エッジAIの世界市場

世界のエッジAIの市場規模は、2023年に168億米ドルに達し、2024～2031年の予測期間中にCAGR 20.6%で成長し、2031年には738億米ドルに達すると予測されています。

専用プロセッサやハードウェアアクセラレータなど、コンピューティングのためのエッジ技術の向上により、エッジでの処理能力が向上します。複雑なAIモデルがエッジデバイス上で効率的に開発・運用されるのは、この処理能力の向上によるもので、難しいデータ分析やリアルタイムの推論作業をより簡単に終わらせることができます。

コンピュータパワーをデータソースに近づけることで、エッジコンピューティングはデータの遅延と転送時間を劇的に短縮します。拡張現実、産業オートメーション、自律走行車など、リアルタイムで意思決定を行う必要があるAIアプリケーションにとって、この遅延時間の短縮は重要です。エッジコンピューティングは、待ち時間を短縮することでシステムパフォーマンスと顧客満足度を向上させ、AIの推論と応答時間の高速化を可能にします。

新製品を発売することでエッジAIを世界的に普及させようとする主要プレーヤーによるイニシアティブの高まりは、予測期間における世界のエッジAI市場の成長を後押しするのに役立っています。例えば、2023年07月06日、SilicomoはHailoとの提携を完了し、エッジAI製品ラインを発表しました。HailoのAIアクセラレータをSilicomの現在のエッジプラットフォームに統合することで、エッジAIアプリケーションのパフォーマンス課題に対処します。その結果、Silicomoの製品は、非常に魅力的な価格性能比で、エッジでの視覚処理とAI推論を提供することになります。

北米の組織や政府は、世界市場で競争力を高めるため、エッジAIインフラ、研究開発、調査に戦略的に投資しています。エッジAI産業が成長し、革新が進んでいるのは、企業投資、政府からの資金提供、官民パートナーシップなどのイニシアチブのおかげです。5G Americas Omdiaが実施した調査によると、北米は2023年第3四半期時点で1億7,600万件の5G接続でリードしており、これは前四半期に2,200万件の新規接続が追加されたことを意味します。

ダイナミクス

モノのインターネット（IoT）の普及拡大

ネットワークの境界では、センサー、カメラ、その他の接続デバイスがIoTデバイスに膨大な量のデータを提供しています。中央集中型のクラウドサーバーに依存することなく、エッジAIはこのデータをエッジ上で直接リアルタイムに処理・分析し、迅速な洞察とアクションを可能にします。リンクされた自動車、スマートホーム、産業オートメーションなど、数多くのモノのインターネットの用途におけるリアルタイムの応答には、低レイテンシーが求められます。このニーズに応えるため、エッジの人工知能はローカルでデータを分析することで、レイテンシを低減し、遠方のデータセンターにデータを送信することで発生する遅延なしに、迅速な意思決定を実現します。

IoTの利用は過去10年間で大幅に増加しました。IHSは、2022年までに使用されるIoTデバイスの数が、2015年の154億1,000万台から426億2,000万台へと約3倍になると予測しています。予測によると、この増加はさらに加速し、2025年には754億4,000万台のIoTデバイスが予想されています。モノのインターネットの成長を後押しする重要な要素は、接続オプションの範囲が拡大し続けていることです。IoTの改善は、5G組織とブロードバンド速度のアクセス可能性の上昇によって活性化されており、これによってデバイスは、この時点まで理解不能で生産的であった速度で関連付けることができます。

自律走行車とロボット工学に対する需要の高まり

カメラ、ライダー、レーダー、超音波センサーなど、少数のセンサーから得られる膨大な量の情報をリアルタイムで処理することは、ロボットや自立走行車にとって不可欠です。組織のエッジでローカルに情報を処理することで、エッジシミュレーションインテリジェンスは、これらのフレームワークがクラウド基盤への依存を減らし、迅速に選択できるようにします。エッジAIは、ロボット工学や自動運転車が重要な選択を迅速に行えるようにすることで、安全性と信頼性を向上させる。システムは、エッジで即座にデータを処理することで、変化する環境条件やあらゆるリスクに迅速に対応することができ、事故の可能性を低減し、全体的なパフォーマンスを向上させます。

