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.

RELATED RESEARCH FROM CB INSIGHTS

• The AI in drug R&D market map
• 3 shifts that will define the future of medtech
• Inside Novo Nordisk’s $33B manufacturing push to strengthen its obesity portfolio and build a biologics powerhouse
• Here’s how the 100 most promising AI startups in 2025 compare by the numbers
• The humanoid robots market map

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In response to these cost pressures, pharma companies are using AI to make R&D more efficient. These capabilities enable organizations to quickly identify and evaluate promising drug candidates, influencing the selection of therapeutic approaches that advance to development.

AI could potentially cut years off the discovery process and compress clinical trial times by up to 30%. This would accelerate the delivery of new treatments to patients, unlock novel treatment approaches, and enable more personalized medicine. Companies that effectively leverage these AI capabilities will gain crucial advantages in speed, precision, and breakthrough discoveries.

Our analysis maps 225 AI-driven drug R&D companies across 27 markets. Below the map, we break down several trends shaping the future of pharmaceutical innovation, as well as share the methodology we used to select and categorize companies.

Please click to enlarge.

Note: This market map is not intended to be exhaustive, and categories are not mutually exclusive. For more, see the detailed methodology at the bottom of this report.

Key takeaways

• • AI tools for clinical development are more commercially mature than the emerging field of preclinical applications. According to CB Insights’ Commercial Maturity scores, 37% of clinical development companies have reached the most mature commercial stages (4: Scaling or 5: Established) compared to just 7% of preclinical companies. Late-stage funding follows a similar pattern — 9% of clinical development funding since 2023 has gone to late-stage companies, compared to just 3% for preclinical tools.
  • AI funding in drug R&D rebounded in 2024, with discovery engines capturing the majority of investments amid consolidation in the clinical trial sector. In 2024, equity funding grew to $3.8B (up from $3B in 2023), with AI-derived biologics and small molecules attracting $1.1B and $1B, respectively. Early 2025 momentum suggests the sector is on track to match last year’s strong performance.
  • Patient recruitment platforms and clinical trial management systems demonstrate the strongest momentum. Examining market performance through average CB Insights Mosaic scores (a proprietary measure of private-company health and growth), EHR-based recruitment platforms lead (716 out of 1,000), while trial management systems show highest deal growth (+150% YoY). Look to these markets as high-growth areas to track within the AI drug R&D space.

Clinical development AI tools have achieved commercial maturity, while preclinical applications offer emerging investor opportunities

The adoption of AI in drug R&D is still emerging, and its pace varies across different sectors.

While early-stage funding dominates all sectors, preclinical development remains the most nascent, with 81% of funding since 2023 directed to early-stage deals and only 3% to late-stage deals. 

Clinical development shows greater maturity — still led by early-stage deals, but with a more established cohort of companies in later stages (70% early-stage, 9% late-stage funding).

CB Insights’ Commercial Maturity metrics further highlight this disparity. 

In preclinical development, 45% of companies are in the earliest commercial stages (1: Emerging and 2: Validating) compared to 32% in discovery and just 15% in clinical development. 

Conversely, only 7% of preclinical companies have reached the most mature stages (4: Scaling or 5: Established) vs. 11% in discovery and a substantial 37% in clinical development.

The disparities in maturity stem from each sector’s unique characteristics:

• Clinical development AI solutions often build upon existing healthcare technology infrastructure, facilitating faster adoption. 
• The use of AI in discovery carries higher investment risks as companies develop unproven molecules from scratch. 
• Preclinical development, positioned mid-pipeline, offers more specialized solutions and faces stricter regulatory scrutiny, explaining its slower advancement despite growing momentum.

For investors, this creates a clear distinction: Clinical development companies provide stronger near-term return potential, while the emerging preclinical space offers better opportunities to establish early market advantages.

Explore all 700+ AI in drug R&D companies

Drug R&D AI funding recovers as discovery engines lead investments amid clinical trial sector consolidation

After declining YoY between 2021 and 2023, equity funding across AI in drug R&D rebounded in 2024, growing from $3B to $3.8B and significantly surpassing pre-pandemic levels ($2.7B in 2019). The momentum continues in 2025, which, after Q1, is on pace to match 2024’s performance, bolstered by Isomorphic Labs‘ $600M Series A round in March 2025.

