Artificial Intelligence (AI) Toolkit Market Building

Artificial Intelligence (AI) Toolkit Market worth $981.41 Bn by 2031 – Exclusive Report by InsightAce Analytic Pvt. Ltd.

InsightAce Analytic Pvt. Ltd. announces the release of a market assessment report on the “Global Artificial Intelligence (AI) Toolkit Market- (By Offering (Software, Hardware (Processors, Accelerators (Graphics processing units (GPUs), Tensor processing units, Field programmable processing units, Neuromorphic chips), Others Hardware Types), Services (Professional Services, Consulting, Deployment & integration, Support & maintenance),

Managed Services), By Technology (Natural Language Processing, Machine Learning, Computer Vision, Robotic Process Automation), By Vertical (Banking, Financial Services, & Insurance (BFSI), Retail & eCommerce, Healthcare & Life Sciences, Manufacturing, Telecom, IT & ITeS, Media & Entertainment,

Energy & Utilities, Government & Defense, Automotive, Transportation, & Logistics, Other Verticals (Education, Travel & Hospitality, Construction & Real Estate, and Agriculture))), Trends, Industry Competition Analysis, Revenue and Forecast To 2031.”

According to the latest research by InsightAce Analytic, the Global Artificial Intelligence (AI) Toolkit Market is valued at US$ 15.02 Bn in 2022, and it is expected to reach US$ 212.70 Bn by 2031, with a CAGR of 34.46% during the forecast period of 2024-2031.

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The AI Toolkit Market: Empowering AI Innovation Across Industries
The Artificial Intelligence (AI) Toolkit Market encompasses the development and distribution of software tools, frameworks, libraries, and platforms that streamline the creation and deployment of AI applications.

These toolkits offer a comprehensive suite of resources for building:
• Machine learning models
• Natural language processing systems
• Computer vision applications
• And more

Market Landscape and Growth Drivers
The AI toolkit market is characterized by:
• Leading players: Technology giants like IBM, Google, Microsoft, and AWS, along with innovative startups and open-source projects.

• Significant growth and innovation: Driven by the increasing demand for AI across various sectors.

The Power of AI Toolkits
AI toolkits play a crucial role in:
• Advancing the development of AI technologies
• Facilitating the widespread adoption of AI in industries like:
o Healthcare
o Finance
o Manufacturing
o Autonomous systems

Market Growth Reflects Broader AI Adoption
The growth of the AI toolkit market mirrors the overall expansion and development of AI applications. This surge is fueled by the rising demand for AI technology across diverse industries, including healthcare, finance, and autonomous systems.

Overall, the AI Toolkit Market serves as a vital catalyst, empowering innovation and adoption of AI across a wide range of industries.

List of Major Players in the Artificial Intelligence (AI) Toolkit market:

• 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)
• Others

Market Dynamics:

Drivers-
Al technology has witnessed tremendous growth over the years. Hence, the demand for Al models and applications has also hiked. For developing an accurate Al tool, it is important to use the correct model architecture, collect proper data, and tune the model accordingly to fulfil desired key performance indicators (KPIs).

Automated machine learning (AutoML) streamlines the process of identifying the optimal models and hyperparameters for a given key performance indicator (KPI). It can automatically find the best Al model for a specific goal and hide many of the complicated steps involved in creating and optimizing Al models.

Various Al toolkits, such as NVIDIA TAO, offer an AutoML feature that automatically optimizes the hyperparameters of a model, reducing the need for manual tuning. This contributes to the increasing adoption of AutoML for training and deploying high-quality models.

Challenges:
The prime challenge is the need for more standardization in the Al toolkit market, which poses a major challenge for businesses and developers. Each Al toolkit available in the market has its strengths and weaknesses. This makes it difficult for businesses to choose the right toolkit for their needs and for developers to learn and use different toolkits. Various factors contribute to the need for more standardization in the Al toolkits, including the rapid pace of innovation in Al,

the diversity of Al applications, and the open-source nature of many Al toolkits. Al is constantly evolving, and new toolkits are always emerging. This makes it difficult for standards to be developed and adopted. Al is being used in various industries and applications, which has led to the development of various specialized Al toolkits.

Many Al toolkits are open source, meaning they are developed and maintained by a community of volunteers. This makes it challenging to coordinate development and ensure compatibility between different toolkits. The lack of standardization in the Al toolkit market can have several negative consequences for businesses and developers, including increased costs, reduced productivity, and increased risk of errors.

Regional Trends:
In North America, the Artificial Intelligence (AI) Toolkit market is flourishing, driven by a high demand for AI-driven solutions across diverse industries. Key regional trends include strong investments in AI research and development, particularly in technology hubs like Silicon Valley. North America boasts significant contributions from industry giants like IBM,

Google, and Microsoft, further propelling market growth. Additionally, favourable regulatory and business environments encourage innovation. The region’s AI toolkit market is characterized by a continuous focus on enhancing AI capabilities and driving technological advancements that impact various sectors, including healthcare, finance, and autonomous vehicles.

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Recent Developments:

• In Nov 2023, IBM declared its intention to release a data governance toolbox for artificial intelligence (AI) models that would be widely accessible. The purpose of this toolkit is to enhance openness in the recommendations produced by AI tools. IBM has announced that watsonx.governance will be accessible starting in early December 2023.

• In May 2023, Jasper declared an expanded collaboration with Google Cloud. The collaboration extended the accessibility of Jasper to a vast user base via the Google Cloud Marketplace, incorporated an additional foundational model into Jasper’s AI Engine in conjunction with Google’s Vertex AI,

and unveiled fresh functionalities for Jasper Everywhere. By forming this partnership, Jasper successfully implemented its overarching goal of offering customized AI support to enterprises, accessible from any location they establish.

Segmentation of Artificial Intelligence (AI) Toolkit market –
By Offering:
• Software
• Hardware
o Processors
o Accelerators
 Graphics processing units (GPUs)
 Tensor processing units
 Field programmable processing units
 Neuromorphic chips
o Others Hardware Types
• Services
o Professional Services
 Consulting
 Deployment & Integration
 Support & Maintenance
• Managed Services

By Technology:
• Natural Language Processing
• Machine Learning
• Computer Vision

By Vertical:
• Banking, Financial Services, & Insurance (BFSI)
• Retail & eCommerce
• Healthcare & Life Sciences
• Manufacturing
• Telecom
• IT & ITeS
• Media & Entertainment
• Energy & Utilities
• Government & Defense
• Automotive, Transportation, & Logistics
• Other Verticals (Education, Travel & Hospitality, Construction & Real Estate, and Agriculture)

By Region-
North America-
• The US
• Canada
• Mexico

Europe-
• Germany
• The UK
• France
• Italy
• Spain
• Rest of Europe

Asia-Pacific-
• China
• Japan
• India
• South Korea
• South East Asia
• Rest of Asia Pacific

Latin America-
• Brazil
• Argentina
• Rest of Latin America

Middle East & Africa-
• GCC Countries
• South Africa
• Rest of Middle East and Africa

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Originally Appeared Here

Author: Rayne Chancer