主要プレーヤーの中には、市場成長をさらに後押しするM&A戦略をとる企業もあります。例えば、2020年6月19日、Autonomous Vehicles Alliance（自律走行車アライアンス）とADLINK（エッジコンピューティングのトレンドセッター）は、個人をインターフェースし、ビジネスと社会にポジティブな影響を与えるという全体的なビジョンを持ち、エッジの人工知能を活用して、すべての人に自立した運転を促すために協力しています。Autowareのオープンソース自動運転イノベーションを利用することで、この提携は、交通と交通信号の取り決めを相互に鋭敏にすることに主眼を置きます。

データセキュリティとプライバシーに関する懸念

データセキュリティとプライバシーに関する懸念は、データを収集、分析、保持するエッジAIシステムに対する顧客や企業の信頼を損なう。信頼感の欠如は、利害関係者が機密データを共有したり、エッジAIアプリを展開したりすることを妨げ、エッジAIソリューションの導入と資金調達を阻害します。個人データを収集、処理、保護する組織は、厳しい規制に従わなければならないです。こうした規制の遵守は、エッジAI実装のコストと複雑性を高めることで、ビジネスの拡大を阻害します。

エッジコンピューティングが成長し、世界中で接続されたガジェットの数が増えるにつれて、エッジAIシステムはデータ漏洩、サイバー攻撃、不正アクセスに対して脆弱になります。その結果、エッジAI技術に対する消費者の信頼が低下し、その拡大が阻害されます。データのプライバシーとセキュリティを確保するためには、暗号化、アクセス制限、認証システム、安全な通信プロトコルのような強力なセキュリティ対策をエッジAI設定に統合する必要があります。しかし、企業は分散したエッジ設定にこれらのセキュリティ管理を実装し維持することが困難であり、エッジAIソリューションの導入を妨げています。

目次

第1章 調査手法と調査範囲

第2章 定義と概要

第3章 エグゼクティブサマリー

第4章 市場力学

• 影響要因
  • 促進要因
    • モノのインターネット（IoT）の普及拡大
    • 自律走行車とロボティクスに対する需要の高まり
  • 抑制要因
    • データのプライバシーとセキュリティへの懸念
  • 機会
  • 影響分析

第5章 産業分析

• ポーターのファイブフォース分析
• サプライチェーン分析
• 価格分析
• 規制分析
• ロシア・ウクライナ戦争の影響分析
• DMIの見解

第6章 COVID-19分析

第7章 コンポーネント別

• ハードウェア
• ソフトウェア
• エッジクラウドインフラ
• サービス

第8章 技術別

• 機械学習（ディープラーニング、機械学習モデル）
• コンピュータビジョン
• 自然言語処理
• 予測分析

第9章 エンドユーザー別

• 家電
• 製造業
• 自動車
• 政府機関
• ヘルスケア
• エネルギー
• ヘルスケア
• その他

第10章 地域別

• 北米
  • 米国
  • カナダ
  • メキシコ
• 欧州
  • ドイツ
  • 英国
  • フランス
  • イタリア
  • スペイン
  • その他の欧州
• 南米
  • ブラジル
  • アルゼンチン
  • その他の南米
• アジア太平洋
  • 中国
  • インド
  • 日本
  • オーストラリア
  • その他のアジア太平洋
• 中東・アフリカ

第11章 競合情勢

• 競合シナリオ
• 市況/シェア分析
• M&A分析

第12章 企業プロファイル

• ADLINK Technology Inc.
• Alphabet Inc.
• Amazon.com, Inc
• Gorilla Technology Group
• Intel Corporation
• International Business Machines Corporation
• Microsoft Corporation
• Nutanix, Inc.
• Synaptics Incorporated
• Viso.ai

第13章 付録

Overview

Global Edge AI Market reached US$ 16.8 Billion in 2023 and is expected to reach US$ 73.8 Billion by 2031, growing with a CAGR of 20.6% during the forecast period 2024-2031.

