#Artificial Intelligence (AI) Market Size

[mordormr]

AI Transforming Drug Discovery: The Future of the Pharmaceutical Market

Artificial Intelligence in Pharmaceutical Market is projected to be valued at USD 3.05 billion in 2024 and is anticipated to reach USD 18.06 billion by 2029, with a CAGR of 42.68% during the forecast period (2024-2029).

Artificial Intelligence (AI) in Drug Discovery Market is gaining momentum as pharmaceutical companies increasingly adopt AI-driven solutions to streamline research and development (R&D) processes. According to Mordor Intelligence, the market is expected to grow significantly, driven by the rising need for faster, cost-effective drug discovery methods, combined with advances in AI technologies like machine learning, natural language processing (NLP), and deep learning.

AI’s Role in Transforming Drug Discovery

Accelerating Drug Discovery Process: Traditionally, drug discovery is a time-consuming and costly process, often taking 10–15 years and billions of dollars to bring a new drug to market. AI is revolutionizing this by speeding up the identification of drug targets and optimizing lead compounds. Algorithms can rapidly analyze vast datasets, predicting drug behavior and outcomes more accurately than traditional methods.

Predictive Modeling and Simulation: AI's ability to create predictive models is transforming how pharmaceutical companies approach drug discovery. AI can simulate how compounds will interact with biological targets, reducing the need for trial-and-error lab work. This not only accelerates the development process but also enhances the chances of finding successful drug candidates.

Data-Driven Research: With the growing availability of biological and chemical data, AI can sift through and analyze enormous datasets, identifying patterns and insights that humans might miss. Machine learning models can analyze genomic data, protein structures, and chemical compounds, helping researchers understand complex biological mechanisms and predict potential therapeutic outcomes.

AI in Target Identification and Validation: AI tools are being employed to identify novel biological targets for therapeutic intervention, as well as to validate their potential effectiveness. This is especially crucial in the development of drugs for complex diseases like cancer, neurodegenerative disorders, and infectious diseases.

AI for Drug Repurposing: AI is also playing a pivotal role in drug repurposing, where existing drugs are investigated for new therapeutic uses. AI algorithms can identify new applications for existing compounds by analyzing data on drug interactions, mechanisms of action, and patient outcomes.

Reduction in Drug Development Costs: By reducing the time and cost involved in early-stage drug discovery, AI is contributing to significant cost savings. Traditional methods often lead to high failure rates, especially in late-stage clinical trials. AI can help mitigate these risks by improving early predictions on a drug’s efficacy and safety profile.

Key Market Growth Drivers

Rising Demand for Personalized Medicine: AI’s ability to analyze genetic, environmental, and lifestyle factors is driving growth in personalized medicine. AI-powered platforms can predict how individuals will respond to treatments, leading to more targeted and effective therapies.

Increasing Partnerships between Pharma and AI Companies: Collaborations between pharmaceutical companies and AI technology firms are growing. These partnerships aim to combine pharma's clinical expertise with AI’s data-processing capabilities to revolutionize drug discovery and development.

AI in Clinical Trials: AI is optimizing the clinical trial process by identifying ideal patient cohorts, predicting trial outcomes, and improving trial design. This not only speeds up the trial process but also reduces costs, which is critical in the pharmaceutical market.

Challenges and Opportunities

Data Quality and Integration: While AI offers immense potential, one of the primary challenges remains the quality and integration of data. Pharmaceutical companies must ensure they have access to clean, structured data to fully leverage AI’s capabilities in drug discovery.

Regulatory Concerns: As AI becomes more integrated into drug discovery, regulatory agencies are working to establish frameworks to ensure the safety and efficacy of AI-driven drugs. Navigating these evolving regulatory landscapes will be crucial for pharmaceutical companies.

AI Talent Shortage: As the demand for AI in drug discovery grows, there is a shortage of skilled professionals who can build, implement, and manage these technologies. Addressing this talent gap is essential for sustained market growth.

Regional Insights

North America leads the market due to the presence of major pharmaceutical companies, strong healthcare infrastructure, and early adoption of AI technologies. The region’s advanced regulatory environment also supports the integration of AI in drug discovery.

