AI Analytics Market Size, Share, Opportunities, And Trends By Technology Type (Machine Learning, Deep Learning, Other), By Deployment (Cloud, On-Premise), By End-User (BFSI, Retail, Healthcare, Others), And By Geography - Forecasts From 2024 To 2029

The AI analytics market is anticipated to expand at a high CAGR over the forecast period.

AI analytics, or artificial intelligence analytics, is the application of artificial intelligence (AI) and machine learning techniques to analyze data, extract insights, and make predictions. It combines sophisticated analytics skills with AI algorithms to handle vast and complicated information, identify patterns, trends, and correlations, and create actionable insights to help with decision-making and business results.

AI analytics starts with collecting, purifying, and transforming raw data from many sources, including databases, sensors, social media, and IoT devices, into an analysis-ready format. The three most prevalent machine learning methodologies used in AI analytics are supervised learning, unsupervised learning, and reinforcement learning.

AI analytics has applications in a variety of sectors and domains, including sales and marketing, finance, healthcare, manufacturing, transportation, retail, energy, and more. It enables businesses to optimize operations, improve customer experiences, reduce risks, and drive innovation.

Market Drivers

• Emergence of Big Data and Cloud Computing fueling the AI analytics market growth

Big data and cloud computing technologies have transformed data storage, processing, and analysis. Cloud-based AI analytics tools are scalable, flexible, and cost-effective, allowing organizations of all sizes to leverage AI for data analysis without making major upfront expenditures.

Applications such as Amazon Lightsail, a solution that serves a variety of sectors, offer simple cloud resources for web apps and websites. It provides simplified services like instances, containers, databases, and storage. Lightsail may be used to create websites or apps using pre-configured blueprints such as WordPress, Prestashop, or LAMP, host static content, link material to worldwide audiences, and set up Windows Business servers.

• Advancements in AI and machine learning are fueling the AI analytics market growth

Ongoing advancements in artificial intelligence and machine learning technologies, including deep learning, natural language processing (NLP), and computer vision, enhance the capabilities of AI analytics solutions. These technologies enable more accurate predictions, faster analysis, and deeper insights, driving adoption across industries.

In various industries, there is a range of products that serve different purposes. One such product is the IBM Cloud Pak is a modular collection of integrated software components for data analysis, organization, and administration. It is available for self-hosting or as a managed service on the IBM Cloud. It has a user-friendly interface, simple installation, consistent performance, and exceptional longevity. Another notable product is Tableau, an analytics and data visualization software that allows users to engage with the data analytics tools. These tools enable data visualization and analytics, allowing reports to be shared inside a browser or incorporated into an application. All of this may take place when Tableau is running in the cloud or on-premise.

Market Restraints

• Talent Shortage and Skills Gap is hampering the market growth

Shortage of competent data scientists, machine learning engineers, and AI professionals with the necessary knowledge to create and deploy AI analytics solutions. To address the talent shortfall and skills gap in AI and analytics, investments in education, training, and workforce development are required. A lack of trained people in AI and analytics might stymie innovation and the development of sophisticated AI analytics solutions. Organisations may have delays in implementing AI analytics programmes due to difficulties in locating and recruiting suitable staff. By investing in talent development and fostering a culture of learning and innovation, organizations can overcome talent shortages and drive the growth and adoption of AI analytics solutions in the market.Top of Form

The AI analytics market is segmented based on different technologies

The AI analytics market can be segmented based on different technologies, such as machine learning, deep learning, and Natural Language Processing. These categories have a crucial role in enabling data analysis, insights generation, and decision-making.

Machine learning is a core concept in AI analytics that allows computers to learn from data and make predictions or judgements without requiring explicit programming. NLP is a field of artificial intelligence that enables computers to understand, interpret, and produce human language. Text analytics, sentiment analysis, chatbots, language translation, and speech recognition are all applications of natural language processing. Deep learning is a type of machine learning that uses artificial neural networks with numerous layers to learn from enormous quantities of data. Deep learning algorithms are used to perform tasks including image identification, object detection, audio recognition, and natural language comprehension.

North America region is anticipated to hold a significant share of the AI analytics market.

The United States is the North American region's leading investor in artificial intelligence. As the investment and business communities have a better understanding of AI, the investment and financing market will become more rational, as investment and financing frequency declines and investment volumes rise. Following rounds of intra-industry rivalry, technology businesses and applied application industries such as healthcare, education, and self-driving startups continue to favour premier AI schools. The majority of the corporations spending extensively on AI are based outside of the United States. The United States is home to major technology companies such as Google LLC, IBM, Microsoft, and Amazon Web Services, Inc. They also spend extensively on AI research and development services. These investments in AI technology will help to drive regional market growth.