The processing power at the edge is increased by improvements in edge technology for computing, such as specialized processors and hardware accelerators. Complex AI models are developed and operated effectively on edge devices because of this enhanced processing power, which makes difficult data analysis and real-time inference jobs simpler to finish.

By moving computer power closer to the data source, edge computing dramatically lowers delay and transmission times for data. For AI applications that need to make decisions in real-time, such as augmented reality, industrial automation and autonomous vehicles, this latency reduction is important. Edge computing improves system performance and customer satisfaction by reducing latency, which allows for faster AI inference and response times.

The growing initiatives by the major key players to promote Edge AI globally by launching new products help to boost global edge AI market growth over the forecast period. For instance, on July 06, 2023, Silicom completed a partnership with Hailo to launch the Edge AI Product Line. The integration of Hailo's AI accelerators into Silicom's current Edge platforms addresses performance challenges for Edge AI applications. Consequently, Silicom's products will deliver visual processing and AI inference at the edge with an exceptionally appealing price/performance ratio.

North American organizations and governments are strategically investing in edge AI infrastructure, R&D and research to be competitive in the global market. The edge AI industry is growing and innovating because of initiatives including business investments, government funding and public-private partnerships. According to the study conducted by 5G Americas Omdia, North America leads with 176 million 5G connections as of Quarter 3 of 2023 which represents an additional 22 million new connections in the last quarter.

Dynamics

The Increasing Adoption of the Internet of Things (IoT)

At the border of the network, sensors, cameras and other connected devices offer enormous volumes of data for IoT devices. Without depending on centralized cloud servers, edge AI enables real-time processing and analysis of this data directly on the edge, enabling quick insights and actions. Low latency is required for real-time response for numerous Internet of Things uses, including linked cars, smart homes and industrial automation. To meet this need, Edge artificial intelligence analyses data locally, which lowers latency and ensures rapid decision-making without the delays imposed on by sending data to distant data centers.

IoT usage has risen significantly over the last 10 years. IHS anticipates that there will be nearly three times as many IoT devices used by 2022 from 15.41 billion in 2015 to 42.62 billion. Forecasts indicate that this increase will pick up even more velocity, with 75.44 billion IoT devices anticipated by 2025. A key element propelling the Internet of Things' growth is the ever-expanding range of connectivity options. IoT improvement has been energized by the rising accessibility of 5G organizations and broadband velocities, which enable devices to associate at rates that were up to this point unfathomable and productive.

Rising Demand for Autonomous Vehicles and Robotics

Real-time processing of enormous quantities of information from a few sensors, similar to cameras, lidar, radar and ultrasonic sensors, is essential for robots and independent vehicles. Through handling information locally at the organization's edge, edge-simulated intelligence empowers these frameworks to settle on choices rapidly and with less dependence on incorporated cloud foundations. Edge AI improves safety and dependability by empowering robotics and self-driving cars to make important choices quickly. The systems can react rapidly to shifting environmental conditions and any risks by processing data immediately at the edge, which lowers the possibility of accidents and boosts overall performance.

Some of the major key players follow merger and acquisition strategies which further help to boost market growth. For instance, on June 19, 2020, the Autonomous Vehicles Alliance and ADLINK, a trendsetter in edge computing with an overall vision to interface individuals and positively influence business and society, are cooperating to utilize edge man-made intelligence to empower independent driving for everybody. Using Autoware's open-source self-driving innovation, the participation will zero in on mutually fabricating astute transportation and traffic signal arrangements.

Data Privacy and Security Concerns

Concerns regarding data security and privacy damage customers' and businesses' faith in Edge AI systems to collect, analyze and retain their data. The lack of confidence prevents stakeholders from sharing sensitive data or deploying AI apps at the edge, which impedes the uptake and funding of Edge AI solutions. Organizations that collect, process and safeguard personal data have to abide by strict restrictions. Adherence to these regulations impedes business expansion by raising the costs and complexity of Edge AI implementations.

