_Toolkit.JPG)
Artificial Intelligence (AI) Toolkit Market Size is valued at USD 15.02 Bn in 2022 and is predicted to reach USD 212.70 Bn by the year 2031 at a 34.46% CAGR during the forecast period for 2023-2031.
The Artificial Intelligence (AI) toolkit market is experiencing robust growth and innovation. With key players like IBM, Google, Microsoft, and AWS, these toolkits are integral for AI application development. The market's evolution is driven by the expanding adoption of AI in various industry sectors, from healthcare to finance, underpinned by the Asia Pacific region's rapid growth. As governments support AI research and development and a skilled workforce emerges, the AI toolkit market is poised for continued expansion. Smaller startups and open-source projects further contribute to its dynamism, ensuring that AI technologies continue to advance and find new applications across a wide range of sectors.
However, the shortage of AI talent has created a thriving market for Artificial Intelligence (AI) toolkits. These toolkits provide pre-built solutions and libraries to empower businesses with AI capabilities without extensive expertise. As organizations seek to harness AI's potential, the toolkit market offers accessible and efficient solutions to bridge the talent gap and accelerate AI adoption.
The Artificial Intelligence (AI) toolkit market is segmented based on offering, technology and vertical. As per the offering, the market is segmented as software, hardware, processors, accelerators, and others (memory and networking equipment), and services include professional services and managed services. According to technology, the market is segmented as natural language processing(NLP), machine learning, computer vision, and robotic process automation. As per the vertical, the market is segmented as banking, financial services, & insurance (bfsi), retail & e-commerce, healthcare & life sciences, manufacturing, telecom, it & sites, media & entertainment, energy & utilities, government & defence, automotive, transportation, & logistics and other verticals (education, travel & hospitality, construction & real estate, and agriculture)
Natural Language Processing (NLP) segment will hold the largest market size during the forecast period. NLP is a driving force behind popular voice assistants (Google Assistant, Amazon Alexa, etc.) contributing to the adoption of the Al toolkit market. These voice-activated services have become integral to homes and businesses, enhancing human-computer interaction and providing voice-activated solutions for various tasks. As these voice assistants gain widespread adoption, the demand for Al toolkits with robust NLP capabilities continues to surge. This trend not only expands the Al toolkit market but also promotes innovation in NLP technology, enabling more versatile and sophisticated voice-activated applications across various sectors, from smart homes to healthcare and customer service.
The Healthcare and Life Sciences segment is expected to lead with the maximum growth rate during the forecast period. "Al toolkits play a pivotal role in advancing healthcare Al research by enabling the analysis of large-scale healthcare datasets, and this function serves as a significant driver for the Al toolkit market. Healthcare institutions and researchers have recently been overwhelmed with an unprecedented volume of patient records, medical imaging, genomic data, and clinical notes due to the inclusion of big data.
Al toolkits empower healthcare Al research by efficiently processing and deciphering this vast pool of information. By leveraging machine learning (ML) algorithms and natural language processing, Al toolkits uncover hidden patterns, correlations, and insights that might elude human analysts. This not only expedites the pace of medical discoveries but also supports the development of more accurate diagnostics, treatment recommendations, and predictive healthcare models. As a result, the demand for Al toolkits in healthcare Al research continues to grow, fostering innovation and driving the expansion of the Al toolkit market.
The North America Artificial Intelligence (AI) Toolkit market drives government support and funding. The commitment of governments in the region to Al research and development initiatives not only fosters innovation but also enhances competitiveness. Public investments in Al projects, research centres, and infrastructure create an ecosystem encouraging collaboration between academia, industry, and startups. This, in turn, fuels the development and adoption of Al toolkits, as they are the fundamental building blocks for Al innovation.