Key Developments

• January 2024 – Open Texted, the information provider, announced the introduction of Cloud Editions 24.1, which included the newest Open-Text aviator technologies. Open-Text Aviator drove numerous AI use cases by allowing safe information management and governance across knowledge bases without requiring clients to relocate their data.
• August 2023 – Google incorporated Duet AI, a generative AI assistant, into its data management and analytics systems (Big Query and Looker). This connection enables users to utilize Duet AI to get insights from data, build interactive dashboards, and automate processes.
• May 2023 – Salesforce revealed new real-time data and AI capabilities in the world's first CRM. Sales teams may increase productivity and growth by leveraging generative AI-powered emails, qualified prospects, and intelligent sales planning.

Company Products-

• Kyndryl Data and AI services – Kyndryl’s Data and AI services may assist organizations in addressing challenging data management and AI issues. Our rapid approach to data and AI transformation delivers agile, integrated, and adaptable solutions for a variety of organizational data estates. Consolidate monitoring and generate exponential value with a self-service platform for consuming, managing, and optimizing data and insights. Implement AI at scale and build an end-to-end data supply chain to ensure smooth data processing and analysis.
• OpenText AI & Analytics Services – OpenText AI & Analytics Services integrates data, people, and technology to provide meaningful insights. The skilled team delivers business and analytics solutions that add immediate benefit while also assisting organizations in preparing for future demands. It enables business and analytics solutions to operationalize goods, services, and solutions in Machine Learning, Natural Language Processing, Expert Systems, and Speech Recognition.

Market Segmentation

• By Technology Type
  • Machine Learning
  • Deep Learning
  • Other
• By Deployment
  • Cloud
  • On-Premise
• By End-User
  • BFSI
  • Retail
  • Healthcare
  • Others
• By Geography
  • North America
    • USA
    • Canada
    • Mexico
  • South America
    • Brazil
    • Argentina
    • Others
  • Europe
    • Germany
    • France
    • UK
    • Spain
    • Others
  • Middle East and Africa
    • Saudi Arabia
    • UAE
    • Israel
    • Others
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Indonesia
    • Taiwan
    • Others