As edge computing grows and there is a growing number of connected gadgets in the world, edge AI systems are vulnerable to data breaches, cyberattacks and unauthorized access. The consequences reduce consumer trust in Edge AI technology and impede its expansion. It is necessary to integrate strong security measures, like encryption, access restrictions, authentication systems and secure communication protocols, in Edge AI settings to ensure data privacy and security. However, businesses find it difficult to implement and maintain these security controls across dispersed edge settings, which hinders the uptake of Edge AI solutions.

Segment Analysis

The global edge AI market is segmented based on component, technology, end-user and region.

Growing Adoption of Edge AI Software

Based on the components, the Edge AI market is segmented into Hardware, Software, Edge Cloud Infrastructure and Services. Software components in the market accounted largest market share due to the growing industrial adoption globally. Edge AI software solutions offer flexibility and adaptability to a wide range of edge computing devices and hardware platforms. The software solutions can be easily integrated into existing edge infrastructure, enabling organizations to leverage their investments in edge devices while adding AI capabilities. Edge AI software solutions can scale to meet the growing demands of diverse applications and use cases across industries. Organizations can deploy Edge AI software across multiple edge devices and locations, allowing for distributed processing and analysis of data without the need for significant hardware upgrades.

Globally, major key players launched innovative edge AI software which helps to boost segment growth over the forecast period. For instance, on February 26, 2024, Intel announced a new edge platform for scaling AI applications. The platform's edge infrastructure incorporates the OpenVINO AI inference runtime for edge AI, along with secure, policy-based automation of IT and OT management tasks. Over the past five years, Intel's OpenVINO has undergone evolution to assist developers in optimizing applications for low latency and low power consumption, facilitating deployment on existing hardware at the edge. The enables standard hardware that is already deployed to efficiently run AI applications without the need for costly upgrades or extensive modifications.

Geographical Penetration

North America is Dominating the Edge AI Market

North America is a pioneer in Edge AI technology development and adoption. Innovation and investment in Edge AI have been fueled by the region's strong ecosystem of technology startups, research centers and venture capitalists. Many significant technological companies that have led the way in creating and implementing Edge AI solutions are based in North America, including Google, Microsoft, Amazon, IBM and Intel. The businesses could dedicate substantial R&D resources to Edge AI research, development and commercialization.

Major key players in the region launched new innovative products which helped to boost regional market growth over the forecast period. For instance, on March 15, 2023, Texas Instruments launched a new family of six Arm Cortex-based vision processors that allow designers to add more vision and artificial intelligence (AI) processing at a lower cost and with better energy efficiency in various applications such as video doorbells, machine vision and autonomous mobile robots.

Competitive Landscape.

The major global players in the market include ADLINK Technology Inc., Alphabet Inc., Amazon.com, Inc., Gorilla Technology Group, Intel Corporation, International Business Machines Corporation, Microsoft Corporation, Nutanix, Inc. Synaptics Incorporated and Viso.ai.

COVID-19 Impact Analysis

Production and delivery of AI edge hardware components were impacted by the pandemic's interruption of global supply chains. Delays in the development and deployment of AI edge devices resulted from the availability of essential parts hampered by manufacturing slowdowns, movement restrictions and border closures. The epidemic pushed up the industry's adoption of digitalization and remote labor. To facilitate remote collaboration, improve cybersecurity for scattered networks and offer edge computing capabilities for distant operations, there's a greater need for AI edge solutions.

Due to the increase in digital activities and detached work, edge computing solutions were becoming increasingly vital to process data closer to the source and reduce latency. AI edge technologies are essential for providing edge computing capabilities, which increases approval in a variety of industries, including retail, logistics and manufacturing. The pandemic hampered research and development efforts in the AI edge sector, which led to several initiatives being shelved or delayed due to restricted access and collaboration in facilities. Research on AI-driven solutions for contact tracing, disease prediction at the edge and pandemic monitoring, however, has increased significantly.

Russia-Ukraine War Impact Analysis

The conflict disrupts the supply chains of AI edge technology components or manufacturing facilities located in the affected regions (Russia or Ukraine), it could lead to delays or shortages in product availability. It could impact companies reliant on these supply chains for their AI edge solutions. Geopolitical tensions create uncertainty in global markets, leading to hesitancy among businesses to invest in AI edge technologies due to concerns about geopolitical stability, trade disruptions or economic sanctions.

