AI (Artificial Intelligence) In Simulation Market Size, Share, Opportunities, And Trends By Technology (Simulation Modeling, Predictive & Prescriptive Analytics, Platform As A Service (PaaS), Others), By Deployment (Cloud, On-Premise), By End-User (Automotive, Infrastructure, Manufacturing, Education, Others), And By Geography - Forecasts From 2024 To 2029

  • Published : Mar 2024
  • Report Code : KSI061616746
  • Pages : 146

The artificial intelligence in simulation market is projected to show steady growth during the forecast period.

AI simulation involves the integration of AI and simulation technologies to create AI agents and virtual environments. AI refers to the replication of human intelligence processes using machines, particularly computer systems. The development of computer programs that mimic the reasoning capabilities of the human brain. Some of the common simulation models are probabilistic models that involve making predictions about future events, such as stock prices or weather conditions, by utilizing calculations and probabilities. Agent-based models concentrate on individual "agents" within a system and simulate intricate interactions like shopkeepers and customers. Monte Carlo models, conduct multiple simulations to statistically evaluate potential outcomes. System dynamics models depict complex systems with interconnected elements and analyze how alterations in one part can impact others. Advancements in simulation technology, demand for predictive analysis, enhancing efficiency, and reducing cost are driving AI in the simulation market growth.

Market Drivers:

  • Advancements in simulation technology enhance AI in simulation market growth.

Simulations are being utilized more and more to enhance processes, improve designs, and cut down on expenses. By conducting tests in virtual settings prior to actual production, simulations aid in forecasting product performance, pinpointing manufacturing challenges, and providing a safe training environment for workers. Growing emphasis on product optimization, coupled with favorable efforts to promote industrial automation, has resulted in technological advancement in simulation technology. For instance, Ansys 2023 Release 2 drives innovation in the industry through revolutionary simulation technologies. The Ansys Discovery software is a simulation-driven 3D design tool utilized by engineers and designers for the creation and analysis of 3D models within a virtual setting. Toyota has revealed additional advancements in its software system, THUMS (Total Human Model for Safety), which is designed to simulate the human body's response in automobile accidents in order to enhance vehicle safety.

  • Demand for predictive insights is steadily increasing propels AI in simulation market growth.

The requirement for AI in simulation arises necessity for anticipatory understanding in diverse domains. AI scrutinizes intricate data from simulations to forecast forthcoming patterns, evaluate hazards, and enhance strategies, thereby enhancing decision-making and achieving superior results. The advancement of simulation technology is driven by the increasing focus on advanced computing systems and complex algorithms, as well as the favorable initiatives to promote predictive insights. For instance, Graph Cast by Google DeepMind provides forecasts with a remarkable level of detail, operating at a high resolution of 0.25 degrees longitude/latitude (equivalent to 28km x 28km at the equator). The model's predictions encompass five Earth-surface variables at each grid point, such as temperature, wind speed and direction, and mean sea-level pressure. Additionally, it forecasts six atmospheric variables at each of the 37 altitude levels, including specific humidity, wind speed and direction, and temperature.

  • Boosting efficiency and cutting down costs in the manufacturing sector enhance AI in simulation market growth.

Businesses are always searching for methods to optimize operations and decrease costs. AI-powered simulations assist in the analysis of procedures to identify inefficiencies, predict potential problems, and reduce the need for costly physical prototypes. Consequently, this leads to enhanced efficiency and reduced expenses. The growing AI and simulation in the manufacturing industry can be attributed to the continuous efforts to improve production processes coupled with proactive measures to promote industrial automation. For instance, in July 2023, Mercedes-Benz AG started conducting trials with ChatGPT in live operations, expediting the integration of smart tools within the MO360 digital production ecosystem, which was initially launched in 2020. In order to enhance the processing of production data, such as those related to quality control, ChatGPT will serve as a versatile, voice-activated interface for production staff.

North America is anticipated to grow gradually.

North America is anticipated to account for a significant share of the AI simulation market as major technology companies in the region are leading the way in AI research and development, establishing a strong presence in the AI simulation market, and prioritizing the cultivation of innovation.

In October 2023, the Defence Research Advanced Research Project Agency (DARPA) announced the development of an innovative method of modeling and simulation to enhance the autonomy of different platforms, including drones and uncrewed vehicles. The objective of this fresh approach is to overcome the constraints of conventional high-fidelity simulations utilized in training autonomous systems. In May 2023, a research collaboration at Ontario Tech University aimed at the development of simulated medical training technology specifically designed for physicians located in remote areas.

Market Restraints:

  • Data bias can impact AI simulation market growth.

AI simulations are capable of acquiring knowledge from data. In cases where the data contains concealed biases, such as making judgments based on race rather than merit, the simulation could unintentionally adopt these biases and consequently make unjust decisions. As a result, incorrect or detrimental consequences may arise.