1. INTRODUCTION

1.1. Market Overview

1.2. Market Definition

1.3. Scope of the Study

1.4. Market Segmentation

1.5. Currency

1.6. Assumptions

1.7. Base, and Forecast Years Timeline

1.8. Key benefits to the stakeholder

2. RESEARCH METHODOLOGY

2.1. Research Design

2.2. Research Process

3. EXECUTIVE SUMMARY

3.1. Key Findings

3.2. Analyst View

4. MARKET DYNAMICS

4.1. Market Drivers

4.2. Market Restraints

4.3. Porter’s Five Forces Analysis

4.3.1. Bargaining Power of Suppliers

4.3.2. Bargaining Power of Buyers

4.3.3. Threat of New Entrants

4.3.4. Threat of Substitutes

4.3.5. Competitive Rivalry in the Industry

4.4. Industry Value Chain Analysis

4.5. Analyst View

5. AI ANALYTICS MARKET BY TECHNOLOGY TYPE

5.1. Introduction

5.2. Machine Learning

5.2.1. Market opportunities and trends

5.2.2. Growth prospects

5.2.3. Geographic lucrativeness 

5.3. Deep Learning

5.3.1. Market opportunities and trends

5.3.2. Growth prospects

5.3.3. Geographic lucrativeness 

5.4. Others

5.4.1. Market opportunities and trends

5.4.2. Growth prospects

5.4.3. Geographic lucrativeness 

6. AI ANALYTICS MARKET BY DEPLOYMENT

6.1. Introduction

6.2. Cloud

6.2.1. Market opportunities and trends

6.2.2. Growth prospects

6.2.3. Geographic lucrativeness 

6.3. On-Premise

6.3.1. Market opportunities and trends

6.3.2. Growth prospects

6.3.3. Geographic lucrativeness 

7. AI ANALYTICS MARKET BY END-USER

7.1. Introduction

7.2. BFSI

7.2.1. Market opportunities and trends

7.2.2. Growth prospects

7.2.3. Geographic lucrativeness 

7.3. Retail

7.3.1. Market opportunities and trends

7.3.2. Growth prospects

7.3.3. Geographic lucrativeness 

7.4. Healthcare

7.4.1. Market opportunities and trends

7.4.2. Growth prospects

7.4.3. Geographic lucrativeness 

7.5. Others

7.5.1. Market opportunities and trends

7.5.2. Growth prospects

7.5.3. Geographic lucrativeness 

8. AI ANALYTICS MARKET BY GEOGRAPHY

8.1. Introduction

8.2. North America

8.2.1. By Technology Type 

8.2.2. By Deployment

8.2.3. By End-user

8.2.4. By Country

8.2.4.1. United States

8.2.4.1.1. Market Trends and Opportunities

8.2.4.1.2. Growth Prospects

8.2.4.2. Canada

8.2.4.2.1. Market Trends and Opportunities

8.2.4.2.2. Growth Prospects

8.2.4.3. Mexico

8.2.4.3.1. Market Trends and Opportunities

8.2.4.3.2. Growth Prospects

8.3. South America

8.3.1. By Technology Type 

8.3.2. By Deployment

8.3.3. By End-user

8.3.4. By Country

8.3.4.1. Brazil

8.3.4.1.1. Market Trends and Opportunities

8.3.4.1.2. Growth Prospects

8.3.4.2. Argentina

8.3.4.2.1. Market Trends and Opportunities

8.3.4.2.2. Growth Prospects

8.3.4.3. Others

8.3.4.3.1. Market Trends and Opportunities

8.3.4.3.2. Growth Prospects

8.4. Europe

8.4.1. By Technology Type 

8.4.2. By Deployment

8.4.3. By End-user

8.4.4. By Country

8.4.4.1. Germany

8.4.4.1.1. Market Trends and Opportunities

8.4.4.1.2. Growth Prospects

8.4.4.2. France

8.4.4.2.1. Market Trends and Opportunities

8.4.4.2.2. Growth Prospects

8.4.4.3. United Kingdom

8.4.4.3.1. Market Trends and Opportunities

8.4.4.3.2. Growth Prospects

8.4.4.4. Spain

8.4.4.4.1. Market Trends and Opportunities

8.4.4.4.2. Growth Prospects

8.4.4.5. Others

8.4.4.5.1. Market Trends and Opportunities

8.4.4.5.2. Growth Prospects

8.5. Middle East and Africa

8.5.1. By Technology Type 

8.5.2. By Deployment

8.5.3. By End-user

8.5.4. By Country

8.5.4.1. Saudi Arabia

8.5.4.1.1. Market Trends and Opportunities

8.5.4.1.2. Growth Prospects

8.5.4.2. UAE

8.5.4.2.1. Market Trends and Opportunities

8.5.4.2.2. Growth Prospects

8.5.4.3. Israel

8.5.4.3.1. Market Trends and Opportunities

8.5.4.3.2. Growth Prospects  

8.5.4.4. Others

8.5.4.4.1. Market Trends and Opportunities

8.5.4.4.2. Growth Prospects

8.6. Asia Pacific

8.6.1. By Technology Type 

8.6.2. By Deployment

8.6.3. By End-user

8.6.4. By Country

8.6.5. China

8.6.5.1. Market Trends and Opportunities

8.6.5.2. Growth Prospects

8.6.6. Japan

8.6.6.1. Market Trends and Opportunities

8.6.6.2. Growth Prospects

8.6.7. India

8.6.7.1.1. Market Trends and Opportunities

8.6.7.1.2. Growth Prospects

8.6.8. South Korea

8.6.8.1.1. Market Trends and Opportunities

8.6.8.1.2. Growth Prospects

8.6.9. Indonesia

8.6.9.1.1. Market Trends and Opportunities

8.6.9.1.2. Growth Prospects

8.6.10. Taiwan

8.6.10.1.1. Market Trends and Opportunities

8.6.10.1.2. Growth Prospects

8.6.11. Others

8.6.11.1. Market Trends and Opportunities

8.6.11.2. Growth Prospects

9. COMPETITIVE ENVIRONMENT AND ANALYSIS

9.1. Major Players and Strategy Analysis

9.2. Market Share Analysis

9.3. Mergers, Acquisition, Agreements, and Collaborations

9.4. Competitive Dashboard

10. COMPANY PROFILES

10.1. Kyndryl Inc.

10.2. Capgemini

10.3. Open Text Corporation

10.4. Polestar Insight Inc.

10.5. Nagarro

10.6. Deloitte

10.7. Fractal Analytics Inc.

10.8. Altair Engineering Inc.

10.9. Adastra.

10.10. Sightspectrum

Kyndryl Inc.

Capgemini

Open Text Corporation

Polestar Insight Inc.

Nagarro

Deloitte

Fractal Analytics Inc.

Altair Engineering Inc.

Adastra.

Sightspectrum