Among markets, discovery engines led funding in 2024, with AI-derived biologics securing $1.6B in equity funding and AI-derived small molecules attracting $1B. This aligns with these companies’ higher funding requirements for developing therapeutics and conducting clinical trials. It also demonstrates investors’ strategic bets on AI’s potential to slash drug discovery timelines — with discovery engines serving as the primary vehicles to prove this capability.

Enveda stands out here, having raised a $130M Series C in November 2024, followed by an additional $20M investment from Sanofi in February 2025 — a strong endorsement of its platform, which combines machine learning, metabolomics, and robotics to identify novel compounds from medicinal plants. The company’s recent collaboration with Microsoft Azure (May 2024) further positions it to scale its generative AI capabilities.

Beyond discovery engines, quantum computing platforms had an exceptional 2024, raising $376M, while decentralized clinical trial platforms followed, securing $129M. Huma led the latter group with an $80M Series D round in July 2024, while the market simultaneously underwent a wave of consolidation, with 5 acquisitions in 2024 alone, doubling all exits since 2020. 

However, among these acquisitions, only Aparito (purchased by Eli Lilly in July 2024) leverages AI in its offerings through its Atom5 platform, which enables comprehensive remote data collection and AI-powered data analysis.

Analyze AI in drug R&D deals

Patient recruitment and quantum computing lead commercial momentum in AI-driven R&D

According to CB Insights’ Mosaic scores, the highest-momentum AI markets across phases of drug R&D are: 

• Discovery: Quantum computing
• Preclinical development: Drug development strategy & compliance platforms
• Clinical development: EHR-based patient recruitment platforms

Among these high-potential sectors, several companies are making significant advances. 

SandboxAQ (Mosaic score: 843) leads in the quantum computing space; its 2023 release of the AQBioSim technology stack combines AI and quantum algorithms to predict molecular behavior and accelerate drug discovery. This expansion into biotech applications attracted Sanofi, resulting in a partnership in October 2024. 

In the regulatory domain, Weave (Mosaic score: 575) has positioned itself as an early mover in AI-driven regulatory automation for life sciences. Its AutoIND platform, launched in 2024, claims to reduce IND application timelines by up to 70%. 

Among these top 10 markets, trial recruitment optimization tools and clinical trial management systems showed the most growth in deals from 2023 to 2024. This illustrates increasing investor confidence in technologies that address critical bottlenecks in clinical trial efficiency and challenges related to patient enrollment.

In these markets, the companies with the highest Mosaic scores demonstrate rapid advancement and growing investment appeal:

• In the clinical trial management space, Lindus Health (Mosaic score: 874) secured a $55M Series B round in January 2025 and established a partnership with the Clinical Data Interchange Standards Consortium (CDISC) in February 2025. This collaboration with CDISC — a nonprofit that sets standards mandatory for FDA submissions — focuses on automating data standardization using Lindus Health’s AI platform for trial protocol generation and analysis.
• Paradigm Health (Mosaic score: 822) leads in trial recruitment optimization with its AI-driven platform for patient recruitment and trial management. Its deployment across 400 research sites and 1,000 healthcare provider locations in 3 countries helped it secure a $203M Series A in January 2023. In November 2024, Japan’s National Cancer Center selected Paradigm for its nationwide clinical trial network to advance precision medicine initiatives, expanding the company’s footprint in the Asian oncology research market.

These market signals suggest AI’s most immediate and transformative impact on drug development will come not from scientific breakthroughs alone, but from technologies that systematically eliminate the operational inefficiencies that have historically extended development timelines and inflated costs.

Dive into all drug R&D tech markets

Methodology

To identify players for this market map, we reviewed AI companies in drug R&D markets and included startups with a Mosaic score of 400+ that have raised funds within the last 5 years. For markets where these criteria identified more than 20 companies (AI-derived small molecule drugs, AI-derived biological drugs, and molecular design platforms), we selected those that had raised at least $20M in funding. If further reduction was needed, only companies in the top 20 Mosaic scores are shown. 

Categories on the market map align with our recent 3-part series on AI in drug R&D:

• Discovery encompasses workflows from project inception through lead selection, where discovery platforms are companies whose products are AI software systems, while discovery engines are companies whose products are therapeutics discovered using proprietary AI systems. 
• Pre-clinical development covers lead development to the first regulatory filing (an Investigational New Drug (IND) application in the United States)
• Clinical development spans from the start of clinical trials through commercialization. 

