Market Definition - Artificial Intelligence Platform (AI)

The Artificial Intelligence (AI) platform is a collection of services that facilitate the machine learning process. This covers assistance with data collection and preparation, as well as training, testing, and deploying machine learning models for large-scale applications. Layers in AI platforms enable enterprises to deploy machine learning models from a range of frameworks, languages, platforms, and tools. These layers can be classified into five groups:

1. The Data and Integration Layer
2. The Experimentation Layer
3. The Operations and Deployment Layer
4. The Intelligence Layer
5. The Experience Layer

The AI platform gives developers the tools and technology they need to build AI-powered apps. Many AI apps are now designed specifically for cloud-based platforms, allowing for quick and easy deployment. The algorithms in the AI platform provide logical models for application developers to construct a variety of unique applications, such as speech and voice recognition, text recognition, and predictive analytics.

Market Overview

Due to the development of massive amounts of data that require analysis to enhance service providers' decision-making processes, the Artificial Intelligence (AI) platform industry is expected to increase in the coming years. The worldwide Artificial Intelligence (AI) platform market is predicted to increase at a 30.5% compound annual growth rate (CAGR) from USD 2.61 billion in 2017 to USD 9.88 billion by 2022. Some of the primary driving factors for the market are the rising need for AI-based solutions and the expansion of data creation.

Machine Learning (ML) software is predicted to have a bigger market share and expand at a faster rate. The AI managed service is predicted to expand at a faster rate than the other services, and it will be a bigger contributor overall. Because there are two ways to implement AI platforms: cloud and on-premises, the managed service is considered to be increasing quicker. Cloud-based solutions provide a wide range of flexible AI platform options. Forecasts and prescriptive models are predicted to have the biggest market share in the application sector, while text recognition is expected to expand at the fastest CAGR throughout the forecast period.

COMPETITIVE LEADERSHIP MAPPING TERMINOLOGY

The competitive leadership mapping section provides information regarding key vendors offering best Artificial Intelligence (AI) platform and outlines the findings and analysis as well as rates them accordingly based on vendor performance within each evaluation criteria. The evaluation criteria are based on 2 broad categories, namely, Product Maturity and Company Maturity. Each category encompasses various parameters on the basis of which Artificial Intelligence platform vendors are evaluated.

Parameters considered under Product Maturity include breadth and depth of product offering, product features & functionality, focus on product innovation, product differentiation and impact on customer value, and product quality & reliability.

Parameters considered under Company Maturity include geographic footprint/presence in emerging markets, breadth of applications served, channel strategy and fit, the effectiveness of organic growth strategy, and mergers & acquisitions strategy.

Top Visionary Leaders in Artificial Intelligence platform 

Microsoft

Microsoft offers AI platform services and tools to aid developers in the development of AI-powered models. Data science tools for rapidly building and operationalizing AI products and services, as well as ready-to-use AI services, are part of the Microsoft AI platform. The Microsoft AI platform provides developers and data scientists with a full range of customized AI Services, enterprise-grade AI Infrastructure, and contemporary AI Tools to help them build future-ready applications.

Google

Machine learning, data analytics, and data storage are among the cloud computing capabilities offered by Google Cloud Platform. The platform delivers a secure and cost-effective infrastructure as well as data and analytics capabilities to help companies produce better products. Google's Cloud ML Engine allows developers to design machine learning models for any quantity of data. The Google Cloud ML Engine provides managed services that serve as a platform for model building and prediction, as well as infrastructure replacement.

IBM

IBM is a key player in deep learning research and development, having spent much in the field. Businesses may use the IBM Watson bundle to integrate AI into their apps while also aiding with cloud data management. To have successful conversional partners, IBM Watson has a wide variety of language processing tools. Watson provides an automated predictive analytic solution that reveals the driving results automatically.

SAP

The SAP Leonardo Machine Learning platform provides a centralized infrastructure for building and maintaining intelligent applications. It is built on the SAP Cloud Platform and features machine learning capabilities to assist companies in discovering connections and patterns in their data. It consists of services that allow people to access and learn from data. It also enables the creation of corporate apps with intelligent features without the requirement for data science expertise.

