AI in Drug Manufacturing Market Size is valued at US$ 0.6 Bn in 2024 and is predicted to reach US$ 5.0 Bn by the year 2034 at an 23.4% CAGR during the forecast period for 2025-2034.
AI in drug manufacturing refers to the utilisation of artificial intelligence technologies, such as machine learning and predictive analytics, to optimise drug formulation, streamline production processes, enhance quality control, and accelerate pharmaceutical development efficiently. The AI in drug manufacturing market is experiencing rapid expansion as pharmaceutical companies increasingly integrate artificial intelligence to optimize production efficiency and quality control.
AI technologies, including machine learning, predictive analytics, and digital twins, are revolutionising process automation, real-time monitoring, and fault detection. A major driver is the increasing adoption of AI to meet the rising demand for drugs, allowing for faster scale-up, reduced downtime, and enhanced consistency in complex manufacturing environments. Moreover, AI supports predictive maintenance and data-driven decision-making, lowering operational costs while maintaining regulatory compliance. This digital transformation is crucial for meeting the global demands of healthcare and personalised medicine.
The AI in drug manufacturing market is experiencing significant growth as pharmaceutical companies increasingly adopt artificial intelligence to enhance production efficiency, quality control, and predictive maintenance. AI-driven analytics aid in optimising formulation design, real-time monitoring, and minimising human error during complex drug production processes.
The market is further propelled by the presence of advanced pharmaceutical manufacturing infrastructure, which enables seamless integration of AI tools into automated systems. These facilities enable high data availability, robust digital frameworks, and compliance with stringent regulatory standards, thereby accelerating AI adoption and fostering innovation in smart manufacturing and process optimisation across the pharmaceutical industry.
Some of the Key Players in the AI in Drug Manufacturing Market:
· C3.AI
· AMD
· IBM
· Kalypso
· SAS Institute
· Körber Pharma
· SDG Group
· Catalyx
· Elisa Industriq
· Straive
· Axiomtek
· Appinventiv
· Amplelogic
· Precognize
The AI in drug manufacturing market is segmented by type of offering, by mode of deployment, by type of AI solution, by type of technology, by application area, by utility in drug manufacturing and by region. By type of offering, the market is segmented into hardware, software, and services. By mode of deployment, the market is segmented into cloud, and on-premise.
By type of AI solution, the market is segmented into standard/off-the-shelf AI solutions, and personalized AI solutions. By type of technology, the market is segmented into computer vision, deep learning, generative AI, machine learning, and other technologies. By application area, the market is segmented into process development & optimization, plant/equipment performance monitoring, predictive maintenance, quality control, supply chain optimization, and other application areas. By utility in drug manufacturing, the market is segmented into defect detection, packaging & label inspection, package counting, fill level inspection, and other utilities.
In 2024, the software is expected to hold a significant market share as pharmaceutical companies utilise intelligent software to enhance production efficiency, quality, and compliance. AI-powered software offers predictive maintenance, process optimisation, and real-time monitoring, thereby reducing downtime and human error. The primary driver is the growing demand for automation and data-driven decision-making to expedite drug development while supporting regulatory compliance. Furthermore, the incorporation of machine learning algorithms broadens yield forecasting and resource management, changing traditional production into intelligent, adaptable systems.
The AI in drug manufacturing market is dominated by cloud-based solutions, driven by the increasing adoption of cloud-based AI, which enhances operational efficiency and scalability. Cloud platforms enable real-time data sharing, predictive analytics, and process optimisation across multiple manufacturing sites. This facilitates faster decision-making, improved quality control, and decreased production expenses. Moreover, cloud-based AI supports advanced drug formulation, automated quality checks, and continuous monitoring, enabling pharmaceutical firms to accelerate innovation and comply with stringent regulatory standards efficiently.
North America dominates the market for AI in drug manufacturing due to region’s strong pharmaceutical infrastructure and rising adoption of automation to improve production efficiency. AI technologies enable predictive maintenance, process optimisation, and real-time quality inspection, thereby reducing operational costs and errors.
Increasing regulatory support for digitalisation and the presence of leading pharmaceutical and AI companies further stimulate innovation. The increasing demand for customised drugs and the acceleration of drug development timelines also drive market growth in the region.
Moreover, Europe's AI in drug manufacturing market is also fueled due to the region’s strong focus on digital transformation and advanced automation in the pharmaceutical industry. AI enhances productivity by streamlining production processes, improving quality control, and anticipating equipment maintenance requirements. Pharmaceutical firms in Europe are embracing AI for real-time tracking, minimising manufacturing errors, and ensuring regulatory compliance. Also driving the market expansion across the region are increased demand for targeted medicine and government incentives for AI-based innovation.