Europe follows closely, driven by increased R&D funding and government support for AI initiatives in healthcare. Asia-Pacific is also expected to see rapid growth due to rising investments in AI and a growing pharmaceutical industry in countries like China and India.

Future Outlook

AI’s transformative impact on drug discovery is still in its early stages, but the potential is vast. As AI continues to evolve, it is expected to significantly reduce the cost and time associated with bringing new drugs to market, while also improving success rates in clinical trials. This will not only benefit pharmaceutical companies but also patients, who will gain faster access to innovative treatments.

In conclusion, AI is reshaping the future of the pharmaceutical industry by optimizing drug discovery processes, improving patient outcomes, and driving cost-efficiency. The next few years will be critical as AI’s role in drug discovery continues to expand, opening up new opportunities for innovation in the pharmaceutical market.

For a detailed overview and more insights, you can refer to the full market research report by Mordor Intelligence https://www.mordorintelligence.com/industry-reports/artificial-intelligence-in-pharmaceutical-market

[trendingreportz]

Artificial Intelligence (AI) in Collaborative Robotic (Cobots) Systems Market - Forecast(2024 - 2030)

AI in Cobots Market Overview

The global AI in cobots market in 2021 reached $118.2 million and is estimated to grow at a CAGR of 34.22% during the forecast period to reach $616.3 million by 2027. The entire robotics industry is witnessing the effects of Covid-19 pandemic, with strain felt on the supply chain restricting parts of imports and equipment exports in H1 2021 especially. The overall economic uncertainty also pushed majority of customers to defer purchases in order to conserve capital. Recent advancements in Machine Learning and human robot interaction have enabled collaborative robots to precisely execute tasks in dynamically changing workspaces, enabling operations and material handling to run more smoothly, efficiently and productively. AI is now intelligently powering cobots by leveraging billions of hours of iterative machine learned practices in manufacturing, production and engineering. Collaborative robots (cobots) represent a variant of industrial robots and is currently considered to be one of the fastest growing segments in industrial automation driven by improved technology such as virtual assistants, cloud computing, internet of things. A cobot is a type of robot that is designed to operate alongside humans in shared workspaces. These machines are easy to program and deploy, can increase productivity manifold, and offer high returns on investment.

Report Coverage

The report: “AI in Cobots Market – Forecast (2022-2027)”, by IndustryARC covers an in-depth analysis of the following segments of the AI in Cobots market

By Payload: Up to 5 Kg, 5 to 10 Kg, Above 10 Kg. By Application: Handling, Assembling/Disassembling, Welding and Soldering, Dispensing, Packaging and Others. By End User: Automotive, Electronics, Semiconductor, Plastics and Polymer, Food and Beverage, Healthcare, Metals and Machining and others. By Geography: North America (U.S, Canada, Mexico), South America (Brazil, Argentina and others), Europe (Germany, UK, France, Italy, Spain, Russia and Others), APAC (China, Japan India, SK, Aus and Others), and RoW (Middle east and Africa).

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Key Takeaways

Group PSA’s Sochaux plant in France has chosen Universal Robots UR10 for its "Plant of the Future" Project. Two UR10 cobots have been implemented at the Sochaux plant in screw driving applications on body-in-white assembly lines to increase performance and reduce production costs at the factory.

In 2019, Walmart has planned to invest $2.7 billion to add new robots totaling almost 4,000 robots in its stores and facilities in order to shift human workforce to customer service roles. The robots are majorly used for scanning, sorting goods from delivery trucks. This is set to create opportunities for AI in cobots in retail sector.