The availability of resources and funding facilitates the exploration of new Al applications and the expansion of Al capabilities, making North America a global leader in Al technology and driving the growth of the Al toolkit market in the region. In addition, Asia Pacific is witnessing substantial growth in the Artificial Intelligence (AI) Toolkit market. It is driven by the increased adoption of AI technology across various sectors, including healthcare, finance, and manufacturing.
|
Report Attribute |
Specifications |
|
Market Size Value In 2022 |
USD 15.02 Bn |
|
Revenue Forecast In 2031 |
USD 212.70 Bn |
|
Growth Rate CAGR |
CAGR of 34.46 % from 2023 to 2031 |
|
Quantitative Units |
Representation of revenue in US$ Bn and CAGR from 2023 to 2031 |
|
Historic Year |
2019 to 2022 |
|
Forecast Year |
2023-2031 |
|
Report Coverage |
The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
|
Segments Covered |
By Offering, Technology, Vertical |
|
Regional Scope |
North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
|
Country Scope |
U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico; France; Italy; Spain; South East Asia; South Korea |
|
Competitive Landscape |
Microsoft (US), Google (US), IBM (US), Oracle (US), Thales Group (France), Salesforce (US), Intel (US), Adobe (US), Meta Platforms (US), AWS (US), NVIDIA Corporation (US), H2O.ai (US), Alteryx (US), Altair (US), KNIME (Switzerland), DataRobot (US), Jasper (US), Rasa (US), SuperAnnotate (US), OpenAI (US), Obviously AI (US), Fiddler AI (US), Determined AI (US), Snorkel Al (US), Levity Al (Germany), Union AI (US), Attri AI (US), Regie.ai (US), and others |
|
Customization Scope |
Free customization report with the procurement of the report and modifications to the regional and segment scope. Particular 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 Artificial Intelligence (AI) Toolkit Market Snapshot
Chapter 4. Global Artificial Intelligence (AI) Toolkit 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. Industry Analysis – Porter’s Five Forces Analysis
4.7. Competitive Landscape & Market Share Analysis
4.8. Impact of Covid-19 Analysis
Chapter 5. Market Segmentation 1: By Offering Estimates & Trend Analysis
5.1. By Offering, & Market Share, 2020 & 2031
5.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2020 to 2031 for the following By Offering:
5.2.1. Software
5.2.2. Hardware
5.2.2.1. Processors
5.2.2.2. Accelerators
5.2.2.2.1. Graphics processing units (GPUs)
5.2.2.2.2. Tensor processing units
5.2.2.2.3. Field programmable processing units
5.2.2.2.4. Neuromorphic chips
5.2.2.3. Others (Memory and Networking Equipment)
5.2.3. Services
5.2.3.1. Professional Services
5.2.3.1.1. Consulting
5.2.3.1.2. Deployment & Integration
5.2.3.1.3. Support & Maintenance
5.2.3.2. Managed Services
Chapter 6. Market Segmentation 2: By Technology Estimates & Trend Analysis
6.1. By Technology & Market Share, 2020 & 2031
6.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2020 to 2031 for the following By Technology:
6.2.1. Natural Language Processing
6.2.2. Machine Learning
6.2.3. Computer Vision
6.2.4. Robotic Process Automation
Chapter 7. Market Segmentation 3: By Vertical Estimates & Trend Analysis
7.1. By Vertical & Market Share, 2020 & 2031
7.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2020 to 2031 for the following By Vertical:
7.2.1. Banking, Financial Services, & Insurance (BFSI)
7.2.2. Retail & eCommerce
7.2.3. Healthcare & Life Sciences
7.2.4. Manufacturing
7.2.5. Telecom
7.2.6. IT & ITeS
7.2.7. Media & Entertainment
7.2.8. Energy & Utilities
7.2.9. Government & Defense
7.2.10. Automotive, Transportation, & Logistics
7.2.11. Other Verticals (Education, Travel & Hospitality, Construction & Real Estate, and Agriculture)
