Physical AI in Manufacturing & Logistics Market: 2026-2030
| 出版 | Juniper Research |
| 出版年月 | 2026年04月 |
| ベーシックライセンス | GBP 3,250 |
| 種別 | 英文調査報告書 |
| 商品番号 | SMR-18073 |
Juniper Researchの「製造および物流におけるフィジカルAI市場 2026-2030年」調査レポートは、この急成長市場の成長を牽引する主要な経済的、運用的、技術的要因を詳細に分析しています。また、市場が直面する主要な課題と、今後12ヶ月間で製造および物流企業による導入を加速させるために、これらの課題がどのように克服されつつあるかについても解説しています。さらに、物理AIソフトウェアベンダー向けの戦略的な提言も提供し、関係者が短期的に市場への投資を最大化する方法についての洞察を提供します。
このレポートには、15カ国における製造および物流におけるフィジカルAI市場の規模を示すデータが含まれています。物理AIに投資している製造業者および物流プロバイダーの数、物理AIソフトウェアへの業界支出など、主要な予測指標を提供しています。また、主要なトレンド、課題、そして関係者向けの重要な提言についても包括的に評価しています。これらの情報は、急速に発展するこの市場を理解するための重要なツールとなり、物理AIおよびロボティクスベンダーが将来の市場戦略を策定する上で役立ちます。
主な特長
- 市場動向：製造および物流におけるフィジカルAI市場の主要なトレンドと機会に関する洞察。労働力不足、eコマース需要の拡大、新たなビジョン・言語・アクション（VLA）モデル、ハードウェアの進歩といった市場推進要因の分析を含む。本調査では、シミュレーションと実世界のギャップ、リアルタイムデータ処理、アクチュエータの限界といった市場課題についても取り上げている。
- 主なポイント：製造および物流におけるフィジカルAI市場の主要な開発機会と調査結果を詳細に分析し、関係者向けの重要な戦略的提言を提示する。
- 業界ベンチマーク予測：フィジカルAIに投資している製造および物流企業の数、フィジカルAIを活用している業界における導入ロボットの数、フィジカルAIソフトウェアへの総支出額などを含む包括的な予測データを提供する。
- Juniper Research・フューチャーリーダーズインデックス：ジュニパーリサーチ・フューチャーリーダーズインデックスに基づき、12社の物理AIソフトウェアベンダーの主要プレーヤーの能力とキャパシティを評価する。以下の主要企業の市場規模分析を掲載しています。
- Ansys
- Amazon Web Services
- Cadence
- Dassault Systèmes
- GE Vernova
- Hitachi
- IBM
- Intrinsic
- Microsoft
- NVIDIA
- Rockwell Automation
- Siemens
Overview
Our Physical AI in Manufacturing & Logistics research suite provides in-depth analysis of the key economic, operational, and technological factors driving growth in this fast-growing market. It also addresses the key challenges facing the market and how limitations are being overcome to accelerate adoption by manufacturing & logistics businesses over the next 12 months. Moreover, it provides strategic recommendations for physical AI software vendors; giving stakeholders insight into how to maximise their investments in the market in the near term.
The suite includes a data deliverable that sizes the physical AI in manufacturing & logistics market across 15 countries; providing key forecast metrics including the number of manufacturers & logistics providers investing in physical AI, as well as industry spend on physical AI software. It also provides a complete assessment of key trends, challenges, and key recommendations for stakeholders. Collectively, these provide a critical tool for understanding this rapidly emerging market; helping physical AI and robotics vendors shape their future market strategy.
All report content is delivered in the English language.
Key Features
- Market Dynamics: Insights into key trends and opportunities within the physical AI in manufacturing & logistics market, including analysis of market drivers such as labour shortages, growing eCommerce demand, emerging Vision-Language-Action models, and hardware advancements. The study also addresses market challenges, including the sim-to-real gap, real-time data processing, and actuator limitations.
- Key Takeaways: In-depth analysis of key development opportunities and findings within the physical AI in manufacturing & logistics market, accompanied by key strategic recommendations for stakeholders.
- Benchmark Industry Forecasts: Comprehensive forecast data including the number of manufacturing & logistics businesses investing in physical AI, the number of deployed robots in the industry that leverage physical AI, and total spend on physical AI software.
- Juniper Research Future Leaders Index: Key player capability and capacity assessment for 12 physical AI software vendors via the Juniper Research Future Leaders Index; featuring market sizing of the following major players:
- Ansys
- Amazon Web Services
- Cadence
- Dassault Systèmes
- GE Vernova
- Hitachi
- IBM
- Intrinsic
- Microsoft
- NVIDIA
- Rockwell Automation
- Siemens
Research Deliverables
Market Data & Forecasts
The market-leading research suite for the Physical AI in Manufacturing & Logistics market includes access to the full set of forecast data comprising 12 tables and over 2,000 datapoints. Metrics in the research suite include:
- Manufacturing & Logistics Businesses Investing in Physical AI
- Manufacturing & Logistics Robots Deployed
- Manufacturing & Logistics Robots Deployed Using Physical AI
- Spend on Physical AI Software by Manufacturing & Logistics Businesses
Juniper Research’s Interactive Forecast Excel contains the following functionality:
- Statistics Analysis: Users benefit from the ability to search for specific metrics; displayed for all regions and countries across the data period. Graphs are easily modified and can be exported to the clipboard.
- Country Data Tool: This tool allows users to look at metrics for all regions and countries in the forecast period. Users can refine the metrics displayed via a search bar.
- Country Comparison Tool: Users can select and compare specific countries. The ability to export graphs is included in this tool.
- What-if Analysis: Here, users can compare forecast metrics against their own assumptions, via three interactive scenarios.
レポート構成＆価格表
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プレスリリース
Physical AI Deployments in Manufacturing & Logistics to Reach 400,000 Systems by 2030
Hampshire, UK – 13th April 2026: A new study by global tech strategist firm Juniper Research has found that deployments of physical AI systems in manufacturing and logistics will reach 400,000 by 2030; an increase of 3,500% from 2026. This growth is being driven by advances in real-time processing and AI models, which are improving both the capabilities and safety of physical AI operating in real-world environments.
Physical AI systems can perceive, reason, and act in the real world. In manufacturing and logistics, they are expected to play a critical role in improving warehouses and factory efficiency; delivering cost savings for businesses.
“Multiple technological advancements are converging to accelerate physical AI adoption,” said Molly Gatford, Senior Research Analyst at Juniper Research. “Reduced latency from improved real-time processing is enabling more reliable real-world operation, while more advanced models allow systems to respond to a broader range of inputs, including tactile data; improving how physical AI interacts with its environment.”
Shifting from Physical AI Development to Deployment
With key technical barriers now being addressed, vendors must move beyond development towards large‑scale deployment of physical AI systems. To do this, vendors must partner with connectivity providers; as reliable, low‑latency connectivity is essential to support real‑time decision‑making, which is vital for physical AI deployment.
“Vendors must prioritise connectivity partners that offer edge-enabled connectivity architectures; allowing physical AI systems to process data locally and reduce latency constraints. This becomes essential with advanced physical AI models now requiring processing of data from multiple different sensor inputs,” Gatford concluded.
The new market research suite offers the most comprehensive assessment of the physical AI in manufacturing & logistics market to date; providing analysis and forecasts of over 2,000 datapoints, across 15 countries, over five years. It includes a ‘Future Leaders Index’ and examination of future market opportunities.