AI in Cobots Market Segment Analysis – By Application

Material Handling had a major share in the AI in Cobots Market with a value share of approximately 22.3% in 2021. Material handling is one of the major applications of industrial robots. Robots in material handling segment are used in applications such as movement of goods, protection, storage and control of products throughout manufacturing as well as warehousing of the products. Any industries that need to store, receive, dispatch or ship its products always entail industrial robot. Manufacturing and Warehouse operations involving handling of goods becomes complex when it takes place at a larger scale. This is made easy and efficient with the aid of industrial robots. Material handling robots are majorly used in warehousing applications as compared to its counterpart. Material handling applications that benefit from the incorporation of AI cobots encompass picking, packing, palletizing, sorting, and more. The wide-ranging use of these applications makes them a more site-specific solution for safety implementation. Operators and other workers are often moving or transporting other materials around the AI cobot, requiring additional planning to avoid hazardous contact. Safety-rated grippers are rare in the market at the present time. Currently, manufacturers typically use pneumatic grippers, which require safety considerations for impacts and the loss of power or suction. Uses of bar code, RFID, voice-activated receiving and packaging, pick-to-light technology, transportation management system is some of the drifts observed by material handling robots. Cycle counting, annual, physical and perpetual are few approaches of keeping a track of inventory.

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AI in Cobots Market Segment Analysis – By End User

Among industries, automotive held the largest share in 2021 at 23.2%. The industry development of AI cobots is ongoing in several different areas. Faster reaction time, more exact movement patterns, orientation capabilities, capabilities in imitating humans – all these aspects contribute to advancements in AI driven cobot development. In addition, brain-computer interfaces is an exciting area that has made significant progress recently. In recent developments in technologies such as linked data, parallel processing, edge computing and distributed artificial intelligence allow for efficient decision making by cobots, making execution robust and efficient. A challenge with the market deployment of AI cobots is that insufficient technology maturity hinders the market deployment of cobots. AI Cobot technology includes hardware design, sensors and actuators, efficient information processing, video processing, planning and multiple of fields from artificial intelligence landscapes, along with technologies that ensure safety, predictability and security of the solution. There is currently a need for high amount of signaling, bandwidth, low latency, and fast decision-making capabilities through efficient computing for AI driven cobots in safety-critical environments, wherein the facilities do not need human intervention. While the automation industry was affected during the pandemic, the longterm outlook for automation is positive, as end users evaluate their reliance on overseas supply chains and reevaluate their operations in a world where a pandemic can stop production cold. Automation is hence being looked upon as a valuable bulwark against the risks laid bare during the pandemic, and this can act as a strong growth driver for AI driven cobots and robots in industrial automation end user verticals.

AI in Cobots Market Segment Analysis – By Geography

Geographically, APAC held major share of 37% of AI in cobots market share in 2021, owing to high adoption of automation technologies in industrial and automotive warehouses and increasing investments and funding. North America is the next largest market with 33% revenue share in 2021. South America is witnessing the fastest growth rate with a CAGR of around 46.6% during the forecast period 2022 – 2027 owing to high investments and growing deployment of automation technology mainly in the countries such as Brazil, Argentina and Colombia. Portuguese company MOV.AI has announced in October, 2020 that it has raised $4m in funding. The company has designed its ROS for manufacturers of cobots, as well as academics and automation integrators. It also contributes to the ROS community. Some of the robots with AI enabled are YuMi from ABB, Franka Emika Panda, APAS from Bosch, Aura, Aubo, NEXTAGE and CORO etc.

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AI in Cobots Market Drivers

Growing demand for automation and technological advancements set to drive the AI In Collaborative Robotics Market

There has been significant growth in AI driven collaborative robotics market owing to the increased demand for automation, high competition in the e-commerce industry, and the advancement in technologies such as Internet of Things (IoT) and Artificial Intelligence (AI). The use of robots reduces the risk of injury to workforce has also witnessed growth. Integration of robots with artificial intelligence (AI) and machine vision technology has been assisting companies in obstacle detection, navigation, movement of the goods. This has been attracting vendors in automating the warehouses and installing the robots in warehouse, thereby driving the collaborative robotics market. In 2019, Geek Plus Robotics, an intelligent logistics robot solution provider had launched the world’s first interweaving sorting robot, which could be an alternative to conveyor systems. Mobile Industrial Robots (MiR), a leading manufacturer of collaborative mobile robots launched a new warehouse robot to automate the transportation of pallets and heavy goods across warehouses. Development of new robots for various applications of warehouses set to boost the demand of collaborative robotics market.

