市場調査レポート
商品コード
1194926
次世代ネットワーキングにおけるAI (2023年~2028年):インフラ・ネットワークタイプ・IoTソリューション・セグメント (消費者・企業・産業・政府)・産業別Artificial Intelligence in Next Generation Networking by Infrastructure, Network Type, IoT Solution, Segment (Consumer, Enterprise, Industrial, and Government), and Industry Vertical 2023 - 2028 |
次世代ネットワーキングにおけるAI (2023年~2028年):インフラ・ネットワークタイプ・IoTソリューション・セグメント (消費者・企業・産業・政府)・産業別 |
出版日: 2023年01月25日
発行: Mind Commerce
ページ情報: 英文 118 Pages
納期: 即日から翌営業日
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ITおよびネットワーキングにおけるAIの総市場は、2028年には104億米ドルの規模に成長すると予測されています。特に、エンタープライズセグメントがAI対応ネットワーキング市場をリードし、2028年には39億米ドルを示す見通しです。
AIは、ソフトウェアやICTインフラの各種側面など、さまざまなデジタル技術にとって、急速に不可欠な要素となりつつあります。例えば、AIチップセット市場は、深層機械学習、画像検出などの多数のAI機能により、組込みシステムのエコシステム全体を変革する態勢となっています。世界のチップセットの85%がAIを搭載して出荷されており、2026年にはエレクトロニクス全体の63%以上が何らかの形で組み込みインテリジェンスを搭載することになる見通しです。
本レポートでは、組み込み機器、コンポーネント、ソフトウェアプラットフォーム (ネットワークの自動化・最適化・変換) など、さまざまなネットワーキング製品およびソリューションにおけるAIの動向を調査し、ネットワーキングにおけるAI技術とその用途、各種影響因子の分析、市場規模の予測、各種区分・地域別の内訳、主要企業のプロファイル、各種提言などをまとめています。
This report assesses the impact of AI in various networking products and solutions including embedded equipment, components, and software platforms (network automation, optimization, and transformation). The report also evaluates the role of SDN, edge computing, NFV, and augmented intelligence in the formation and support of AI-driven networking ecosystems.
In addition, the impact of 5G networks, IoT technology and systems, and network analytics functions are also analyzed. The report assesses technologies, products, and solutions from key solution providers, identifying key companies in each segment of the competitive landscape. This includes companies focused on AI specifically and related areas such as intent-based networks and experiential networking.
The report also provides forecasts for the AI-driven networking market based on major market segments and subsegments, AI technology type, deployment type, network type, industry vertical, and region. The report provides qualitative and quantitative analysis for the AI next generation networking market by infrastructure, network type, IoT solution, segment (consumer, enterprise, industrial, and government), and industry verticals from 2023 through 2028.
Artificial Intelligence is rapidly becoming an integral part of various digital technologies including software and many aspects of ICT infrastructure. For example, the AI chipset marketplace is poised to transform the entire embedded system ecosystem with a multitude of AI capabilities such as deep machine learning, image detection, and many others. With 85% of all chipsets globally shipping AI-equipped, over 63% of all electronics will have some form of embedded intelligence by 2026. The AI in next generation networking market as a whole will ultimately be much larger as infrastructure vendors embed AI within virtually all software and platforms.
Infrastructure is anticipated to be one of the primary focus areas for AI as network operators seek to reduce costs and improve efficiencies while simultaneously reducing the incidence of errors and adverse network events. AI technology will play a key role in the transformation of network intelligence to become increasingly self-driven. Technologies like cognitive computing, machine learning, deep learning, and predictive application will be fundamental to the transformation of network configuration automation and operational autonomy.
AI-driven networking is going to impact wireless networking of all sizes for all communication service providers, improving service realization and support, and ultimately impacting every industry vertical from transportation to medical care to financial services. Furthermore, we see the convergence of AI and Internet of Things (IoT) technologies and solutions (AIoT) leading to "thinking" networks and systems that are becoming increasingly more capable of solving a wide range of problems across a diverse number of industry verticals.
In terms of the impact of AI on wireless networks, the evolution is already underway from a standards and network topology approach with 5G service-based architectures. Implementation within public communications service providers will scale slowly due to legacy systems such as OSS/BSS. However, closed-loop private 5G wireless networks will be in the vanguard of deployment for AI next generation networking.
This evolution will lead to AI-enabled functions throughout 6G networks within the 2030 to 2040 timeframe. This will include contextually agile RF networks that support event-driven adaptation and resource allocation optimization. It will also include many improvements at the device level such as AI-enabled distributed computing, which will facilitate persistent computation-oriented communications.
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