Embedded AI Market Report 2023-2028: Growing Demand for Intelligent and Autonomous Systems for a Personalized Experience and Increasing Advancements in AI and ML Technologies Fuels Growth

DUBLIN, July 17, 2023 /PRNewswire/ -- The "Embedded AI Market by Offering (Hardware, Software, Services), Data Type (Numerical Data, Categorical Data, Image & Video Data), Vertical (Automotive, Manufacturing, Healthcare & Life Sciences, Telecom), and Region - Global Forecast to 2028" report has been added to ResearchAndMarkets.com's offering.

The Embedded AI market is projected to grow from USD 9.4 billion in 2023 to USD 18.0 billion by 2028 at a compound annual growth rate (CAGR) of 14.0%

The market is anticipated to grow due to the growing demand for intelligent and autonomous systems for a personalized experience and increasing advancements in AI and ML technologies for better and smart decisions.

By offering the hardware segment to hold the largest market size during the forecast period

The hardware segment of the embedded AI market is growing rapidly due to the increasing demand for AI-powered devices and applications. Embedded AI hardware plays a critical role in the market by providing the necessary computing power and specialized capabilities to support AI applications directly on embedded systems.

Embedded AI hardware can be customized and integrated into specific embedded systems, ensuring seamless compatibility and efficient utilization of resources. This allows hardware vendors and system designers to tailor the AI hardware to meet the specific requirements of the target application, achieving optimal performance and functionality.

By vertical, the healthcare and life sciences segment to have the highest CAGR during the forecast period

Across the healthcare and life science sector, embedded AI is used in medical devices and equipment for diagnostics, patient monitoring, personalized medicine, and data analysis.

AI algorithms embedded in medical devices help in the early detection of diseases, decision support for clinicians, and remote patient monitoring. Embedded AI adoption in the healthcare and life sciences industry has grown rapidly, driven by the potential to improve patient outcomes, enhance efficiency, and enable personalized medicine.

North America to witness fastest growing market size during the forecast period

North America is experiencing significant technological growth in the Embedded AI market, driven by various factors shaping the landscape of intelligent and connected devices.

Embedded AI adoption in North America is gaining momentum across industries, driven by technological advancements, the rise of IoT, a supportive ecosystem, and increasing awareness of its benefits. The region is witnessing a proliferation of intelligent edge devices and innovative applications that leverage Embedded AI, contributing to the transformation of various

Competitive landscape

In-depth assessment of market shares, growth strategies, and service offerings of leading players such as Google (US), IBM (US), Microsoft (US), AWS (US), NVIDIA (US), Intel (US), Qualcomm (US), Arm (UK), AMD (US), MediaTek (Taiwan), Oracle (US), among others in the Embedded AI market strategies. 

Key Attributes:

Premium Insights

• Proliferation of Connected Devices and IoT Ecosystem for Effective Communications to Drive Market Growth
• Embedded AI Market to Witness Minor Decline in Y-O-Y Growth in 2023
• Numeric Data Segment to Grow at Highest CAGR During Forecast Period
• Hardware Segment and Automotive Segment to Hold Largest Market Shares in North America in 2023
• North America to Hold Largest Market Share in 2023

Market Dynamics

Drivers

• Growing Demand for Intelligent and Autonomous Systems
• Increasing Advancements in AI and Ml Technologies for Better and Smart Decisions
• Proliferation of Connected Devices and IoT Ecosystem for Effective Communications
• Rising Use of Embedded AI for Industry-Specific Applications

Restraints

• Data Privacy and Security Concerns
• Shortage of Skilled and Talented Workforce

Opportunities

• Rising Demand for More Powerful and Energy-Efficient Processors
• Integration with Cloud-Based AI Services for Better Scalability

Challenges

• Inadequate Computational Resources and Model Optimization
• High Infrastructure Costs with Lower Roi

Case Study Analysis

• Case Study 1: Edge Impulse Helped Oura Ring Provide Enhanced Analysis of Sleep Patterns and User Readiness
• Case Study 2: Nvidia Jetson Tx2 Nx Offered Accurate Fall Detection by Deploying Novi Smart Lamp
• Case Study 3: Rolloos Actively Monitored Red Zones in Real Time by Deploying Nvidia's Acceleration Toolkits
• Case Study 4: Mercedes-Benz Consulting Optimized Dealership Layout Using Modcam Store Analytics
• Case Study 5: Tvgh Achieved Real-Time AI Inference by Utilizing Aetina Edge AI Starter Package

Key Components of Embedded AI Architecture

• Model Module
• Data Module
• Computing Power Module

Technology Analysis

• Key Technology
• Ml and Deep Learning
• Data Science
• Edge Computing
• IoT
• Computer Vision
• Neural Networks
• Tensorflow Lite

Adjacent Technology

• Signal Processing
• Data Mining and Predictive Analysis
• Blockchain
• 5G

Impact of Embedded AI on Business Modernization

• Business Process and Task Automation
• Advanced Predictive Analytics
• Intelligent Decision-Making
• Streamlined Customer Experience

Business Model Analysis

• Business Models for Hardware Vendors
• Business Models for Software Providers
• Business Models for Service Providers

Company Profiles

Key Players

• Google
• IBM
• Microsoft
• Aws
• Nvidia
• Intel
• Qualcomm
• Arm
• Amd
• Mediatek
• Oracle

Other Key Players

• Salesforce
• Nxp
• Lattice Semiconductor
• Octonion
• Neuropace
• Siemens
• Hpe
• Luis Technology
• Code Time Technologies
• Hisilicon
• Vectorblox
• Au-Zone Technologies
• Stmicroelectronics
• Sensetime

Startup/Sme Profiles

• Edge Impulse
• Perceive
• Eta Compute
• Sensiml
• Syntiant
• Graphcore
• Sima.AI

For more information about this report visit https://www.researchandmarkets.com/r/yrccp3

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