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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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The sector also showed renewed vitality through the return of billion-dollar M&A deals and the highest quarterly addition of new unicorns in nearly three years. These developments further confirm that the digital health landscape is prioritizing specialized market leaders over broader capital distribution. 

Key takeaways from the report include: 

• Investors are concentrating capital in fewer, higher-quality bets. Equity funding jumped 47% QoQ to reach the highest level since Q2’22, even as deal count dropped 9%. Startups with strong clinical validation, demonstrable ROI, and scalable business models are leading the pack. 

• Mega-rounds are back, and AI is claiming most of them. Funding from mega-rounds ($100M+ deals) surged to $2.5B across 11 deals in Q1, capturing 46% of all digital health funding — the highest share since Q4’21. AI-focused startups secured 8 of these 11 mega-rounds, signaling where investors expect outsized returns. 

• AI companies are capturing more than half of digital health funding. AI startups raised $3.2B in Q1, or 60% of all digital health funding — up from 41% in 2024. Top-funded segments included AI-derived small molecule drug discovery and clinical documentation tools, underscoring the shift toward targeted, high-impact applications. 

• Billion-dollar deals mark a digital health M&A revival. M&A activity surged 27% QoQ to 51 deals in Q1, with the US driving growth and two $1B+ acquisitions (CentralReach and Alto Pharmacy) demonstrating renewed market confidence in high-value digital health platforms. 

• Unicorn creation rebounds, driven by AI-native platforms. Digital health saw 6 new unicorns in Q1’25 —  more than in all of 2024 — and the highest quarterly total since Q2’22. With half focused on AI for provider workflows, the data suggests investor conviction is highest where AI directly supports care delivery.  

We dive into the trends below. 

Investors are concentrating capital in fewer, higher-quality bets

Digital health equity funding surged 47% QoQ, making it the strongest quarter since Q2’22. But while capital surged, deal volume slipped 9%, underscoring a broader VC trend: fewer bets, bigger checks.. This consolidation pushed the global median deal size from $5.4M to $6.4M. 

This growth was powered by a handful of major raises, most notably Isomorphic Labs‘ record-breaking $600M Series A on the final day of Q1. This investment — the largest ever for AI in drug discovery — will support the company’s evolution from an AI molecular design platform to a comprehensive therapeutic discovery engine. 

Deal stage distribution also shifted. Early-stage deal share declined from 60% of total volume in 2024 to 51% in 2025 YTD, while mid and late-stage deal shares increased slightly. But the most striking change was in deal size: median late-stage deal size grew 96% QoQ, compared to 41% for mid-stage and 25% for early-stage rounds.  

This late-stage surge reflects investor preference for companies with regulatory milestones and scalable AI platforms. Examples include Saluda Medical, which received FDA approval for its Evoke System; Insilico Medicine, advancing drug candidates to clinical trials; and Innovaccer, now serving 6 of the top 10 US healthcare systems.  

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Mega-rounds are back, and AI is claiming most of them 

Mega-rounds made a strong comeback in Q1’25, totaling $2.5B across 11 deals — more than double Q4’24’s funding, despite only a modest uptick in volume. These $100M+ investments captured 46% of all digital health funding, marking the highest concentration of capital in mega-rounds since Q4’21 and signaling renewed investor confidence in mature digital health companies. 

AI-focused startups dominated these large investments, securing 8 of the 11 mega-rounds in Q1. Standout deals include Isomorphic Labs’ $600M Series A for therapeutic development, Truveta‘s $320M Series C for electronic health record (EHR) data analytics, and Innovaccer’s $275M Series F for its clinical decision support platform. 

Explore this quarter’s mega-rounds

AI companies are capturing more than half of digital health funding

AI now accounts for the majority of digital health funding, pulling in 60% of Q1’25 investment — up from 41% in 2024 and 37% in 2023. This quarter marks the first time AI companies have captured more than half of all digital health dollars, signaling a structural shift likely to continue as the sector matures.   

