Industry AI Adoption Leaderboard
Top AI-ready Manufacturing companies — 4,515 ranked
Ranked leaderboard of 4,515 Manufacturing companies by Meo AI adoption score.
4515
Companies Scored
58
Avg Adoption Score
Advanced
Top Stage
Which 4,515 ranked companies lead in AI adoption?
- What is the average AI adoption score in the 4,515 ranked industry?
- Who are the top 10 AI adopters in 4,515 ranked?
| # | Company | Stage | Key Opportunity | Location |
|---|---|---|---|---|
| 1 | Red Nucleus | Advanced | Automated Clinical Trial Document Generation and Review | Yardley, Pennsylvania |
| 2 | Cellares | Advanced | Automated Clinical Trial Document Review and Data Extraction | South San Francisco, California |
| 3 | merck | Advanced | Accelerating drug discovery and development by using generative AI to design novel molecules and predict clinical trial outcomes. | rahway, New Jersey |
| 4 | the janssen pharmaceutical companies of johnson & johnson | Advanced | AI can dramatically accelerate drug discovery and clinical trial design by predicting molecular interactions and optimizing patient recruitment, reducing time-to-market for new therapies. | raritan, New Jersey |
| 5 | astra zeneca lp us | Advanced | AI can dramatically accelerate drug discovery and clinical trial design by predicting molecular interactions and optimizing patient recruitment, reducing time-to-market for new therapies. | wilmington, Delaware |
| 6 | pfizerpro | Advanced | AI can accelerate drug discovery and clinical trial optimization, reducing development timelines from years to months and saving billions in R&D costs. | new york, New York |
| 7 | starkindustries2, ltds. | Advanced | AI-driven molecular simulation and materials discovery can drastically accelerate R&D cycles and reduce costs for new nanotechnology products. | watertown, New York |
| 8 | pfizer | Advanced | AI can dramatically accelerate drug discovery by predicting molecular interactions and optimizing clinical trial design, potentially cutting years and billions from R&D timelines. | new york, New York |
| 9 | vertex pharmaceuticals | Advanced | AI can dramatically accelerate target identification and compound optimization for novel genetic disease therapies, compressing years of research into months. | boston, Massachusetts |
| 10 | monsanto company | Advanced | AI-driven predictive modeling can optimize the genetic selection and field trial process for new seed and trait development, dramatically accelerating R&D cycles and improving yield predictability under varying climate conditions. | st. louis, Missouri |
| 11 | msd | Advanced | AI can dramatically accelerate drug discovery and clinical trial design by predicting molecular interactions and optimizing patient recruitment, potentially saving billions in R&D costs and years in development timelines. | rahway, New Jersey |
| 12 | eli lilly and company | Advanced | AI can accelerate drug discovery by predicting molecular interactions and optimizing clinical trial design, dramatically reducing time-to-market for new therapies. | indianapolis, Indiana |
| 13 | Vanigent | Advanced | Automated Clinical Trial Patient Recruitment & Screening | Atlanta, Georgia |
| 14 | The Cary Company | Advanced | Automated Inventory Management and Replenishment Forecasting | Addison, Illinois |
| 15 | Amplity | Advanced | Automated Medical Information Request Handling | Langhorne, Pennsylvania |
| 16 | Lantheus | Advanced | Automated Clinical Trial Patient Recruitment and Screening | Bedford, Massachusetts |
| 17 | amgen | Advanced | AI can dramatically accelerate drug discovery and clinical trial design by predicting protein structures, identifying novel therapeutic targets, and optimizing patient recruitment, potentially cutting years and billions from R&D timelines. | thousand oaks, California |
| 18 | Walsworth | Advanced | Brookfield, Missouri | |
| 19 | Myers Industries | Advanced | Akron, Ohio | |
| 20 | MFA Oil | Advanced | Columbia, Missouri | |
| 21 | IWCO | Advanced | Chanhassen, Minnesota | |
| 22 | Resource Label Group | Advanced | Franklin, Tennessee | |
| 23 | bristol myers squibb | Advanced | AI can accelerate drug discovery and clinical trials by predicting molecular interactions, optimizing trial design, and identifying patient cohorts, dramatically reducing the time and cost of bringing new therapies to market. | lawrence township, New Jersey |
| 24 | procter & gamble | Advanced | AI-driven demand sensing and dynamic supply chain optimization can significantly reduce stockouts and inventory costs across its global portfolio of fast-moving consumer goods. | cincinnati, Ohio |
| 25 | Alleguard | Advanced | brentwood, Tennessee | |
| 26 | Takeda Oncology | Advanced | Cambridge, Massachusetts | |
| 27 | avantor | Advanced | AI-driven supply chain optimization and predictive quality control for high-purity materials can reduce waste and improve on-time delivery. | radnor, Pennsylvania |
| 28 | RelaDyne | Advanced | Cincinnati, Ohio | |
| 29 | NYSCC | Advanced | New York, New York | |
