Worldwide Asset Tracking and AI in Supply Chain Management Industry - Cloud-based AI-as-a-Service for SCM Will Exceed $2.3 Billion by 2026
DUBLIN, Sept. 7, 2021 /PRNewswire/ -- The "Asset Tracking and AI in Supply Chain Management Market 2021 - 2026" report has been added to ResearchAndMarkets.com's offering.
This research evaluates asset tracking technologies, solutions, and the overall asset management and logistics ecosystem including major players, strategies and market positioning. The research evaluates the impacts of use case-specific considerations in terms of asset tracking technology and solution selection.
The asset management market remains constrained by a relatively low number of enterprise-connected assets across certain important asset classes. Leading asset tracking solution companies are focusing on the asset value to a business or governmental organization rather than the book value of the asset itself. A consultative marketing/sales approach is necessary to inform enterprises, first of the value of interconnecting business assets, and secondly, demonstrative asset tracking outcomes that bring value straight to the bottom line.
Modern supply chains represent complex systems of organizations, people, activities, information, and resources involved in moving a product or service from supplier to customer. Supply Chain Management (SCM) solutions are typically manifest in software architecture and systems that facilitate the flow of information among different functions within and between enterprise organizations.
Leading SCM solutions catalyze information sharing across organizational units and geographical locations, enabling decision-makers to have an enterprise-wide view of the information needed in a timely, reliable and consistent fashion. Various forms of Artificial Intelligence (AI) are being integrated into SCM solutions to improve everything from process automation to overall decision-making. This includes greater data visibility (static and real-time data) as well as related management information system effectiveness.
In addition to fully automated decision-making, AI systems are also leveraging various forms of cognitive computing to optimize the combined efforts of artificial and human intelligence. For example, AI in SCM is enabling improved supply chain automation through the use of virtual assistants, which are used both internally (within a given enterprise) as well as between supply chain members (e.g. customer-supplier chains). It is anticipated that virtual assistants in SCM will leverage an industry-specific knowledge database as well as company, department, and production-specific learning.
AI-enabled improvements in supply chain member satisfaction causes a positive feedback loop, leading to better overall SCM performance. One of the primary goals is to leverage AI to make supply chain improvements from production to consumption within product-related industries as well as create opportunities for supporting "servitization" of products in a cloud-based "as a service" model. AI will identify opportunities for supply chain members to have greater ownership of "outcomes as a service" and control of overall product/service experience and profitability.
Key Topics Covered:
Asset Tracking Market by Infrastructure, Connection Type, Mobility, Location Method, Solution Type, Supporting Tech and Industry Verticals
1. Executive Summary
AI in Supply Chain Management Market by Technology, Processes, Solutions, Management Function, Deployment Model, Business Type and Industry Verticals
1.0 Executive Summary
3.0 AI in SCM Challenges and Opportunities
4.0 Supply Chain Ecosystem Company Analysis
5.0 AI in SCM Market Case Studies
6.0 AI in SCM Market Analysis and Forecasts 2021 - 2026
7.0 Summary and Recommendations
For more information about this report visit https://www.researchandmarkets.com/r/188mr5
Research and Markets
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