Despite an overall decline in digital health deals, AI digital health deal volume rose 6% QoQ — from 109 in Q4’24 to 116 in Q1’25 — underscoring sustained investor appetite for AI-driven solutions. The top-funded AI markets were AI-derived small molecule drugs ($204M across 5 deals) and clinical documentation solutions ($372M across 4 deals). 

The surge reflects not just hype, but real traction: AI is evolving from general-purpose tools to vertical-specific, regulatory-compliant platforms that address provider burnout, accelerate R&D, and improve diagnostics.  

High-momentum startups in Q1’25 — according to CB Insights’ Mosaic score — include Ubie (Mosaic score: 922), which offers an AI-powered symptom tracker, and Suki (Mosaic score: 913), a voice assistant for clinical documentation.  These use cases show how AI is delivering measurable clinical and operational value across the ecosystem. 

See 370+ high-potential AI startups in digital health

Billion-dollar deals mark a digital health M&A revival

M&A activity surged 27% QoQ to 51 deals in Q1, reaching its highest level since Q1’23. This growth was driven entirely by US companies, where deal volume increased 85% QoQ to 37, while Europe dipped slightly (12 to 10 deals) and Asia saw just 1 deal, down from 3. 

The quarter featured two $1B+ acquisitions — the first such deals since Q2’22 — signaling the return of strategic buyers to the market. Roper Technologies‘ acquired CentralReach, an autism and IDD care software provider, for $1.6B and Paulus Holdings purchased digital pharmacy platform Alto Pharmacy for $1.5B. 

These acquisitions highlight a strategic shift toward platforms with market dominance and proprietary data. Alto Pharmacy serves more than 500,000 patients and captures deep insights into medication use and patient behavior. CentralReach supports 200,000 users with rich clinical and behavioral datasets for autism and IDD care. Strategic buyers are showing a clear willingness to pay premium valuations for scaled operations paired with hard-to-replicate data ecosystems.  

Unicorn creation rebounds, driven by AI-native platforms 

6 new unicorns were minted in Q1’25 –  the most in a single quarter since Q2’22 – but with  a striking difference in scale. Today’s unicorns are leaner, averaging just 196 employees compared to 408 during the 2021-2022 boom. OpenEvidence reached the milestone with a team of just 21. 

They’re also reaching unicorn status faster. The average time to unicorn this year has fallen to 6 years from 7 in 2022, with Hippocratic AI setting the pace — hitting a $1B+ valuation just two years after its founding in 2023. 

Regionally, the US led the charge with 4 new unicorns, while Europe contributed 1 and Asia celebrated its first digital health unicorn birth since 2021.  

Half of these newly minted unicorns apply AI to support provider workflows: Hippocratic AI (patient follow-up), Abridge (clinical documentation), and OpenEvidence (healthcare decision-making). This trend highlights both growing demand for clinician-support tools — and strong investor conviction in AI’s ability to deliver venture-scale returns.

With M&A activity surging and $1B+ acquisitions returning to the market, these companies are prime candidates for notable future exits. Based on CB Insights’ M&A probability metrics, OpenEvidence stands out as the frontrunner with a 35% likelihood of acquisition in the next 2 years, while Neko Health follows with 22% — both exceeding the market average of 20%. follows with 22% – both exceeding the market average of 20%. 

See all of digital health’s current 120+ unicorns

MORE DIGITAL HEALTH RESEARCH FROM CB INSIGHTS 

• State of Digital Health 2024 Report 
• The generative AI in healthcare and life sciences market map 
• AI in clinical trials: How the tech is serving pharma’s riskiest bet 
• The cybersecurity in healthcare market map 
• Digital Health 50: The most promising digital health startups of 2024 

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The AI boom has set the stage for a wave of tech M&A this year.

After 2 consecutive years of decline, tech M&A deals were up in 2024, with some of the largest deals centering on AI. AI companies have also bucked the general downward trend in exit valuations, instead seeing nearly double the median acquisition price from 2023 to 2024.

Using CB Insights’ predictive signals, such as Mosaic and M&A Probability, we’ve identified 7 AI-related areas where we expect to see M&A activity this year, as well as high-potential acquisition targets for each.

See highlights below, and download the full report for the rationale behind each prediction, as well as M&A target shortlists.