|
Report Attribute |
Specifications |
|
Market Size Value In 2024 |
USD 0.6 Bn |
|
Revenue Forecast In 2034 |
USD 5.0 Bn |
|
Growth Rate CAGR |
CAGR of 23.4% from 2025 to 2034 |
|
Quantitative Units |
Representation of revenue in US$ Bn and CAGR from 2025 to 2034 |
|
Historic Year |
2021 to 2024 |
|
Forecast Year |
2025-2034 |
|
Report Coverage |
The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
|
Segments Covered |
By Type of Offering, By Mode of Deployment, By Type of AI Solution, By Type of Technology, By Application Area, By Utility in Drug Manufacturing |
|
Regional Scope |
North America, Europe, Asia Pacific, Latin America, Middle East & Africa |
|
Country Scope |
U.S., Canada, Germany, The UK, France, Italy, Spain, Rest of Europe, China, Japan, India, South Korea, Southeast Asia, Rest of Asia Pacific, Brazil, Argentina, Mexico, Rest of Latin America, GCC Countries, South Africa, Rest of the Middle East and Africa |
|
Competitive Landscape |
C3.AI, AMD, IBM, Kalypso, SAS Institute, Körber Pharma, SDG Group, Catalyx, Elisa Industriq, Straive, Axiomtek, Appinventiv, Amplelogic and Precognize. |
|
Customization Scope |
Free customization report with the procurement of the report, Modifications to the regional and segment scope. Geographic competitive landscape. |
|
Pricing and Available Payment Methods |
Explore pricing alternatives that are customized to your particular study requirements. |
Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions
Chapter 2. Executive Summary
Chapter 3. Global AI in Drug Manufacturing Market Snapshot
Chapter 4. Global AI in Drug Manufacturing Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis
4.6. Porter's Five Forces Analysis
4.7. Incremental Opportunity Analysis (US$ MN), 2025-2034
4.8. Competitive Landscape & Market Share Analysis, By Key Player (2024)
4.9. Use/impact of AI on AI in Drug Manufacturing Market Industry Trends
4.10. Global AI in Drug Manufacturing Market Penetration & Growth Prospect Mapping (US$ Mn), 2024-2034
Chapter 5. AI in Drug Manufacturing Market Segmentation 1: By AI solution, Estimates & Trend Analysis
5.1. Market Share by AI solution, 2024 & 2034
5.2. Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following AI solution:
5.2.1. Standard / Off-the-shelf AI solutions
5.2.2. Personalized AI solutions
Chapter 6. AI in Drug Manufacturing Market Segmentation 2: By Utility in Drug Manufacturing, Estimates & Trend Analysis
6.1. Market Share by Utility in Drug Manufacturing, 2024 & 2034
6.2. Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Utility in Drug Manufacturing:
6.2.1. Defect Detection
6.2.2. Packaging and Label Inspection
6.2.3. Package Counting
6.2.4. Fill Level Inspection
6.2.5. Other Utilities
Chapter 7. AI in Drug Manufacturing Market Segmentation 3: By Application Area, Estimates & Trend Analysis
7.1. Market Share by Application Area, 2024 & 2034
7.2. Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Application Area:
7.2.1. Process Development and Optimization
7.2.2. Plant / Equipment Performance Monitoring
7.2.3. Predictive Maintenance
7.2.4. Quality Control
7.2.5. Supply Chain Optimization
7.2.6. Other Application Areas
Chapter 8. AI in Drug Manufacturing Market Segmentation 4: By Offering, Estimates & Trend Analysis
8.1. Market Share by Offering, 2024 & 2034
8.2. Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Offering:
8.2.1. Hardware
8.2.2. Software
8.2.3. Services
Chapter 9. AI in Drug Manufacturing Market Segmentation 5: By Deployment Mode, Estimates & Trend Analysis
9.1. Market Share by Deployment Mode, 2024 & 2034
9.2. Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Deployment Mode:
9.2.1. Cloud
9.2.2. On-Premise
Chapter 10. AI in Drug Manufacturing Market Segmentation 6: By Technology, Estimates & Trend Analysis
10.1. Market Share by Technology, 2024 & 2034
10.2. Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Technology:
10.2.1. Computer Vision
10.2.2. Deep Learning
10.2.3. Generative AI
10.2.4. Machine Learning
10.2.5. Other Technologies
Chapter 11. AI in Drug Manufacturing Market Segmentation 7: Regional Estimates & Trend Analysis
