domestic AI-integrated facilities. Just 3.9 points separate second-place Merck KGaA (70.7) from fifth-place Roche (66.8), compared to an 11-point gap in 2023. These new domestic facilities will serve as testing grounds for large-scale AI deployment in the coming years, determining which companies gain lasting competitive advantages.
• The pharma AI leaders are playing a dual-pronged game, cracking the AI-readiness code through complementary strategies of capital deployment and strategic alliances. Lilly and Merck KGaA lead on investments (13 and 10, respectively, since August 2023), while Roche and Bayer dominate business relationships (22 and 21, respectively). External collaboration drives top rankings as breakthrough innovations increasingly emerge from partnerships rather than internal development alone.
• Oncology has established itself as the top priority for pharma AI partnerships. This field captures one-third of all partnerships, with top startups collaborating with major pharma across the entire care continuum, from tumor profiling (Caris Life Sciences) to patient monitoring (Huma).

Pharma AI arms race intensifies as supply chain fears drive domestic facility buildout

The pharmaceutical AI landscape was particularly competitive this year, with just 3.9 points separating second place from fifth place, compared to an 11-point difference in 2023’s list. This tight clustering signals AI readiness has evolved from a competitive advantage for select leaders into a strategic imperative across the entire industry. Strong execution scores throughout the industry drive this competition, stemming from three common internal AI initiatives among top performers: new AI-integrated facilities, internal LLMs, and drug discovery platforms. 

AI-integrated facilities

Supply chain disruptions from tariffs and geopolitical tensions have catalyzed massive investments in domestic facilities, with nearly every major pharma company committing billions to new US and EU manufacturing and research centers. The biggest pledges have come from J&J at $55B, Roche at $50B, and Eli Lilly at $27B.

Beyond just replacing capacity, these proposed facilities present the opportunity to execute comprehensive digital transformation strategies, incorporating automation, IoT sensors, and AI into their core workflows. Planned AI integration spans from predictive maintenance to operational optimization. These new facilities will serve as testing grounds for the large-scale deployment of AI and automation over the next several years, with companies that execute integrations most effectively gaining competitive advantages in efficiency and innovation.

Internal LLMs

Internal LLMs have become the second pillar of pharma AI deployment, with companies either developing proprietary systems or partnering with big tech to enable the automation of data querying and document processing. For example, Pfizer‘s Amazon-powered Vox platform demonstrates how companies are deploying these tools for internal researchers’ use, while companies like Merck & Co and Bayer have implemented comprehensive LLM systems across business units.

Drug discovery platforms

Drug discovery platforms constitute the third common deployment area, with virtually every top-10 company building internal AI systems to analyze data, predict drug-target interactions, and guide experimental design. Examples include Sanofi’s CodonBERT platform to aid in mRNA design and AbbVie’s ARCH platform for consolidating data and aiding in target discovery. 

These trends illustrate that AI readiness has shifted from preparedness for emerging technology to effective implementation and agility, enabling organizations to stay at the cutting edge. The scramble among major pharma companies reflects this new reality: it’s no longer about getting ready for AI but about not being left behind in its application.

External activity drives top rankings

All AI-readiness leaders invested strongly in internal initiatives; what differentiated those at the top was their external activity, both partnerships and deal-making. 

Eli Lilly, this year’s top performer, made the most dramatic leap in the rankings, jumping from #14 in 2023 to #1 this year. The company’s record-breaking GLP-1 profits powered increased investment activity, including substantial AI investments. With this financial windfall, Lilly doubled its total direct investment spending from 2022 ($0.7B) to 2024 ($1.5B), which translated directly into AI leadership. Lilly’s 13 AI investments this year outpaced every other pharmaceutical company.

Lilly’s investment strategy reveals 3 key areas where the company sees AI’s greatest potential in pharmaceuticals: drug discovery (Insilico Medicine), medical devices (RetiSpec), and regulatory solutions (Yseop). Drug discovery represents the most significant focus, accounting for half of Lilly’s AI investments. Lilly’s impressive track record in this area includes 2 portfolio companies that successfully IPO’d last year — BioAge and Alto Neuroscience — suggesting strong prospects for current investments like Insilico Medicine, which boasts a 29% IPO probability score compared to the platform average of just 1%.