Tech M&A prediction highlights

• Big tech players set their sights on humanoid robotic: As physical AI takes off thanks to the rise of LLMs, humanoid robotics is becoming big tech’s next battlefield. Among high-potential acquisition targets, 1x stands out for its dual focus on industrial and consumer humanoids (just in January, it acquired Kind Humanoid to accelerate household robot development). This makes it a prime target for Meta, which recently announced plans to enter the consumer humanoid market.
• Enterprise tech heavyweights compete for AI infrastructure dominance: We’re already seeing strong signals from cash-rich companies such as Cisco and IBM, which are future-proofing their business models with AI investments. Hardware-aware AI optimization players CentML and Nota AI — which help accelerate AI model deployment while reducing compute costs — appear in our AI infrastructure acquisition target list. These companies have already shown quantifiable efficiency improvements as well as validation from Nvidia as a partner or investor.

Source: CB Insights advanced search. Data is dynamic (as of 2/27/2025).

• Data center energy demands fuel interest in cooling tech: Companies offering immersion and liquid cooling solutions enjoyed a funding rebound last year, attracting a combined $120M in fresh funding. Hypertec and Submer are high-potential acquisition targets in this space.
• Professional services firms seek AI capabilities: GenAI is coming for knowledge jobs — and leading professional services firms are buying AI capabilities to get ahead of it. One area where we see high M&A potential for professional services firms is to cater to clients’ responsible AI needs, with potential acquisition targets such as Lasso Security and HydroX AI.
• Pharma companies target AI drug discovery startups: AI drug discovery M&A is surging, with 12 deals in the sector since 2023. That M&A deal volume reflects both a maturing technology and growing urgency among pharma players to bring AI tech in-house.
• SaaS giants fortify their offerings with AI agent acquisitions: While some believe AI agents signal the death of SaaS companies, we anticipate SaaS leaders will acquire AI agent companies to avoid disruption. We’re already starting to see this happen with ServiceNow acquiring Moveworks for close to $3B in March 2025.

Source: CB Insights — ServiceNow Acquisition Insights

• Coding AI agents drive next wave of AI agent consolidation: Explosive growth, soaring valuations, a fractured AI agent landscape, and rising doubts about revenue defensibility make the coding AI agents market ripe for consolidation. While some players like Cursor look too expensive for an acquisition, we’ve identified Warp, Vidoc, and Bito as likely targets with high Mosaic scores and higher-than-average M&A Probabilities.

What is Mosaic?

Mosaic is CB Insights’ proprietary metric that measures the overall health and growth potential of private companies using non-traditional signals. Mosaic is widely used as a target company and market screener to identify high-potential emerging tech companies, typically defined as those with a score of 510 or higher.

What is M&A Probability?

M&A Probability is CB Insights’ proprietary signal that measures a private company’s chance of an M&A exit within the next 2 years. It is used to quickly screen and triangulate companies based on exit likelihood.

Combining both Mosaic Score and M&A Probability makes it easy to shortlist acquisition targets.

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Clinical development represents one of pharma’s costliest and riskiest investments.

Trials average $55M each, per a study in JAMA Health Forum, and can take more than a decade to complete. However, over 90% of drugs still fail. AI is emerging as a game-changing force in clinical development, tackling its biggest pain points head-on.

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Estimates indicate that US hospitals lose $262B annually to revenue cycle inefficiencies, while drugmakers spend more than $1B on average to develop a single drug. Meanwhile, the healthcare workforce in the US faces high burnout and a projected shortage of 124,000 physicians by 2034, according to the Association of American Medical Colleges.

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Mirroring trends in the broader venture market, AI proved to be a bright spot amid the downturn in digital health deals. In 2024, AI-focused companies secured 42% of digital health funding and accounted for 31% of deals — both record highs.

Download the full report to access comprehensive data and charts on the evolving state of digital health.

