Artificial Intelligence (AI) Toolkit Market

[286 Pages Report] The AI Toolkit market is estimated at USD 19.5 billion in 2023 to USD 91.6 billion by 2028, at a Compound Annual Growth Rate (CAGR) of 36.2%. The increased accessibility of high-performance hardware components such as GPUs and TPUs has significantly enhanced the efficiency of training and deploying sophisticated AI models. AI toolkits are purposefully engineered to harness this computational power to its fullest potential, facilitating faster model development and improved performance. This alignment of AI toolkits with potent hardware resources is a pivotal factor driving the expansion of the AI toolkit market, as it empowers developers and organizations to leverage cutting-edge AI capabilities for a broad spectrum of applications.

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AI Toolkit Market Dynamics

Driver:  Growing adoption of AutoML to train high-quality models

AI technology has witnessed tremendous growth over the years. Hence, the demand for AI models and applications has also hiked. For developing accurate AI tool, it is important to use correct model architecture, collect proper data, and tune the model accordingly to fulfil desired key performance indicators (KPIs). Automated machine learning (AutoML) helps to automate the manual task of finding the best models and hyperparameters for the desired KPI. It can automatically find the best AI model for a specific goal and hide a lot of the complicated steps involved in creating and optimizing AI models. Various AI toolkits such as NVIDIA TAO offer 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.

Restraint: Lack of standardization in AI toolkit market

The need for more standardization in the AI toolkit market poses a major challenge for businesses and developers. Each AI 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 AI toolkits, including the rapid pace of innovation in AI, the diversity of AI applications, and the open-source nature of many AI toolkits. AI is constantly evolving, and new toolkits are always emerging. This makes it difficult for standards to be developed and adopted. AI is being used in various industries and applications, which has led to the development of various specialized AI toolkits. Many AI 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 AI toolkit market can have several negative consequences for businesses and developers, including increased costs, reduced productivity, and increased risk of errors.

Opportunity: Growth in data generated by IoT devices creating new opportunities

The automated power of AI is contributing to the adoption of intelligent IoT technologies, as organizations can extract insights from massive datasets collected by these devices. These insights enable organizations to create a holistic view of operations and business performance and use that data for launching new products and services in the market. IoT generates heaps of data, and this data offers new insights into organizational performance and health. AI helps businesses use the power of IoT by enabling prescriptive and predictive analytics to interpret data collected by sensors, trackers, and other input devices. These intelligent insights support preventive maintenance, improved decision-making, and forecasting leading to better customer service. For instance, in remote manufacturing sensors track production processes at different locations and send status updates to centralized facility that uses ML for monitoring machine health and reducing downtime occurring through failure prediction. AI plays an important role in addressing security issues faced during IoT implementations.

Challenge: Concerns related to AI transparency, explainability, and biases

The number of organizations adopting AI systems has increased. However, there have been ethical issues due to the black-box nature of AI systems. There are various interest groups across the world, including IEEE and ACM that have defined comprehensive ethical guidelines and principles to ensure responsible AI usage. Various established groups have developed AI ethical guidelines emphasizing transparency and explainability for developing AI systems. Organizations utilize different ML models and algorithms in the decision-making processes. Moreover, AI systems' outputs and decisions are usually difficult to understand and lack transparency. Even if an AI system is transparent, explaining how it reached a particular decision may not be easy. This makes it difficult to trust the system's decisions and identify and address potential biases. Sometimes, AI systems can be biased, reflecting the biases of the data they are trained on or the people who design them. This can lead to unfair and discriminatory outcomes. For instance, a facial recognition system biased against certain racial groups could lead to false arrests or other negative consequences. A medical diagnosis system that is biased against certain diseases or populations could lead to misdiagnoses and delays in treatment. It is important to address these concerns to ensure that AI systems are used responsibly and ethically.