Qualcomm

Qualcomm AI Platform was designed with the goal of bringing machine learning to mobile devices. The platform offers a variety of smartphone, camera, and virtual and augmented reality (VR/AR) activities. To eliminate the requirement for a network or Wi-Fi connection, Qualcomm is working on integrating AI technology into a range of devices, including robots and automobiles. Furthermore, Qualcomm Research was formed in the Netherlands, demonstrating the company's continuing efforts in AI R&D.

Amazon

The Amazon machine learning service reduces the need to grasp challenging technology and machine learning methodologies, as well as offers visualization tools and wizards to help with model construction. By offering visualization tools and wizards to help in the creation of machine learning models, it eliminates the need to understand difficult technology and machine learning methodology.

Salesforce

The Salesforce Einstein package contains data modelling, preparation, and infrastructure activities that may be leveraged to enhance predictive models and applications. By making picture identification and natural language processing capabilities available to customers, the Einstein platform services lay the groundwork for creating AI-driven apps. Marketers may examine the target audience, content, and channels while developing campaigns with Marketing Cloud Einstein capabilities like Predictive Scoring, Predictive Audiences, and Automated Send-time Optimization.

Intel

Intel has made investments in startups in order to boost its AI platform's technological capabilities. Apart from investments, Intel has bolstered its Artificial Intelligence Platform through acquisitions. By utilizing such methodologies, Intel is seeking to retain a competitive position in AI platform technologies such as deep learning, neural networks, and machine learning (ML). The Intel Nervana Platform is designed to serve as the foundation for AI systems that are highly efficient. The platform is intended to be easy and quick to use.

Top Dynamic Differentiators in Artificial Intelligence Platform

HPE

HPE unveiled hardware, services, and software focused on assisting research institutes and businesses in creating insights from huge volumes of data using high-performance computing and AI technology. The HPE C3 AI Suite is a collection of services and capabilities that enables AI applications to be delivered more quickly than using previous methods. Data scientists and application developers may use the C3 model-driven architecture, as well as a set of data integration, management, and processing capabilities, time-series services, AI and model management, and a security framework, to deliver AI at scale.

Infosys

To boost the productivity of its projects, Infosys is focusing on implementing the software automation platform, as well as AI-based automation approaches. Many of Infosys' clients benefit from the Mana AI platform, which helps them achieve efficiency and automation. The Infosys AI platform Nia is made up of three main components: a data platform, and automation platform, and a knowledge platform, as well as AI capabilities including machine learning, data analytics, and robotic process automation.

Wipro

Through innovation, research, and investments, Wipro is concentrating on AI platform technology. To differentiate oneself in the IT services industry, Wipro is focusing on AI initiatives. Wipro HOLMES aims to create the framework for cognitive process automation, knowledge virtualization, predictive systems, digital virtual assistants, robots, drones, and digital virtual agents. Natural language processing, machine learning, semantic ontologies, deep learning, genetic algorithms, knowledge modelling, and pattern recognition are among the technologies included in the platform, which cut costs while improving the experience, efficiency, and automation.

Top Innovators in Artificial Intelligence Platform

SAS

SAS combines artificial intelligence into its software to give organizations more intelligent, automated solutions that help them boost productivity and explore new prospects. SAS Visual Data Mining and Machine Learning is a cutting-edge technology that combines complex analytics, data preparation, visualization, model assessment, and model deployment in one convenient location. SAS AI technologies provide smarter, automated solutions. It boosts your imagination and opens doors to new possibilities.

Oracle

Oracle's ready-to-build AI platform provides a set of cloud services enabling data scientists and application developers to quickly design, train, deploy, and manage AI-powered applications. Its ready-to-use AI cloud apps with cognitive capabilities aid in achieving better business outcomes. It provides a comprehensive set of cloud services for developing, deploying, and managing AI-powered systems. Machine learning is working behind the scenes to automate security patches and backups, as well as enhance database query speed, with ready-to-use Oracle Autonomous Database solutions.

Absolutdata

Absolutdata provides the NAVIK AI platform, which serves as a foundation for developing AI-enabled products and services. It is a platform that allows improved decision-making through the combination of analytics, data, and technology. The service provides superior decision-making skills to the marketing and sales teams. NAVIK Converter 2. 0 is an improved version of Absolutdata's NAVIK Converter that includes enhanced analytics and machine learning to assist marketers with campaign creation.