Growth in E-Commerce Sector

E-Commerce industry is rising at global level of retail and logistics. As a result, growing number of e-commerce companies look forward to automate warehouses. Warehouse robots play a key role in e-commerce industry for various applications such as automated storage and retrieval, picking and placing, order fulfillment operations and many others. Adoption of warehouse cobots by e-commerce companies helps in reducing operational and logistical costs and save on delivery time. This has been increasing automation in warehouses in order to deliver goods to shoppers in faster and more efficient ways by increasing productivity of supply chain. In developed countries such as the U.S., and Canada, Grocery retailers are focusing on deploying robots that bring the shelf stacks to human workers, who pick out the right products and package them up to be sent out. These robots travel with high speed, faster than humans, thereby increasing efficiency of the work. In 2019, Amazon had introduced new warehouse cobots in several of its U.S. warehouses that scan and pack items to be sent to customers. It has started using robots in warehouses, which scans goods coming down a conveyor belt raising the scope of adoption. In 2020 Covariant.ai launched its AI robots and solutions through its warehouse bin-picking robots which is being used by companies such as Knapp, a warehouse logistics company and Obeta, a German electronics retailer. As per estimates, around 2,000 AI powered robots have been deployed across warehouses globally.

AI in Cobots Market Challenges

High Initial Investment

The initial cost of AI driven collaborative robots that are used in factories are high as the cost of automation is much higher in comparison with labor costs. This prevents most companies from completely automating their operations with robots. The average selling prices of cobots vary from $25,000 to $50,000 and does not include the installation costs. In addition to this, there is a training cost associated with the robots that further restricts the operators’ likeability for integrating robots into their operating lines. Slow deployment of collaborative robotic systems by smaller and medium enterprises hampers the robotics market. However, high labor costs are set to drive the collaborative robot market during forecast period.

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AI in Cobots Market Landscape

Technology launches, acquisitions, and R&D activities are key strategies adopted by players in the AI in Cobots market. In 2021, the market of AI in Cobots market has been consolidated by the top players

Fanuc

Techman Robots

Rethink Robots

AUBA Robots

ABB

Kawasaki

KUKA

Yaskawa

Staubli

Universal Robots

Recent Developments

In May 2019, the government of Saudi Arabia announced an investment of $30 billion to upgrade warehousing facilities by adoption of the advanced autonomous robots in the newly built warehouses across Saudi Arabia, thereby contributing towards the growth of the cobots market during forecast period in this region.

In October 2019, the South Korean government announced an investment $150 million to develop the intelligent robots for various industrial application which includes warehousing and logistics, thereby enhancing the growth of the cobots market.

[marketreports-blog]

The U.S. artificial intelligence (AI) market size was estimated at USD 37.01 billion in 2023 and is projected to hit around USD 369.34 billion by 2033, growing at a CAGR of 28.83% during the forecast period from 2024 to 2033.

[laxmandige05]

In the rapidly growing field of global artificial intelligence (AI) in life sciences market size was valued at USD 1.72 billion in 2023 and is projected to reach USD 8.92 million by 2032, growing at a CAGR of 20.1% from 2023 to 2032 according to a new report by Nova One Advisor.

[health-views-updates]

Artificial Intelligence (AI) In Diagnostics Market Forecast 2030 by Manufacturing Technology, Key Manufacturers, Industry Trends

The global Artificial Intelligence (AI) in Diagnostics market size was valued at USD 1,172.46 million in 2022 and is anticipated to reach USD 5,123.16 million by 2030, exhibiting a remarkable CAGR of 23.45% during the forecast period from 2023 to 2030. These insights are drawn from an exhaustive report titled "Artificial Intelligence in Diagnostics Market Size" released by SNS Insider.

The integration of artificial intelligence in diagnostic processes has revolutionized the healthcare industry by enhancing the accuracy, efficiency, and speed of diagnoses. AI-powered diagnostic solutions leverage advanced algorithms, machine learning, natural language processing (NLP), context-aware computing, and computer vision technologies to analyze medical data and assist healthcare professionals in making more informed decisions.