Since this year’s AI readiness rankings hinged largely on external investment and partnership activity, one might expect the list to correlate with market cap. While this is generally true, 2 companies stand out as high performers with AI readiness scores that significantly exceed what their market cap would suggest: Merck KGaA and Bayer. Ranking second and third, respectively, these companies demonstrate that strategic focus can be as important as financial resources.

Both companies achieved their high rankings through significant external engagement strategies. While matching competitors on internal AI initiatives, Merck KGaA recorded the second-highest number of AI investments (10), trailing only Lilly’s 13. Bayer secured the second-highest number of business relationships with 21 AI partnerships, just behind Roche’s 22.

Strategic partnership approaches can elevate AI readiness regardless of market cap, as these examples illustrate. Breakthrough innovations often emerge from partnerships and acquisitions rather than purely internal development, with over 70% of new molecular entity revenues since 2018 coming from externally sourced products, demonstrating the importance of external collaboration.

Oncology dominates pharma AI partnerships

Oncology has emerged as the clear focus for pharma AI partnerships, capturing 1 in 3 pharma business relationships among the 50 companies analyzed — far more than any other therapeutic area. This concentration stems from both market dynamics and cancer’s data complexity. Cancer rates continue rising worldwide while the field shifts toward precision oncology, creating opportunities for pharmaceutical companies to apply AI across multiple aspects of cancer care. Furthermore, cancer drug revenues have increased 70% over the past decade, creating substantial commercial opportunity for AI-enabled drug development.

The AI startups with the highest Mosaic scores that partner with big pharma in oncology each tackle completely different pieces of the cancer puzzle. These partnerships span the entire care continuum, from liquid biopsy screening (Caris Life Sciences) and antibody therapeutics (BigHat Biosciences) to patient monitoring (Huma) and diagnostic pathology (Aignostics).

While these companies all work in oncology, they demonstrate how AI addresses fundamentally different challenges across cancer care. Cancer’s data-rich environment and biological complexity make it a natural testing ground for AI innovation, suggesting that oncology will continue to drive the most cutting-edge applications in pharmaceutical AI.

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For information on reprint rights or other inquiries, please contact reprints@cbinsights.com.

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The Denmark-based company’s revenue more than doubled from $21B to $44B between 2021 and 2024. It’s estimated to have driven half of Denmark’s GDP growth last year. 

This financial windfall has supercharged Novo Holdings, the company’s venture arm and majority shareholder, with investment capacity. Armed with this war chest, Novo Nordisk is positioning itself to shape the future of pharmaceuticals.

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Using CB Insights data, we uncovered 4 strategic priorities highlighted by Roche’s acquisitions, investments, and partnerships since Q1’23. We then categorized companies by their relationships with Roche across these priorities.

Here are 3 key takeaways from our analysis:

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What you need to know:

• Eli Lilly is using technology to reengineer how it develops treatments, leveraging AI to speed up drug discovery.
• The company is investing in novel drug delivery methods, such as targeted delivery systems, to improve treatment efficacy and the patient experience.
• Lilly is rapidly expanding its direct-to-consumer approach through LillyDirect, partnering with telehealth providers and integrating with digital pharmacies to streamline drug distribution and improve patient access.

Eli Lilly is using technology to reengineer how it develops and delivers treatments.

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What you need to know:

• In 2021, Morgan Stanley became the largest US wealth manager by assets managed.
• It achieved this by developing a self-sustaining asset-gathering funnel through the incorporation of 2 new channels beyond its flagship wealth management business.
• Its efforts and adherence to this strategy exemplify how wealth managers can turbocharge asset growth and retention through acquisitions and collaborative initiatives.

In the wake of the 2008 financial crisis, then-new Morgan Stanley (MS) CEO James Gorman decided to anchor the firm’s long-term growth in wealth management, where revenues — typically based on fees as a percentage of managed assets — are stable, recurring, and rise in tandem with market growth.