Ayasdi

Ayasdi's cutting-edge machine intelligence platform combines automation, machine learning, and topological data analysis to make extracting knowledge from even the largest and most complex data sets as simple as possible, while also enabling the deployment of intelligent, AI-based applications across the enterprise. Ayasdi is striving to extend the application of artificial intelligence in a range of businesses. In order to introduce its AI platform in the healthcare and finance industries, Ayasdi teamed with Deloitte.

Top Emerging Companies in Artificial Intelligence Platform

Rainbird

To improve your decision-making and client experiences, the Rainbird platform uses AI-powered automation. In a number of industries, including healthcare, financial services, retail, and manufacturing, the Rainbird platform allows improved decision-making. As with human conversations, the Rainbird artificial intelligence engine guarantees that future queries are evaluated in context.

Kasisto

Kasisto is a conversational AI platform that allows users to build virtual assistants and bots that provide personalized, pleasant, and intelligent experiences across different channels. On the mobile, web, messaging platforms, and voice-enabled devices, the KAI conversational AI platform enables virtual assistants and bots. It creates intelligent discussions with clients that fulfill requests, solve issues, and anticipate their requirements.

DataRobot

The DataRobot automated machine learning platform combines knowledge, experience, and best practices to give machine learning projects unrivaled levels of automation and ease of use. In a fraction of the time, the DataRobot platform provides extremely accurate prediction models. It analyses the training data and recommends the best model type automatically. DataRobot transforms characteristics for best outcomes by executing operations such as one-hot encoding, missing value imputation, text mining, and standardization.

BigML

BigML's cloud-based Machine Learning solution is easy to use, integrate, and put into action right now. BigML's Machine Learning algorithms handle real-world challenges throughout your business utilizing a single, standardized framework. In a number of sectors, it offers a wide range of predictive applications. It adjusts resources automatically to meet computational demands in a cost-effective way while protecting end-users from infrastructure issues.

Vital AI

Vital AI builds AI applications that intelligently automate business processes for greater efficiency and create innovative communication for people, devices, and data using the Haley Software Development Kit (SDK), an intelligent agent platform with various AI algorithms. This set of tools is capable of maintaining and deploying intelligent data models across application architectures.

Top 10 Artificial Intelligence Platform:

1. MICROSOFT Azure AI
2. GOOGLE Cloud Machine Learning Engine
3. IBM Watson
4.  AMAZON ML platform services
5. SAP Leonardo Machine Learning
6. INTEL Nervana Platform
7. Salesforce Einstein suite
8. Qualcomm 
9. HPE C3 AI Suite
10. SAS 

Benefits of Artificial Intelligence Platform

Gains in efficiency and productivity

Two of the most frequently mentioned advantages of using AI in the workplace are increased efficiency and productivity. The Artificial Intelligence Platform can complete jobs at a speed and scale that people cannot. Simultaneously, by eliminating such activities from the obligations of human employees, AI empowers those individuals to focus on higher-value jobs that technology cannot. This enables businesses to reduce the expenses of completing monotonous, repeated operations that can be automated while still utilizing the talent of their human resources.

Improved business speed

Artificial Intelligence promotes faster development cycles and reduces the time it takes to get from design to commercialization, resulting in a higher, and more rapid, return on investment in research funds.

New competencies and a broader business model

Executives may utilize AI to expand their company models. Data and analytics deployment in the company gives up new options for organizations to compete in many fields.

Customer service that is better

The AI-Powered Enterprise can learn more about the demands of its customers, resulting in more tailored and individualized interactions between businesses and their customers.

Improved surveillance

Organizations may adopt near-instantaneous monitoring capabilities that can alert them to concerns, propose action, and, in some circumstances, even start a reaction, thanks to AI's ability to take in and interpret huge volumes of data in real-time.

A few uses of Artificial Intelligence platform -

• Speech to text conversion
• Spam filtering
• Image classification and tagging, for example, for parental advise
• Media object detection
• Customer behavior analysis
• Network intrusion detection
• Recommendation systems (shopping, music, friends, etc.)
• Detecting terrorism funding (among millions of transactions every day)
• Detecting faces in a photo, video, or other images
• Stock price movement forecast

Market Dynamics

Drivers

The proliferation of data generation, increasing demand for AI-based solutions, increasing operational efficiency and lowering costs, and the growing desire to improve customer experience are the main driving drivers for the artificial intelligence platform market.