AI Toolkit Market Ecosystem

Prominent players in this market include well-established, financially stable AI toolkit solutions, services providers, and regulatory bodies. These companies have been operating in the market for several years and possess a diversified product portfolio and state-of-the-art technologies. Prominent companies in this market include Microsoft (US), Google (US), and Meta (US) and so on.

"By technology, Natural Language Processing (NLP) segment to hold the largest market size during the forecast period.

NLP serves as a driving force behind popular voice assistants such as Google assistant and Amazon Alexa contributing to the adoption of the AI toolkit market. These voice-activated services have become integral to homes and businesses, enhancing human-computer interaction, and providing voice-activated solutions for an array of tasks. As these voice assistants gain widespread adoption, the demand for AI toolkits equipped with robust NLP capabilities continues to surge. This trend not only expands the AI 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.

“Based on vertical, the Healthcare & Life Sciences segment is expected to register the fastest growth rate during the forecast period. “

AI toolkits play a pivotal role in advancing healthcare AI research by enabling the analysis of large-scale healthcare datasets, and this function serves as a significant driver for the AI toolkit market. In recent healthcare institutions and researchers are overwhelmed with an unprecedented volume of patient records, medical imaging, genomic data, and clinical notes due to inclusion of big data. AI toolkits empower healthcare AI research by efficiently processing and deciphering this vast pool of information. By leveraging machine learning algorithms and natural language processing, AI 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 AI toolkits in healthcare AI research continues to grow, fostering innovation and driving the expansion of the AI toolkit market.

North America is expected to hold the largest market size during the forecast period

Government support and funding play a crucial role in driving the AI toolkit market in North America. The commitment of governments in the region to AI research and development initiatives not only fosters innovation but also enhances competitiveness. Public investments in AI projects, research centers, and infrastructure create an ecosystem encouraging collaboration between academia, industry, and startups. This, in turn, fuels the development and adoption of AI toolkits, as they are the fundamental building blocks for AI innovation. The availability of resources and funding facilitates the exploration of new AI applications and the expansion of AI capabilities, making North America a global leader in AI technology and driving the growth of the AI toolkit market in the region.

Market Players:

The major players in the AI Toolkit market are 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 AI (US), Levity AI (Germany), Union AI (US), Attri AI (US), Regie.ai (US). These players have adopted various growth strategies, such as partnerships, agreements and collaborations, new product launches and enhancements, and acquisitions to expand their AI Toolkit market footprint.

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Scope of the Report

This research report categorizes the AI Toolkit market to forecast revenues and analyze trends in each of the following submarkets:

Based on Offering:

• Software
• Hardware
  • Processors
  • Accelerators
  • Others (Memory and Networking Equipment)
• Services
  • Professional Services
  • Managed Services

Based on Technology:

• Natural Language Processing
• Machine Learning
• Computer Vision
• Robotic Process Automation

Based on 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
  • United States (US)
  • Canada
• Europe
  • United Kingdom (UK)
  • Germany
  • France
  • Italy
  • Spain
  • Nordics
  • Rest of Europe
• Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Australia & New Zealand
  • Southeast Asia
  • Rest of Asia Pacific
• Middle East & Africa
  • GCC Countries
  • South Africa
  • Rest of Middle East & Africa
• Latin America
  • Brazil
  • Mexico
  • Rest of Latin America

Recent Developments

• In September 2023, Infosys and NVIDIA expanded their existing collaboration to develop a generative AI platform to help enterprises increase productivity. The partnership offers a scalable platform using NVIDIA technology to enhance Infosys’ Responsible AI Toolkit.
• In August 2023, IBM and Salesforce collaborated to assist businesses across various sectors in expediting their integration of AI into Customer Relationship Management. This collaboration empowers organizations to transform customer, partner, and employee interactions while ensuring the security of their data.
• In July 2023, Microsoft and Meta partnered to support Large Language Models on Azure and Windows.

Frequently Asked Questions (FAQ):

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