Key takeaways from the report include:

• Digital health dealmaking continues to decline. Despite a slight increase in funding YoY, digital health deal count dropped again in 2024, hitting its lowest annual total (1,225) since 2014. Regionally, Europe saw the sharpest drop in deals, with a 29% YoY decline.
• Fewer deals, bigger checks. The median digital health deal size jumped 39% YoY to hit a record high of $5.3M in 2024. The combination of declining deal volume and larger deal sizes suggests that selective investors are concentrating their resources on companies that meet heightened benchmarks in areas like clinical validation, commercial traction, and regulatory readiness.
• AI takes center stage in digital health. In 2024, AI-focused companies captured 42% of digital health funding and 31% of deals — both record highs. The 5 largest AI-focused digital health deals were spread across diagnostics, drug development, and women’s health.
• Digital health mega-rounds rebound in 2024. Mega-rounds ($100M+ deals) increased in 2024 after 2 years of decline, with the top 3 deals focused on drug discovery and development. Most top deals (7 out of 10) went to US-based companies, pointing to the region’s position as a hub for high-value digital health investment.

We dive into the trends below.

Digital health dealmaking continues to decline

Following 2 years of decline, digital health funding increased slightly in 2024, rising by 3% YoY.

However, digital health deal count fell for the third year straight in 2024. It dropped by 23% YoY to reach just 1,225 — its lowest level since 2014 — highlighting that investors remain cautious.

Regionally, Europe saw the steepest drop, with deal count shrinking 29% YoY to 258, despite a modest funding increase to $2.8B. Asia also experienced a decline, with deal count falling 19% YoY to 218, alongside a funding drop to $0.8B. While still the most active market, the US recorded a 19% YoY decline in deal count to 683, even as funding climbed to $11.7B.

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Fewer deals, bigger checks

While the overall deal count fell, the median digital health deal size surged in 2024.

It climbed by 39% YoY to reach $5.3M — a record high.

This combination of factors suggests that selective investors are prioritizing companies that meet heightened benchmarks in areas like clinical validation, commercial traction, and regulatory readiness.

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AI takes center stage in digital health

AI is commanding a growing share of digital health investment activity.

AI-focused companies captured 42% of total digital health funding and 31% of deal volume in 2024 — both record highs. 

This surge reflects heightened investor confidence in AI’s ability to accelerate drug discovery, improve early disease detection, deliver personalized care, and more.

The top 2 AI-focused digital health deals in 2024 went to drug development platform Xaira Therapeutics. Freenome followed with a $254M Series F to expand its AI-driven early cancer detection tools, while Flo Health secured a $200M Series C to scale its personalized women’s health platform. BioAge Labs rounded out the top 5 with a $170M Series D to advance its AI-powered aging-related treatments.

Explore the top AI-focused digital health deals

As AI adoption grows across healthcare operations — from clinical and administrative workflows to drug development — healthcare providers and pharmaceutical giants will likely pursue strategic partnerships and acquisitions to maintain their competitive edge.

Digital health mega-rounds rebound in 2024

Digital health mega-round activity rebounded in 2024 after 2 consecutive years of decline, with deal count rising by 50% YoY to 33.

The top 3 mega-rounds of 2024 all went to drug discovery and development companies. 

Xaira Therapeutics led the pack with two $500M rounds for its AI-driven drug discovery and development platform, followed by Formation Bio with a $372M Series D to advance its drug development efforts. 

At the regional level, the US accounted for 7 of the top 10 mega-rounds in 2024, reflecting its position as a hub for high-value digital health investments. 

MORE DIGITAL HEALTH RESEARCH FROM CB INSIGHTS

• State of Digital Health Q3’24 Report
• AI’s moment in preclinical drug development arrives: Why formulation tech is the next frontier
• Inside the AI drug discovery arms race: Record M&A activity, a biologics funding spree, and more
• Digital Health 50: The most promising digital health startups of 2024
• The $4.6B opportunity in healthcare: Ambient AI to target clinician burnout

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For pharma companies, it’s critical to maximize efficiency in preclinical development — the stage after drug discovery and before clinical trials — as poor processes can mask early warning signs of drug candidates that are likely to fail.

The stakes are high: Studies show that 90% of drugs fail in clinical trials. In Phase 1 trials alone — which have a median cost of $3.4M per trial — 40% of drug candidates fail.

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Bringing a drug to market traditionally involves staggering costs — averaging $1.3B when accounting for all failed compounds — and costs continue to rise as productivity in the drug R&D process declines. 

AI has the potential to break this pattern by dramatically accelerating drug discovery and reducing costs.

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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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Our 2025 Tech Trends report provides a concrete roadmap for corporate leaders to navigate some of the most important technology shifts in the year ahead.

We include specific recommendations for action so that business leaders can get ahead of the next wave of value creation.