The following are some significant drivers for the artificial intelligence platform: The need for AI-based solutions is increasing. As the need for automation and optimization of corporate processes grows, more companies are turning to AI-based solutions.

The automobile and IT industries are driving development. The artificial intelligence platform market is expected to grow in the coming years due to the trend of industries moving toward automation to boost productivity.

In addition, the market for artificial intelligence platforms is being driven by the proliferation of big data and the desire for intelligent virtual assistants.

Restraints

The Artificial Intelligence Platforms Market is hampered by a number of factors. Some of the barriers to the growth of the AI platform market include a lack of skilled employees and data privacy concerns in emerging economies. These variables contribute to the danger of failing to perform in a competitive business environment, necessitating the use of AI platform solutions. In addition, the artificial intelligence platform industry will be challenged by its inability to guard against new types of threats.

Opportunity

The artificial intelligence platform industry has risen in response to a shift in client preferences toward convenience and luxury. Moreover, numerous firms are predicted to utilize the artificial intelligence platform market to boost their consumer services. Furthermore, the growing demand for intelligent business processes and end-user innovations will provide ample opportunity for the artificial intelligence platform market to grow.

Threats

The emergence of data privacy concerns will pose a significant threat to the artificial intelligence platform business. AI applications raise a number of safety and security concerns. In AI solutions, there is a high risk of information leakage, which can lead to data misuse or manipulation. Also, customers are concerned about the lack of openness about the usage and processing of data. Access control, identity management, risk management, regulatory and legislative compliance, auditing, and logging are all areas where these concerns might have legal and security repercussions.

360 Quadrants Research Methodology

Top Companies in Artificial Intelligence Platform will be rated using the following methodology -

1. A highly experienced team of researchers and senior analysts conduct extensive research to generate a list of vendors (competitors).
2. A patent-pending algorithm is used to collect inputs from key stakeholders—industry experts, buyers, vendors, and 360Quadrants analysts—based on criteria for Product Maturity and Company Maturity.

1. Criteria under Product Maturity include breadth and depth of product/service offering, product features and functionalities, product differentiation, and their impact on customer value.
2. Criteria under Company Maturity include geographical footprint, partner ecosystem, financial stability, and client coverage or sector footprint.

3. Approximately 25+ in-depth parameters will be considered for research for the Artificial Intelligence Platform market. These parameters will be updated every 6 months to ensure the latest developments are taken into consideration.
4. A weight is assigned to each stakeholder based on information gathered pertaining to the above criteria as well as inputs from stakeholders. These inputs follow the order of priority given below:

1. Buyers
2. Industry Experts
3. 360Quadrants Analysts
4. Vendors (Competitors)

5. The inputs are analyzed, and a final rating is assigned to each vendor (competitor).
6. After the finalization of ratings, each vendor is placed in the most relevant quadrant based on their score.

USER FAQs

What are the most common artificial intelligence systems?

Natural language generation, speech recognition, virtual agents, text analysis, machine learning platforms, AI optimized hardware, emotion recognition, image decision management, deep learning platforms, biometrics, robotics automation, cyber defense, compliance, knowledge worker assistance, content creation, recognition, and marketing automation are just a few of the technologies that are being developed.

What are the AI platform market's applications?

Chatbots, speech recognition, text recognition, face identification, and sentiment analysis are all examples of predictive and prescriptive models.

What is the significance of AI?

Accessibility of AI and analytics tools is critical with the development of citizen data scientists. By offering tools for managing the end-to-end machine learning life cycle, AI platforms assist to democratize and productize ML models. They do it by using a SaaS interface that is meant to make user interactions easier for non-technical individuals. Without these platforms, AI's impact would be limited because a larger portion of resources would be spent on developing and maintaining models.

What does artificial intelligence have in store for the future?

Environment monitoring and reaction for climate change objectives, automated transportation, taking over risky occupations, robots working alongside people, enhanced senior care, cyborg (organic/bio-mechanic) creatures.