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Unlike big tech peers like Google and Meta, it’s largely kept its in-house model development activity out of the public eye. With a focus on the on-device user experience — and smaller models as a result — Apple is relying on external large language models (LLMs) from partners like OpenAI to round out its generative AI suite.

Using CB Insights data, we uncovered the 3 biggest strategic priorities in Apple’s AI strategy:

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For the networking leader, AI forms the crux of a multi-pronged strategy to steer away from pure hardware toward services and software, which offer expanded revenue streams. Cisco is investing in pure-play AI infrastructure startups, forming AI partnerships, and embedding AI in its products.

Yet Cisco is going one step further by embracing an approach to AI computing centered on Ethernet and networking fabrics. These technologies could help handle the scale the speed demanded by data- and compute-intensive AI workloads. To this end, Cisco has partnered with chip leaders like Nvidia to help businesses manage AI clusters and deployments more easily. 

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From ambient documentation to surgical tools and digital wound care, AI solutions are helping providers focus on patients, improve diagnostics, and find new ways to perform surgeries and other procedures.

To determine which health systems are most prepared for the shift, CB Insights has launched the Hospital AI Readiness Index.

We looked at the top private-sector health systems in the US (by hospital count) and ranked them based on how prepared they are to adapt to a rapidly evolving AI landscape across 2 key pillars: innovation and execution.

• Innovation: The innovation score measures a health system’s track record of developing or acquiring novel AI capabilities. This score is based on CB Insights data including patents, acquisitions, and deal-making activity. It also considers the presence of an AI-dedicated research center.
• Execution: The execution score measures a health system’s ability to bring AI-powered products and services into clinical practice as well as deploy AI internally across business and back-office functions. This score is based on CB Insights data including business relationships, product launch media mentions, and earnings transcripts.

Below, we present the 25 health systems (inclusive of subsidiaries and venture arms) most prepared for AI.

Want to dive into key data featured in this index? CB Insights customers can check out the links below:

• AI investments
• AI acquisitions
• AI patents

Leaders

Mayo Clinic leads in AI readiness primarily due to its relatively high level of AI innovation. 

Its innovative nature is reflected in part by its patent activity. For example, Mayo has filed 50+ patents across areas like cardiovascular health and oncology. It has also invested in AI-enabled companies addressing a range of use cases in healthcare, from clinical documentation to surgical intelligence.

Intermountain Health and Cleveland Clinic round out the top three. 

Notable activities for these players include Intermountain’s internal development of a real-time clinical decision support platform. Meanwhile, Cleveland Clinic stands out on the execution front due to its high volume of AI-focused business relationships, such as a partnership with PathAI focused on leveraging pathology algorithms to enhance translational research and clinical care.

Source: CB Insights — Cleveland Clinic Business Relationship Insights

Innovation

Innovation scores are based on the presence of an AI-dedicated research center and CB Insights data on AI-related patents as well as acquisitions and deal-making activity since 2019 (as of 5/29/2024).

The most active health system in terms of investment count is Mayo Clinic. Its investments highlight areas where AI is picking up steam in healthcare. For example, at the end of 2023, it participated in a funding round for Abridge — a startup that helps transcribe patient-provider conversations and create clinical notes using generative AI — alongside investors like CVS Health Ventures, the American College of Cardiology, and Kaiser Permanente Ventures. Mayo Clinic has also funded companies like Theator, which combines computer vision and AI to help surgeons draw and act on insights from videos of procedures.

Intermountain Health is the second most active AI investor among evaluated health systems. Via its venture arm, Intermountain Ventures, it backed AI-powered patient engagement platform Gyant, which has since been acquired. Most recently, its venture arm invested in Freenome, which develops blood tests for early cancer detection.

When it comes to patent count, Mayo Clinic and Cleveland Clinic lead the pack. 

One focus area for Mayo Clinic is cardiovascular health. For example, in 2022, it was granted a patent for a system that uses a machine learning model to analyze electrocardiogram (ECG) data and predict the likelihood that a patient will have a stroke. 

Source: CB Insights — Mayo Clinic patents

Meanwhile, Cleveland Clinic was granted a patent for a decision support system that utilizes machine learning to individualize radiotherapy doses, enhancing the precision and effectiveness of cancer treatments.