Here is a selection of key findings from the report:

• AI agents are given money to spend: AI agents’ utility is limited until they can make transactions seamlessly. A small group of tech players is building new infrastructure to make that happen.
• The future data center arrives: With data center power usage expected to more than double by 2026, big tech companies are morphing into energy innovators to support AI workloads. There’s a huge opportunity in improving data centers’ energy efficiency.
• Investment floodgates open for RNA therapeutics: RNA therapeutics developers are pioneering new ways to treat traditionally “undruggable” diseases, with a growing focus on neurodegenerative disorders like Alzheimer’s and Huntington’s diseases.
• AI M&A fuels the next wave of corporate strategy: AI’s share of corporate tech M&A has doubled since 2020. Tech incumbents like Nvidia, Salesforce, and Snowflake, as well as consultancies like Accenture, are rapidly acquiring AI startups to tap into enterprise demand. 
• Disease management enters a new phase with AI: AI is improving care delivery across 3 key areas of disease management: precise symptom evaluation; testing/screening for earlier disease detection (including before symptoms even appear); and finding at-risk individuals in datasets of entire patient populations. 
• Retail’s personalization imperative: Generative AI is unlocking 1:1 experiences across commerce touchpoints, with leaders like Target seeing a corresponding 3x boost in conversation rates. Personalization will become omnipresent in retailers’ offerings.
• And much more

Methodology

Our analysis relies on a wide range of CB Insights datasets, including financing and acquisition data, valuations, founding team and key people data, earnings transcripts, and more. We also leverage CB Insights’ proprietary scoring algorithms to measure business health (Mosaic) and maturity (Commercial Maturity), as well as the likelihood of acquisition (M&A Probability score). Throughout the report, we provide CB Insights customers with jumping-off points to dig deeper into the data behind the report.

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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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To do this, new tech-enabled solutions are targeting key bottlenecks throughout the clinical trial lifecycle for all participating stakeholders, from researchers to life science companies to patients.  

To help strategy teams prioritize clinical trials markets in their planning decisions, we plotted markets using CB Insights’ TECH framework, which scores markets across 2 dimensions:

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What you need to know: 

• Animal health is seeing rising demand and early-stage startups are building novel products targeting the space, including AI-based solutions.
• Focus areas for emerging trends include: Diagnostic platforms for vets, advanced therapies, methane-reducing solutions, AI-driven diagnostics & monitoring, and disease prevention & treatment.

Animal health — which includes companion and livestock animals — is steadily growing as a topic of interest among executives.

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Essential resources to understand the future of healthcare:

• • The generative AI in healthcare market map — These tech companies are bringing generative AI into medical research and clinical settings.
  • Pharma AI Readiness Index: Who’s best-positioned for the AI boom? — Assess how prepared top pharmaceutical companies are to adopt and respond to rapidly evolving AI technologies.
  • 6 digital health markets gaining momentum in 2024 — We analyzed early-stage investment trends to uncover which digital health markets — from telepsychiatry to virtual & hybrid women’s healthcare — are quickly evolving and how.
• 
  • The Digital Health 50 — Here are the world’s most promising digital health startups.
  • Big Tech in Healthcare — How Amazon, Google, Microsoft, & Nvidia are looking to transform drug R&D, primary care, and more.
  • State of Digital Health Q2’24 Report — Funding in digital health drops, but larger check sizes and an uptick in exits highlight bright spots for the industry in Q2’24.
• 
  • Longevity tech market map — 64 promising startups across 12 categories aiming to expand lifespans, from human cryopreservation to cellular reprogramming.
  • Digital Health AI M&A — Every second acquisition in 2024 has been an AI company; here’s where we’re seeing the most activity.
  • 20 tech trends to watch closely in 2024 — The technology trends that will transform industries as generative AI takes center stage, including several directly impacting healthcare.

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In 2024 so far, a16z has backed more than 20 AI startups working within disruptive categories. For example, this year, it has invested in several AI-driven copilots and agents designed to automate key workflows in big industries like healthcare and finance. It has also turned its attention to multimedia generation startups expediting the creation of a wide variety of content, from images to videos to audio.