Companies increase their investment strategies in AI edge technologies, potentially diverting resources away from regions directly affected by the conflict to more stable areas. It could lead to shifts in research and development, manufacturing or investment in AI-edge startups and companies. Geopolitical tensions and conflicts prompt governments to enact new regulations or export controls on AI edge technologies, particularly if they are deemed sensitive or have dual-use applications. The regulatory changes could impact the global flow of AI edge technology and influence market dynamics.

By Component

• Hardware
• Software
• Edge Cloud Infrastructure
• Services

By Technology

• Machine Learning (Deep Learning, Machine Learning Models)
• Computer Vision
• Natural Language Processing
• Predictive Analytics

By End-User

• Consumer Electronics
• Manufacturing
• Automotive
• Government
• Healthcare
• Energy
• Healthcare
• Others

By Region

• North America
  • U.S.
  • Canada
  • Mexico
• Europe
  • Germany
  • UK
  • France
  • Italy
  • Spain
  • Rest of Europe
• South America
  • Brazil
  • Argentina
  • Rest of South America
• Asia-Pacific
  • China
  • India
  • Japan
  • Australia
  • Rest of Asia-Pacific
• Middle East and Africa

Key Developments

• On February 01, 2024, Advantech launched a ruggedized edge AI system for heavy industry applications. The MIC-715-OX ruggedized edge AI system is purpose-built to address these exact challenges. Encased in ruggedized housing, it effectively mitigates vibrations and mechanical shocks. With an IP67 rating, it ensures resistance against water and dust ingress. Its fanless design ensures optimal cooling in any weather condition, eliminating the need to draw outside contaminated air into the enclosure.
• On October 10, 2023, Macrometa launched PhotonIQ, AI Services at the Edge. PhotonIQ utilizes both Macrometa's unparalleled Global Data Network (GDN), which provides data and computational capabilities to two billion individuals and 10 billion devices globally and the most recent advancements in Artificial Intelligence and Machine Learning.
• On January 10, 2024, Ambarella, Inc. launched the leading-edge Cooper Developer Platform. Cooper provides a seamless integration of software, hardware, advanced finely-tuned AI models and services, offering comprehensive support for Ambarella's complete range of AI systems-on-chip (SoCs).

Why Purchase the Report?

• To visualize the global edge AI market segmentation based on component, technology, end-user and region, as well as understand key commercial assets and players.
• Identify commercial opportunities by analyzing trends and co-development.
• Excel data sheet with numerous data points of edge AI market-level with all segments.
• PDF report consists of a comprehensive analysis after exhaustive qualitative interviews and an in-depth study.
• Product mapping available as excel consisting of key products of all the major players.

The global edge AI market report would provide approximately 62 tables, 59 figures and 201 Pages.

Target Audience 2024

• Manufacturers/ Buyers
• Industry Investors/Investment Bankers
• Research Professionals
• Emerging Companies

Table of Contents

1. Methodology and Scope

• 1.1. Research Methodology
• 1.2. Research Objective and Scope of the Report

2. Definition and Overview

3. Executive Summary

• 3.1. Snippet by Component
• 3.2. Snippet by Technology
• 3.3. Snippet by End-User
• 3.4. Snippet by Region

4. Dynamics

• 4.1. Impacting Factors
  • 4.1.1. Drivers
    • 4.1.1.1. The Increasing Adoption of the Internet of Things (IoT)
    • 4.1.1.2. Rising Demand for Autonomous Vehicles and Robotics
  • 4.1.2. Restraints
    • 4.1.2.1. Data Privacy and Security Concerns
  • 4.1.3. Opportunity
  • 4.1.4. Impact Analysis

5. Industry Analysis

• 5.1. Porter's Five Force Analysis
• 5.2. Supply Chain Analysis
• 5.3. Pricing Analysis
• 5.4. Regulatory Analysis
• 5.5. Russia-Ukraine War Impact Analysis
• 5.6. DMI Opinion