| 30 | iff | Advanced | Accelerate novel flavor and fragrance molecule discovery with generative AI, cutting R&D cycle time by 30–50% while optimizing for cost, sustainability, and regulatory compliance. | new york, New York |
| 31 | Fagron US | Advanced | Automated Prior Authorization Processing | Austin, Texas |
| 32 | PBF Energy | Advanced | Parsippany-Troy Hills, New Jersey | |
| 33 | itw | Advanced | Deploy AI-driven predictive maintenance across global manufacturing lines to reduce unplanned downtime and optimize equipment effectiveness. | , |
| 34 | ProVia | Advanced | Sugarcreek, Ohio | |
| 35 | abbvie | Advanced | AI-driven target discovery and clinical trial optimization can dramatically accelerate drug development pipelines and reduce multi-billion-dollar R&D costs. | north chicago, Illinois |
| 36 | Federal | Moderate | Springfield, Illinois | |
| 37 | Sinclair Oil | Moderate | , null | |
| 38 | BEHR | Moderate | Santa Ana, California | |
| 39 | Valvoline™ Global | Moderate | lexington, Kentucky | |
| 40 | Libertycoke | Moderate | Philadelphia, Pennsylvania | |
| 41 | North Sails | Moderate | Newport, Rhode Island | |
| 42 | Mannington | Moderate | Salem, New Jersey | |
| 43 | regeneron | Moderate | AI can accelerate Regeneron's core R&D by predicting drug-target interactions and patient response biomarkers, drastically reducing the time and cost of bringing new biologics to market. | tarrytown, New York |
| 44 | Prognos Health | Moderate | Automated Clinical Trial Patient Matching and Outreach | New York, New York |
| 45 | medivation | Moderate | Leveraging generative AI to accelerate clinical trial patient recruitment and optimize oncology drug trial protocols, reducing time-to-market by up to 30%. | new york, New York |
| 46 | dupont | Moderate | AI can accelerate the discovery and formulation of new sustainable materials by predicting molecular properties and optimizing synthesis pathways, drastically reducing R&D timelines. | wilmington, Delaware |
| 47 | sanofi genzyme | Moderate | AI can accelerate drug discovery for rare diseases by predicting molecular interactions and optimizing clinical trial design, drastically reducing development timelines and costs. | cambridge, Massachusetts |
| 48 | daiichi sankyo us | Moderate | AI can accelerate oncology drug discovery by predicting compound efficacy and optimizing clinical trial designs, reducing time-to-market for life-saving therapies. | basking ridge, New Jersey |
| 49 | gilead sciences | Moderate | AI can dramatically accelerate drug discovery and clinical trial design by predicting molecular interactions and identifying optimal patient cohorts. | foster city, California |
| 50 | bristol-myers squibb | Moderate | Leveraging generative AI to accelerate clinical trial document generation and regulatory submission drafting, reducing cycle times by 30-40% for a mid-market pharma firm. | seattle, Washington |
| 51 | egpi | Moderate | Leveraging AI for accelerated drug discovery and predictive analytics in clinical trials to reduce time-to-market and R&D costs. | torrance, California |
| 52 | thermo fisher scientific | Moderate | AI can accelerate drug discovery and diagnostics by analyzing vast genomic and proteomic datasets to identify novel biomarkers and therapeutic targets, dramatically reducing R&D timelines. | waltham, Massachusetts |
| 53 | johnson & johnson | Moderate | AI can accelerate drug discovery and clinical trials by predicting molecular interactions and optimizing patient recruitment, dramatically reducing time-to-market and R&D costs. | new brunswick, New Jersey |
| 54 | Atmus | Moderate | nashville, Tennessee | |
| 55 | Voyant Beauty | Moderate | Lyons Township, Illinois | |
| 56 | Lannett | Moderate | Philadelphia, Pennsylvania | |
| 57 | PAHC | Moderate | Teaneck Township, New Jersey | |
| 58 | dow | Moderate | AI-driven predictive maintenance and process optimization in large-scale chemical plants can significantly reduce unplanned downtime, improve yield, and enhance safety. | midland, Michigan |
| 59 | medformers | Moderate | Leverage AI for accelerated drug discovery and clinical trial optimization to reduce time-to-market and R&D costs. | new york, New York |
| 60 | Drug Plastics & Glass Co., Inc. | Moderate | boyertown, Pennsylvania | |
| 61 | schering-plough research institute | Moderate | AI can accelerate drug discovery by predicting molecular interactions and optimizing clinical trial design, dramatically reducing time-to-market for new therapeutics. | kenilworth, New Jersey |
| 62 | TP Orthodontics | Moderate | La Porte, Indiana | |
| 63 | celgene | Moderate | AI-driven drug discovery and clinical trial optimization can significantly accelerate time-to-market for novel therapies while reducing R&D costs. | summit, New Jersey |
| 64 | YAK MAT | Moderate | Columbia, Mississippi | |
| 65 | Alaffia | Moderate | Olympia, Washington | |
| 66 | milliporesigma | Moderate | AI can accelerate drug discovery and bioprocess optimization by predicting experimental outcomes, analyzing complex multi-omics data, and automating the design of novel reagents and assays. | burlington, Massachusetts |