11.1. Global AI in Drug Manufacturing Market, Regional Snapshot 2024 & 2034
11.2. North America
11.2.1. North America AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Country, 2021-2034
11.2.1.1. US
11.2.1.2. Canada
11.2.2. North America AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by AI solution, 2021-2034
11.2.3. North America AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Utility in Drug Manufacturing, 2021-2034
11.2.4. North America AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Application Area, 2021-2034
11.2.5. North America AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Offering, 2021-2034
11.2.6. North America AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Deployment Mode, 2021-2034
11.2.7. North America AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2021-2034
11.3. Europe
11.3.1. Europe AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Country, 2021-2034
11.3.1.1. Germany
11.3.1.2. U.K.
11.3.1.3. France
11.3.1.4. Italy
11.3.1.5. Spain
11.3.1.6. Rest of Europe
11.3.2. Europe AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by AI solution, 2021-2034
11.3.3. Europe AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Utility in Drug Manufacturing, 2021-2034
11.3.4. Europe AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Application Area, 2021-2034
11.3.5. Europe AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Offering, 2021-2034
11.3.6. Europe AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Deployment Mode, 2021-2034
11.3.7. Europe AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2021-2034
11.4. Asia Pacific
11.4.1. Asia Pacific AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Country, 2021-2034
11.4.1.1. India
11.4.1.2. China
11.4.1.3. Japan
11.4.1.4. Australia
11.4.1.5. South Korea
11.4.1.6. Hong Kong
11.4.1.7. Southeast Asia
11.4.1.8. Rest of Asia Pacific
11.4.2. Asia Pacific AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by AI solution, 2021-2034
11.4.3. Asia Pacific AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Utility in Drug Manufacturing, 2021-2034
11.4.4. Asia Pacific AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Application Area, 2021-2034
11.4.5. Asia Pacific AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Offering, 2021-2034
11.4.6. Asia Pacific AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Deployment Mode, 2021-2034
11.4.7. Asia Pacific AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2021-2034
11.5. Latin America
11.5.1. Latin America AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Country, 2021-2034
11.5.1.1. Brazil
11.5.1.2. Mexico
11.5.1.3. Rest of Latin America
11.5.2. Latin America AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by AI solution, 2021-2034
11.5.3. Latin America AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Utility in Drug Manufacturing, 2021-2034
11.5.4. Latin America AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Application Area, 2021-2034
11.5.5. Latin America AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Offering, 2021-2034
11.5.6. Latin America AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Deployment Mode, 2021-2034
11.5.7. Latin America AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2021-2034
11.6. Middle East & Africa
11.6.1. Middle East & Africa Wind Turbine Rotor Blade Market Revenue (US$ Million) Estimates and Forecasts by country, 2021-2034
11.6.1.1. GCC Countries
11.6.1.2. Israel
11.6.1.3. South Africa
11.6.1.4. Rest of Middle East and Africa
11.6.2. Middle East & Africa AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by AI solution, 2021-2034
11.6.3. Middle East & Africa AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Utility in Drug Manufacturing, 2021-2034
11.6.4. Middle East & Africa AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Application Area, 2021-2034
11.6.5. Middle East & Africa AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Offering, 2021-2034
11.6.6. Middle East & Africa AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Deployment Mode, 2021-2034
11.6.7. Middle East & Africa AI in Drug Manufacturing Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2021-2034
Chapter 12. Competitive Landscape
12.1. Major Mergers and Acquisitions/Strategic Alliances
12.2. Company Profiles
12.2.1. C3.AI
12.2.1.1. Business Overview
12.2.1.2. Key AI solution/Service Overview
12.2.1.3. Financial Performance
12.2.1.4. Geographical Presence
12.2.1.5. Recent Developments with Business Strategy
12.2.2. AMD
12.2.3. IBM
12.2.4. Kalypso
12.2.5. SAS Institute
12.2.6. Körber Pharma
12.2.7. SDG Group
12.2.8. Catalyx
12.2.9. Elisa Industriq
12.2.10. Straive
12.2.11. Axiomtek
12.2.12. Appinventiv
12.2.13. Amplelogic
12.2.14. Precognize
AI in Drug Manufacturing Market by Type of Offering-
· Hardware
· Software
· Services
AI in Drug Manufacturing Market by Mode of Deployment-
· Cloud
· On-premise
AI in Drug Manufacturing Market by Type of AI Solution-
· Standard / Off-the-shelf AI solutions
· Personalized AI solutions
AI in Drug Manufacturing Market by Type of Technology-
· Computer Vision
· Deep Learning
· Generative AI
· Machine Learning
· Other Technologies
AI in Drug Manufacturing Market by Application Area-
· Process Development and Optimization
· Plant / Equipment Performance Monitoring
· Predictive Maintenance
· Quality Control
· Supply Chain Optimization
· Other Application Areas
AI in Drug Manufacturing Market by Utility in Drug Manufacturing-
· Defect Detection
· Packaging and Label Inspection
· Package Counting
· Fill Level Inspection
· Other Utilities
AI in Drug Manufacturing Market by Region-
North America-
· The US
· Canada
Europe-
· Germany
· The UK
· France
· Italy
· Spain
· Rest of Europe
Asia-Pacific-
· China
· Japan
· India
· South Korea
· Southeast Asia
· Rest of Asia Pacific
Latin America-
· Brazil
· Argentina
· Mexico
· Rest of Latin America
Middle East & Africa-
· GCC Countries
· South Africa
· Rest of the Middle East and Africa
InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.
Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.
Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.
Secondary research
The secondary research sources that are typically mentioned to include, but are not limited to:
The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista
Primary Research:
Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies
The contributors who typically take part in such a course include, but are not limited to:
Data Modeling and Analysis:
In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.
The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.
To know more about the research methodology used for this study, kindly contact us/click here.