6. COVID-19 Analysis

• 6.1. Analysis of COVID-19
  • 6.1.1. Scenario Before COVID
  • 6.1.2. Scenario During COVID
  • 6.1.3. Scenario Post COVID
• 6.2. Pricing Dynamics Amid COVID-19
• 6.3. Demand-Supply Spectrum
• 6.4. Government Initiatives Related to the Market During Pandemic
• 6.5. Manufacturers Strategic Initiatives
• 6.6. Conclusion

7. By Component

• 7.1. Introduction
  • 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
  • 7.1.2. Market Attractiveness Index, By Component
• 7.2. Hardware*
  • 7.2.1. Introduction
  • 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 7.3. Software
• 7.4. Edge Cloud Infrastructure
• 7.5. Services

8. By Technology

• 8.1. Introduction
  • 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
  • 8.1.2. Market Attractiveness Index, By Technology
• 8.2. Machine Learning (Deep Learning, Machine Learning Models) *
  • 8.2.1. Introduction
  • 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 8.3. Computer Vision
• 8.4. Natural Language Processing
• 8.5. Predictive Analytics

9. By End-User

• 9.1. Introduction
  • 9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
  • 9.1.2. Market Attractiveness Index, By End-User
• 9.2. Consumer Electronics*
  • 9.2.1. Introduction
  • 9.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 9.3. Manufacturing
• 9.4. Automotive
• 9.5. Government
• 9.6. Healthcare
• 9.7. Energy
• 9.8. Healthcare
• 9.9. Others

10. By Region

• 10.1. Introduction
  • 10.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
  • 10.1.2. Market Attractiveness Index, By Region
• 10.2. North America
  • 10.2.1. Introduction
  • 10.2.2. Key Region-Specific Dynamics
  • 10.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
  • 10.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
  • 10.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
  • 10.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
    • 10.2.6.1. U.S.
    • 10.2.6.2. Canada
    • 10.2.6.3. Mexico
• 10.3. Europe
  • 10.3.1. Introduction
  • 10.3.2. Key Region-Specific Dynamics
  • 10.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
  • 10.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
  • 10.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
  • 10.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
    • 10.3.6.1. Germany
    • 10.3.6.2. UK
    • 10.3.6.3. France
    • 10.3.6.4. Italy
    • 10.3.6.5. Spain
    • 10.3.6.6. Rest of Europe
• 10.4. South America
  • 10.4.1. Introduction
  • 10.4.2. Key Region-Specific Dynamics
  • 10.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
  • 10.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
  • 10.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
  • 10.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
    • 10.4.6.1. Brazil
    • 10.4.6.2. Argentina
    • 10.4.6.3. Rest of South America
• 10.5. Asia-Pacific
  • 10.5.1. Introduction
  • 10.5.2. Key Region-Specific Dynamics
  • 10.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
  • 10.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
  • 10.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
  • 10.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
    • 10.5.6.1. China
    • 10.5.6.2. India
    • 10.5.6.3. Japan
    • 10.5.6.4. Australia
    • 10.5.6.5. Rest of Asia-Pacific
• 10.6. Middle East and Africa
  • 10.6.1. Introduction
  • 10.6.2. Key Region-Specific Dynamics
  • 10.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
  • 10.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
  • 10.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User

11. Competitive Landscape

• 11.1. Competitive Scenario
• 11.2. Market Positioning/Share Analysis
• 11.3. Mergers and Acquisitions Analysis

12. Company Profiles

• 12.1. ADLINK Technology Inc.*
  • 12.1.1. Company Overview
  • 12.1.2. Product Portfolio and Description
  • 12.1.3. Financial Overview
  • 12.1.4. Key Developments
• 12.2. Alphabet Inc.
• 12.3. Amazon.com, Inc
• 12.4. Gorilla Technology Group
• 12.5. Intel Corporation
• 12.6. International Business Machines Corporation
• 12.7. Microsoft Corporation
• 12.8. Nutanix, Inc.
• 12.9. Synaptics Incorporated
• 12.10. Viso.ai

LIST NOT EXHAUSTIVE

13. Appendix

• 13.1. About Us and Services
• 13.2. Contact Us