Chapter 8. Artificial Intelligence (AI) Toolkit Market Segmentation 4: Regional Estimates & Trend Analysis
8.1. North America
8.1.1. North America Artificial Intelligence (AI) Toolkit Market revenue (US$ Million) estimates and forecasts By Offering, 2019-2031
8.1.2. North America Artificial Intelligence (AI) Toolkit Market revenue (US$ Million) estimates and forecasts By Technology, 2019-2031
8.1.3. North America Artificial Intelligence (AI) Toolkit Market revenue (US$ Million) estimates and forecasts By Vertical, 2019-2031
8.1.4. North America Artificial Intelligence (AI) Toolkit Market revenue (US$ Million) estimates and forecasts by country, 2019-2031
8.2. Europe
8.2.1. Europe Artificial Intelligence (AI) Toolkit Market revenue (US$ Million) By Offering, 2019-2031
8.2.2. Europe Artificial Intelligence (AI) Toolkit Market revenue (US$ Million) By Technology, 2019-2031
8.2.3. Europe Artificial Intelligence (AI) Toolkit Market revenue (US$ Million) By Vertical, 2019-2031
8.2.4. Europe Artificial Intelligence (AI) Toolkit Market revenue (US$ Million) by country, 2019-2031
8.3. Asia Pacific
8.3.1. Asia Pacific Artificial Intelligence (AI) Toolkit Market revenue (US$ Million) By Offering, 2019-2031
8.3.2. Asia Pacific Artificial Intelligence (AI) Toolkit Market revenue (US$ Million) By Technology, 2019-2031
8.3.3. Asia Pacific Artificial Intelligence (AI) Toolkit Market revenue (US$ Million) By Vertical, 2019-2031
8.3.4. Asia Pacific Artificial Intelligence (AI) Toolkit Market revenue (US$ Million) by country, 2019-2031
8.4. Latin America
8.4.1. Latin America Artificial Intelligence (AI) Toolkit Market revenue (US$ Million) By Offering, (US$ Million) 2019-2031
8.4.2. Latin America Artificial Intelligence (AI) Toolkit Market revenue (US$ Million) By Technology, (US$ Million) 2019-2031
8.4.3. Latin America Artificial Intelligence (AI) Toolkit Market revenue (US$ Million) By Vertical, (US$ Million) 2019-2031
8.4.4. Latin America Artificial Intelligence (AI) Toolkit Market revenue (US$ Million) by country, 2019-2031
8.5. Middle East & Africa
8.5.1. Middle East & Africa Artificial Intelligence (AI) Toolkit Market revenue (US$ Million) By Offering, (US$ Million) 2019-2031
8.5.2. Middle East & Africa Artificial Intelligence (AI) Toolkit Market revenue (US$ Million) By Technology, (US$ Million) 2019-2031
8.5.3. Middle East & Africa Artificial Intelligence (AI) Toolkit Market revenue (US$ Million) By Vertical, (US$ Million) 2019-2031
8.5.4. Middle East & Africa Artificial Intelligence (AI) Toolkit Market revenue (US$ Million) by country, 2019-2031
Chapter 9. Competitive Landscape
9.1. Major Mergers and Acquisitions/Strategic Alliances
9.2. Company Profiles
9.2.1. Microsoft (US),
9.2.2. Google (US),
9.2.3. IBM (US),
9.2.4. Oracle (US),
9.2.5. Thales Group (France),
9.2.6. Salesforce (US),
9.2.7. Intel (US),
9.2.8. Adobe (US),
9.2.9. Meta Platforms (US),
9.2.10. AWS (US),
9.2.11. NVIDIA Corporation (US),
9.2.12. H2O.ai (US),
9.2.13. Alteryx (US),
9.2.14. Altair (US),
9.2.15. KNIME (Switzerland),
9.2.16. DataRobot (US),
9.2.17. Jasper (US),
9.2.18. Rasa (US),
9.2.19. SuperAnnotate (US),
9.2.20. OpenAI (US),
9.2.21. Obviously AI (US),
9.2.22. Fiddler AI (US),
9.2.23. Determined AI (US),
9.2.24. Snorkel AI (US),
9.2.25. Levity AI (Germany),
9.2.26. Union AI (US),
9.2.27. Attri AI (US),
9.2.28. Regie.ai (US).
Artificial Intelligence (AI) Toolkit Market By Offering:
Artificial Intelligence (AI) Toolkit Market By Technology:
Artificial Intelligence (AI) Toolkit Market By Vertical:
Artificial Intelligence (AI) Toolkit Market By Region-
North America-
Europe-
Asia-Pacific-
Latin America-
Middle East & 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.