The evaluated health systems are not overly acquisitive — just one has inked an acquisition in the past 5 years: Providence. In 2019, it acquired Lumedic, which uses blockchain and AI to streamline healthcare revenue cycle management.

Execution

Execution scores are based on CB Insights data including AI-related business relationships, product launch media mentions, and earnings transcripts since 2019 (as of 5/29/2024).

The majority of the health systems evaluated for this ranking have established business relationships with AI-enabled companies.

For example, in 2024 so far:

• Mayo Clinic teamed up with Techcyte to develop a platform that will help healthcare organizations harness AI in their pathology practices.
• Meanwhile, Banner Health worked with Regard to ease the administrative burden on clinicians by automating key tasks, like notetaking and chart reviews.
• Johns Hopkins Medicine partnered with Healthy.io to offer digital wound care services to patients.

Few evaluated health systems have earnings calls, as many are non-profit organizations with different financial reporting requirements than publicly traded companies. However, earnings calls among systems that do hold them reveal how AI is coming into view in a hospital setting. 

For example, Community Health Systems’ EVP of clinical operations, Miguel Benet, highlighted how AI could be deployed to streamline clinical documentation on an earnings call in Q4’23. He also discussed how CHS is using AI to provide patients with relevant information regarding local resources upon discharge — an initiative that has already yielded positive results, such as reductions in length of stay.

Source: CB Insights — Community Health Systems earnings transcripts

Four of the health systems on this list have launched AI-enabled products. 

For example, last year, Intermountain Health developed a platform equipped with real-time clinical decision support tools that leverage AI to improve patient diagnosis and treatment. Just a few months ago, CommonSpirit Health launched Insightli, an internal AI assistant capable of generating written content.

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Major players like BP and Shell are aiming to become net-zero emissions energy businesses by 2050, with Shell targeting a 50% emissions reduction by 2030 compared to 2016 levels.

These ambitious goals are driven in part by shifting regulatory frameworks. The EU, for instance, plans to require oil & gas companies to buy carbon credits to compensate for offshore activities, while in the US, the Inflation Reduction Act has incentivized sustainable aviation fuel (SAF) production.

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The pharma giant is partnering with companies to speed up drug discovery using AI. These efforts extend across its core R&D focus areas, including immunology and oncology.

The company is also leveraging partnerships and investments to enhance clinical trials and bring its 75+ clinical-stage projects to market more quickly. For example, Sanofi Ventures led a Series B round for Nucleai, which uses AI to help drugmakers understand how patients will respond to their drugs and, as a result, select the most suitable patients for clinical trials.

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While Nvidia initially developed its graphics processing units (GPUs) for gaming, these chips turned out to be ideal for powering AI tasks. Now, the company is focusing its efforts on providing the computing hardware — notably its A100 and H100 GPUs — and the software infrastructure required for developing generative AI applications.

Amid the generative AI rush, Nvidia has grown rapidly. In fact, it recently surpassed Microsoft and Apple to become the world’s most valuable company. To bolster its leadership position and keep ahead of AI computing competitors like AMD and Intel, Nvidia has forged relationships with companies across the AI landscape.

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Assisted driving technologies also remain a core interest. In addition, automotive leaders are exploring the potential of humanoid robots to automate automotive manufacturing processes.

Below, we use CB Insights data on automotive leaders’ investments, acquisitions, and partnerships as well as earnings calls to benchmark their activity so far this year.

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To do that, the company is prioritizing growth opportunities that augment its core business, with recent actions laddering up to broad themes like improving decision-making in claims and underwriting.

Notably, M&A activity is absent from Nationwide’s strategy. Instead, it grows its network of relationships through investments — at the corporate level and through its CVC arm, Nationwide Ventures — and partnerships.

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Automakers have pursued cleaner, connected, and autonomous vehicles via a mix of acquisitions, investments, and partnerships. However, their strategies have evolved over the past few years.

For instance, many automakers have adjusted their plans for electric vehicles (EVs) in response to market pressures. General Motors recently rolled back its EV production goal for North America in 2024.