While championing AI’s advancement, the firm also acknowledges associated risks — its founders are proponents of open-source models, arguing that their transparency and accessibility will help ensure that AI is developed in a secure and ethical way. So far this year, the two largest a16z-backed AI deals have gone to open-source large language model (LLM) developers xAI and Mistral AI.

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As a result, a range of technologies have emerged to address issues across the entire trial lifecycle. These use AI, data analytics, and digital platforms to streamline processes, improve data quality, and boost patient engagement — all with the aim of driving down trial times and costs while increasing success rates.

This market map identifies 96 vendors in 14 categories reshaping clinical trials. This tech ecosystem offers sponsors and research organizations opportunities to conduct more efficient, patient-centric trials that also meet regulatory requirements.

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This acquisition follows Commure’s Oct 2023 acquisition of another AI-driven provider workflow solution Athelas — which offers revenue cycle management (RCM) and automated documentation services — further bolstering its AI arsenal.

These deals reflect a key trend in healthcare M&A: AI is all the rage. 

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The impact on the pharma industry has been substantial, with Ozempic’s producer, Novo Nordisk, seeing a 36% rise in sales in 2023 driven by the accelerated adoption of its GLP-1 products. D2C pharmacies like Hims are also entering the space, offering their own GLP-1 drugs at a fraction of the cost to patients. 

The rapid growth in prescriptions for these appetite-curbing drugs has drawn wide-spread attention from corporates across industries.  

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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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These leaders are harnessing their existing offerings — in areas like cloud computing, AI, and hardware — to service healthcare providers and pharmaceutical companies.

While big tech players are competing with each other in this landscape, they are also carving out distinct strategies: 

• Amazon is going deeper into primary and specialized care.
• Google is amassing troves of health data, which could play a role in its biotech bets. 
• Microsoft is equipping healthcare organizations with AI tools to improve clinical research, drug R&D, and care delivery.
• Nvidia’s long-standing hardware dominance positions it to play a major role in the future of smart hospitals. 

This report uses CB Insights datasets like investments, acquisitions, business relationships, patents, buyer interviews, company scouting reports, and more. Learn more about our data here.

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The industry is built around encoding information in quantum entities called “qubits” — which have a probability of being either 1 or 0, as opposed to traditional bits that can only be one or the other — to open up new computational approaches and ways of handling data that are not possible on conventional devices.

For example, quantum computing could allow entirely new algorithms that are much more efficient at some key tasks — like complex optimization problems, sorting through large datasets, and running simulations. Though the tech is not yet mature, companies are already working to apply quantum computing to commercial applications like drug discovery, finance, materials discovery, and logistics. Investors are excited — startups in the space saw equity funding surge to $1.3B in 2023, a rare bright spot for venture last year. As quantum computers become more capable in the coming years, expect commercial interest to rise quickly.

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Salesforce CEO Marc Benioff called AI “the single most important moment in the history of the technology industry” in the company’s most recent earnings call. JPMorgan CEO Jamie Dimon said, in his April 2024 letter, “we are completely convinced the consequences [of AI] will be extraordinary.” 

Others are hyper-focused on AI’s potential to drive new efficiencies and product development. Big pharma companies are pushing ahead with AI-powered drug discovery collaborations, with the goal of accelerating drug development timelines. Payments giants, meanwhile, are leveraging AI to fight back against a wave of fraud.  

Much of the hype around recent advances has yet to translate to revenue. No AI-discovered drug has been approved yet for sale (though Insilico Medicine brought the first drug fully generated by AI into human trials in 2023), and Salesforce acknowledged its latest AI push would not have a material impact on its revenue this year. 

But the promise of future opportunities — and the perceived risk of inaction — is driving leaders to make moves now that could eventually reshape some of the world’s biggest industries. Our 70-slide report surveys the AI strategies of the following companies:

• Financial services & insurance: JPMorgan, Visa, Mastercard, UnitedHealth Group
• Enterprise tech: Oracle, Salesforce
• Pharma: Eli Lilly, Novo Nordisk, Johnson & Johnson
• Industrials: Toyota, Siemens

Using the CB Insights technology intelligence platform, we analyzed signals like investment & partnership activity, executive chatter in earnings transcripts, patents, and more to understand their efforts. Download the full report to see them all. 

Largest companies based on market cap (as of 4/15/2024). Our analysis excludes big tech, semiconductor developers, and state-owned companies.

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