Key Development:

  • In February 2024: MicroAI introduced AIStudio, a cutting-edge data modeling platform enhanced by artificial intelligence for the future era.
  • October 2023: Altair launched Altair HyperWorks 2023, the ultimate Computer Aided Engineering (CAE) platform, offering engineers an extensive array of design and simulation products tailored for various industries such as automotive, aerospace, electronics, and beyond. With its unparalleled comprehensiveness, power, versatility, and openness, this platform empowers engineers of all proficiency levels.
  • October 2023: Foxconn partnered with NVIDIA to integrate the latter’s technology and aimed at facilitating diverse applications, including the digitalization of manufacturing and inspection procedures, the progression of AI-powered electric vehicle and robotics systems, and the expansion of language-based generative AI services.
  • February 2023: AVEVA, a well-known international leader in industrial software, launched its latest software, AVEVA Predictive Analytics. This state-of-the-art software is specifically developed to meet the predictive monitoring requirements of diverse industrial sectors, such as oil and gas, power, chemicals, mining and minerals, and manufacturing.

Company Products:

  • Altair OptiStruct: Altair OptiStruct, an integral part of the Altair HyperWorks suite, is a robust software for structural analysis and optimization. It is extensively utilized by engineers to examine the performance of structures under different loads and conditions, as well as to enhance designs in terms of weight, strength, and other essential performance criteria.
  • HxGN Smart Build™ Insight: Hexagon (HxGN) offers Smart Build Insight, which is a cutting-edge solution developed by Hexagon to enhance building design and construction by connecting the office and the field. It achieves this by harnessing digitalization across the entire construction process.

Segmentation

  • By Technology
    • Simulation Modeling
    • Predictive & Prescriptive Analytics
    • Platform as a Service (PaaS)
    • Others
  • By Deployment
    • Cloud
    • On-Premise
  • By End-User
    • Automotive
    • Infrastructure
    • Manufacturing
    • Education
    • Others
  • By Geography
    • North America
      • United States
      • 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 (ARTIFICIAL INTELLIGENCE) IN THE SIMULATION MARKET BY TECHNOLOGY 

5.1. Introduction

5.2. Simulation Modeling

5.2.1. Market opportunities and trends

5.2.2. Growth prospects

5.2.3. Geographic lucrativeness 

5.3. Predictive & Prescriptive Analytics

5.3.1. Market opportunities and trends

5.3.2. Growth prospects

5.3.3. Geographic lucrativeness 

5.4. Platform as a Service (PaaS)

5.4.1. Market opportunities and trends

5.4.2. Growth prospects

5.4.3. Geographic lucrativeness 

5.5. Others

5.5.1. Market opportunities and trends

5.5.2. Growth prospects

5.5.3. Geographic lucrativeness 

6. AI (ARTIFICIAL INTELLIGENCE) IN THE SIMULATION 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 (ARTIFICIAL INTELLIGENCE) IN THE SIMULATION MARKET BY END-USER

7.1. Introduction

7.2. Automotive

7.2.1. Market opportunities and trends

7.2.2. Growth prospects

7.2.3. Geographic lucrativeness 

7.3. Infrastructure

7.3.1. Market opportunities and trends

7.3.2. Growth prospects

7.3.3. Geographic lucrativeness 

7.4. Manufacturing

7.4.1. Market opportunities and trends

7.4.2. Growth prospects

7.4.3. Geographic lucrativeness 

7.5. Education

7.5.1. Market opportunities and trends

7.5.2. Growth prospects

7.5.3. Geographic lucrativeness 

7.6. Others

7.6.1. Market opportunities and trends

7.6.2. Growth prospects

7.6.3. Geographic lucrativeness 

8. AI (ARTIFICIAL INTELLIGENCE) IN THE SIMULATION MARKET BY GEOGRAPHY

8.1. Introduction

8.2. North America

8.2.1. By Technology

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

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

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

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

8.6.2. By Deployment

8.6.3. By End-user

8.6.4. By Country

8.6.4.1. China

8.6.4.1.1. Market Trends and Opportunities

8.6.4.1.2. Growth Prospects

8.6.4.2. Japan

8.6.4.2.1. Market Trends and Opportunities

8.6.4.2.2. Growth Prospects

8.6.4.3. India

8.6.4.3.1. Market Trends and Opportunities

8.6.4.3.2. Growth Prospects

8.6.4.4. South Korea

8.6.4.4.1. Market Trends and Opportunities

8.6.4.4.2. Growth Prospects

8.6.4.5. Indonesia

8.6.4.5.1. Market Trends and Opportunities

8.6.4.5.2. Growth Prospects

8.6.4.6. Taiwan

8.6.4.6.1. Market Trends and Opportunities

8.6.4.6.2. Growth Prospects

8.6.4.7. Others

8.6.4.7.1. Market Trends and Opportunities

8.6.4.7.2. 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. AnyLogic

10.2. IBM

10.3. Altair

10.4. Sky Engine AI

10.5. Hadean

10.6. MSC

10.7. Simulation

10.8. CosmoTech


AnyLogic

IBM

Altair

Sky Engine AI

Hadean

MSC

Simulation

CosmoTech