| 67 | p&g pharmaceuticals | Moderate | AI-driven target discovery and clinical trial optimization can dramatically accelerate drug development cycles and reduce multi-billion-dollar R&D costs. | , |
| 68 | Sprague | Moderate | Portsmouth, New Hampshire | |
| 69 | iveric bio, an astellas company | Moderate | Leverage AI-powered analysis of retinal imaging and real-world data to accelerate clinical development and personalize treatment for geographic atrophy. | parsippany, New Jersey |
| 70 | radim spa | Moderate | Leverage AI for accelerated drug discovery and predictive quality control to reduce time-to-market and improve manufacturing efficiency. | , |
| 71 | Vireo | Moderate | minneapolis, Minnesota | |
| 72 | Rhino Linings | Moderate | San Diego, California | |
| 73 | biogen | Moderate | AI can accelerate drug discovery and clinical trial design for complex neurological diseases by predicting drug-target interactions and identifying optimal patient cohorts. | cambridge, Massachusetts |
| 74 | incyte | Moderate | AI can accelerate oncology drug discovery by predicting compound efficacy and patient response biomarkers, dramatically reducing R&D timelines and costs. | wilmington, Delaware |
| 75 | TemperPack | Moderate | Richmond, Virginia | |
| 76 | patheon | Moderate | AI can optimize end-to-end drug development and manufacturing processes, from predictive formulation design to real-time quality control, significantly reducing time-to-market and production costs for client therapies. | waltham, Massachusetts |
| 77 | ironshore | Moderate | Leveraging AI for accelerated drug discovery and clinical trial optimization to reduce time-to-market and R&D costs. | , |
| 78 | kelly engineering service at dow chemical | Moderate | AI-driven predictive maintenance and process optimization can significantly reduce unplanned downtime, improve yield, and enhance safety across large-scale chemical manufacturing complexes. | houston, Texas |
| 79 | mylan | Moderate | AI can optimize complex global supply chains and production schedules to reduce costs and prevent drug shortages. | canonsburg, Pennsylvania |
| 80 | alnylam pharmaceuticals | Moderate | AI can accelerate target identification and validation for RNAi therapeutics by analyzing multi-omics data to predict gene-disease associations and optimize siRNA design. | cambridge, Massachusetts |
| 81 | Fralock | Moderate | Santa Clarita, California | |
| 82 | ecolab | Moderate | AI-powered predictive maintenance and chemical dosing for water treatment and cleaning systems, optimizing resource use and preventing equipment failures. | st. paul, Minnesota |
| 83 | catalent | Moderate | AI can optimize complex biologics manufacturing processes, predict batch failures, and accelerate formulation development, directly improving yield, quality, and time-to-market. | tampa, Florida |
| 84 | LIFOAM | Moderate | Greer, South Carolina | |
| 85 | imclone systems, a wholly-owned subsidiary of eli lilly and company | Moderate | AI can accelerate oncology drug discovery and clinical trial design by predicting drug-target interactions and optimizing patient stratification for therapies like Erbitux. | , |
| 86 | Berkshire Corporation | Moderate | Great Barrington, Massachusetts | |
| 87 | supernus pharmaceuticals, inc. | Moderate | Leveraging AI for drug discovery and clinical trial optimization to accelerate CNS pipeline development and reduce R&D costs. | rockville, Maryland |
| 88 | p&g chemicals | Moderate | AI-driven predictive modeling can optimize complex chemical synthesis processes, reducing energy consumption, minimizing waste, and accelerating R&D for new sustainable formulations. | cincinnati, Ohio |
| 89 | millennium pharmaceuticals, inc. | Moderate | AI-driven target discovery and patient stratification can dramatically accelerate the development of novel oncology therapies and improve clinical trial success rates. | cambridge, Massachusetts |
| 90 | Porex | Moderate | Fairburn, Georgia | |
| 91 | sanofi-aventis u.s. llc | Moderate | AI can dramatically accelerate drug discovery and clinical trial design by predicting molecular interactions and optimizing patient recruitment, potentially cutting years and billions from R&D timelines. | bridgewater, New Jersey |
| 92 | viatris | Moderate | AI can optimize the end-to-end pharmaceutical supply chain, from predictive demand forecasting to dynamic inventory management, reducing costs and preventing drug shortages. | pittsburgh, Pennsylvania |
| 93 | Polytex | Moderate | Ponte Vedra, Florida | |
| 94 | HellermannTyton | Moderate | Tlaquepaque, Jalisco | |
| 95 | ColorMasters | Moderate | Albertville, Alabama | |
| 96 | Nutraceutical | Moderate | Park City, Utah | |
| 97 | ENTEK | Moderate | Lebanon, Oregon | |
| 98 | Bgintr | Moderate | union, New Jersey | |
| 99 | Sierra Nevada Corporation | Moderate | Sparks, Nevada | |
| 100 | Kimia Farma Apotek | Moderate | Jakarta Special Capital Region, New York |
See where your company ranks.
Get a private AI adoption assessment with actionable recommendations and deployment timeline.