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But when it comes to leaders’ investments and partnerships, cross-border payments expansion and digital wallet integration continue to dominate. 

A newer focus has also emerged: crypto. Though not discussed in their earnings calls, payments leaders are reengaging with digital currencies after pulling back in recent years.

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These tech moves reveal shared strategic themes across the industry.

Cyber risk — which primarily covers cyber capabilities related to insurance coverage, as well as tools for internal cybersecurity operations — is the top tech priority among leading insurers like AXA and Allianz in our analysis.

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It’s tackling the issue on all fronts, from investing in AI-enabled care models via Google Ventures, to forging partnerships through its Google Cloud division, to launching new products that tailor generative AI to healthcare use cases.

These moves seek not only to address the challenges facing the sector, but also to strategically differentiate Google from big tech peers like Nvidia, Microsoft, and Amazon — all of whom are making concerted efforts to integrate AI into healthcare.

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The data management company has seen a surge in demand from enterprises clambering to take advantage of generative AI. The company’s revenue grew to $1.6B for the fiscal year ending in January 2024 — up over 50% YoY — and it has looked to sustain its growth with product expansion and acquisitions. 

One of the company’s biggest recent moves was its acquisition of MosaicML in June 2023 for a whopping $1.3B (at a 65x revenue multiple). The MosaicML team ultimately helped build Databricks’ open-source large language model (LLM), DBRX, which it released in March 2024. 

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The tech giant found a major entry point into healthcare workflows when it acquired Nuance for $19.7B in 2022. It followed up on this by expanding its existing relationship with leading EHR vendor Epic to introduce generative AI across clinical workflows, with the aim of improving provider efficiency and mitigating staffing shortages.

Microsoft’s recent relationships also point to an increasing focus on developing and deploying generative AI in the pharmaceutical industry. The tech behemoth is partnering with and investing in startups in drug development, where early applications of generative AI have seen especially strong investor and commercial traction.

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The company has faced multiple high-profile incidents over the past 6 years — including crashes involving its planes and a fuselage blowout. This series of events has resulted in a decline in consumer trust, aggravated airlines, and lost sales to rival Airbus.

Amid these challenges, Boeing has shaken up its corporate leadership and moved to improve its manufacturing quality. For instance, the company is exploring a reintegration with Spirit AeroSystems to help address production flaws.

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To reach that goal, the pharma giant is investing internally — it has 178 projects in the pipeline and spent nearly $11B on R&D last year, up 12% from 2022 — as well as looking to emerging technologies that can help it fire on all cylinders.

AstraZeneca has been strategically partnering with companies offering AI drug discovery, diagnostics, and real-world data to help offset some of the cost of drug development and speed up the process. For example, it signed a $247M deal with Absci in December 2023 to develop generative AI-designed antibody therapies for cancer.

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Its corporate venture arm, MassMutual Ventures, was among the top 25 most active CVC firms in 2023, backing 22 companies. Insurance sales are MassMutual’s foundational growth driver, so the company prioritizes investments to serve policyholders — and sell more insurance. 

But its reach extends far beyond core life insurance. The company also offers annuities, retirement plans, and other financial products to businesses and consumers.

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The company maintains a robust internal combustion portfolio, but it has aggressively invested across the entire vehicle electrification ecosystem. Despite scaling back its EV production goals to account for fluctuating consumer demand, GM remains committed to electric vehicles and plans to have the capacity to produce 1M EVs by 2025.

Meanwhile, GM has also pulled back from fully autonomous driving by reducing spending on Cruise — its autonomous vehicle (AV) subsidiary — and moved investments away from AV companies. However, the company has retained its focus on its advanced driver assistance system (ADAS), Super Cruise.

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Its planned $35B acquisition of Discover Financial, announced in February 2024, would make Capital One the owner of Discover’s payments network and open the door to more high-spending, low-risk customers. It would also make Capital One the largest card issuer in the US with 19% of the revolving consumer loan market, ahead of current leader JP Morgan Chase’s 16%.

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The index calculates innovation by analyzing CB Insights data on acquisitions, dealmaking activity, and patent filings for each player, and it calculates execution based on earnings transcript mentions, partnership & licensing agreements, and product launches.