Get Free PDF Sample Copy of Report @ https://www.snsinsider.com/sample-request/1849

The report segments the Artificial Intelligence in Diagnostics market based on component, technology, diagnosis type, and geographic scope:

Component: Hardware, Software, Services.

Technology: Machine Learning, NLP, Context-Aware Computing, Computer Vision.

Diagnosis Type: Radiology, Oncology, Neurology & Cardiology, Chest & Lungs, Pathology.

Geographic Scope: Regional and Global Markets.

Among these segments, the machine learning technology segment is expected to witness substantial growth during the forecast period, owing to its ability to analyze large datasets and identify patterns and anomalies with high accuracy. Additionally, the radiology diagnosis type segment is anticipated to dominate the market due to the increasing adoption of AI-powered imaging solutions for early disease detection and treatment planning.

Geographically, North America holds a significant share in the Artificial Intelligence in Diagnostics market, attributed to the presence of key market players, technological advancements in healthcare infrastructure, and favorable government initiatives supporting AI research and development. However, the Asia Pacific region is projected to witness rapid growth opportunities during the forecast period, driven by the increasing healthcare expenditure, rising prevalence of chronic diseases, and growing demand for advanced diagnostic solutions.

Key players operating in the Artificial Intelligence in Diagnostics market include HeartFlow, Inc., Therapixel SA, Nano-X Imaging Ltd., Prognos Health Inc., Butterfly Network, Inc., Aidence B.V., Siemens AG, GE Healthcare, Digital Diagnostics Inc., IBM. These companies are focusing on strategic collaborations, partnerships, and product innovations to gain a competitive edge in the market.

In conclusion, the global Artificial Intelligence in Diagnostics market is poised for substantial growth over the forecast period, driven by the increasing adoption of AI-powered diagnostic solutions, technological advancements in healthcare, and growing demand for accurate and efficient diagnostic tools.

[luckydige45]

The global Artificial Intelligence (AI) in Renewable Energy Industry size was estimated at USD 10 billion in 2022 and is projected to hit around USD 114.87 billion by 2032, growing at a CAGR of 27.70% during the forecast period from 2023 to 2032.

[kenresearch1]

Discover the Future of Farming: Global AI in Agriculture Industry is transforming agriculture through advanced technology and industry leaders like IBM and John Deere.

[futuretonext]

The North America Artificial Intelligence (AI) in Stock Trading Market is projected to grow at a CAGR of more than 50% during the forecast period, i.e., 2023-28. AI & other data-science technologies have simplified the stock trading workflow by enabling easy & real-time identification of complex trading patterns across varied markets. Besides, they have also reduced communication complexity and enhanced business processes & customer care interactions. Hence, the coming years will likely be highly optimistic for AI in the stock trading industry. With increasing innovations in AI & machine learning, payment processors, banks, and other financial organizations are now able to detect fraud & make informed decisions. In addition, the capability of AI to gather & classify unbiased information, recognize stock patterns, and effectively perform stock analysis is expected to propel the industry in the coming years.

[rohitsathpute45]

The artificial intelligence (AI) market size was estimated at USD 454.19 billion in 2022 and is expected to surpass around USD 2,608.29 billion by 2032 and poised to grow at a compound annual growth rate (CAGR) of 19.1% during the forecast period 2023 to 2032.

[marketspace360]

Artificial Intelligence (AI) in Retail Market| Manufacturers, Regions, Type and Application, Forecast by 2029

[marketreports-blog]

The global artificial Intelligence (Ai) in medical diagnostics market size was exhibited at USD 1.90 billion in 2022 and is projected to hit around USD 51.56 billion by 2032, growing at a CAGR of 39.11% during the forecast period 2023 to 2032.

[laxmandige05]

According to the latest research by nova one advisor, the global artificial intelligence (AI) In drug discovery market size is estimated at USD 1,939.01 million in 2023, and is expected to reach USD 20,041.44 million by 2033, growing at a CAGR of 29.63% during the forecast period (2024-2033).

[luckydige45]

The global automotive artificial intelligence market size was exhibited at USD 3.17 billion in 2022 and is projected to hit around USD 22.96 billion by 2032, growing at a CAGR of 21.9% during the forecast period 2023 to 2032.