Below, we look at how prepared the top 50 insurance companies (inclusive of subsidiaries) are to adapt to a rapidly evolving AI landscape across 2 key pillars: innovation and execution.

• Innovation: The innovation score measures an insurance company’s track record of developing or acquiring novel AI capabilities. This score is based on CB Insights data including patents, acquisitions, and dealmaking activity.
• Execution: The execution score measures an insurance company’s ability to bring AI-powered products and services to market, as well as deploy AI internally across corporate functions. This score is based on CB Insights data including business relationships, product launch media mentions, and earnings transcripts.

Want to dive into key data featured in this index? CB Insights customers can check out the links below:

• AI investments
• AI acquisitions
• AI patents
• AI earnings call mentions

Leaders

Cigna leads in AI readiness, primarily due to its relatively high level of AI innovation. For example, the company is actively patenting AI-related tech. It has also funded companies with diverse AI use cases (like digital twin leader Aitia) and acquired AI-enabled solutions (like care navigation platform Bright.MD). When it comes to execution, however, Cigna lags behind some of its peers — this is due in part to lawsuits over alleged AI-guided claims denials.

Travelers and Munich Re round out the top 3. Notable AI initiatives for these companies include Travelers’ $435M acquisition of AI-powered cyber insurance startup Corvus Insurance. Meanwhile, Munich Re actively invests in and partners with AI-enabled companies like Augury.

GenAI-powered products are increasingly coming into focus for leaders in the space. More than 10 of the assessed companies have publicly announced genAI products, many of which are focused on operational improvements, such as claims processing and document summarization.

Innovation

Most assessed companies have demonstrated measurable AI innovation across various focus areas, although innovation scores generally lag behind execution scores.

Only 4 of the top 50 insurance companies — Cigna, Centene, Travelers, and Willis Towers Watson — have made an AI acquisition since 2019 (as of 2/16/24). Additionally, one of these acquisitions has since been divested: Centene sold Apixio to investment firm New Mountain Capital last year. However, 2 of these deals occurred just last quarter amid a boom of executive attention on AI. Travelers acquired Corvus Insurance and Cigna’s Evernorth picked up Bright.MD.

UnitedHealth Group and MassMutual lead in AI startup investments, as each company has inked 25+ deals since 2019. In fact, among assessed insurance companies, MassMutual was the most active AI investor in 2023 with 4 investments, most of which were focused on cancer treatment.

Just 5 companies — State Farm, UnitedHealth Group, Allstate, Cigna, and The Hartford — have accounted for the vast majority of the 900+ US AI patents filed by the evaluated cohort. State Farm alone has filed 300+ patents, including over 50 related to computer vision.

Execution

While AI execution scores vary among assessed companies, no player has emerged as a singular leader in this capacity.

Twenty-eight of the top publicly traded insurance companies have discussed AI strategies on earnings calls at least once since 2019. AI mentions surged in 2023, underpinned by discussion of genAI adoption from companies including Aon, Travelers, and UnitedHealth Group.

Meanwhile, 34 of the 50 insurance companies analyzed have entered into partnership or licensing agreements with AI startups. To highlight a few:

• AXA partnered with Kayrros to launch a wildfire risk management service last year.
• Munich Re partnered with EvolutionIQ in 2022 to support AI-enabled claims guidance for disability insurance carriers.
• Last year, Swiss Re and One Concern forged a strategic partnership focused on business interruption underwriting for natural catastrophe-related risks.

Many of the evaluated companies have also launched AI-enabled products. These efforts have commonly centered on opportunities within claims, operations, and underwriting. For example, Elevance Health is using genAI to analyze health data and provide members with care recommendations, while Liberty Mutual is analyzing loss data with AI. Multiple companies — including AXA and Manulife — are implementing internal genAI tools for employees.

Even so, a few insurance companies have faced lawsuits over their use of AI, which has weighed on their execution scores. For instance, separate lawsuits were filed against Humana and UnitedHealth Group in Q4’23 over their alleged use of AI to deny care for older adults.

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