Artficial Intelligence in Logistics: Global Drivers, Restraints, Opportunities, Trends, and Forecasts up to 2023

  • ID: 4495806
  • Report
  • Region: Global
  • 71 Pages
  • Infoholic Research LLP
1 of 5

FEATURED COMPANIES

  • ActiveScalar
  • Amazon
  • Google
  • IBM
  • Microsoft
  • Pluto 7
  • MORE

Overview:
The logistics vertical is undergoing a fundamental transformation with the increase in the amount of data and the number of devices utilized,  reduction in costs to maintain the competitiveness, and urge to maintain the required stock levels, (staged and in-transit) to ensure on time delivery and shortages. All this requires some level of automation in the supply chain to allow for timely decision making.

Artificial Intelligence is in a nascent stage in logistics but is expected to grow at a rapid pace. It is expected to remould the logistics industry with high level of automation in manufacturing, logistics, warehousing and last mile delivery. Machine and human collaboration will enable smart order picking in logistics and smart glasses will enable smart hands-free operations. Automated vehicles and drones are expected to change the paradigm of the logistics industry.

Market Analysis:
The companies are increasingly testing Artficial Intelligence in Logistics to improve on the last mile delivery, reduce the time to go to market, and provide for the required customization to customers. As per this research, the Artificial Intelligence market in logistics is predicted to grow at a CAGR of 42.9% over 2017-2023 to reach $6.5 billion by 2023. The market is analysed by application, vertical, region, and mode of transport.

Market Segmentation Analysis:
The market has been segmented on the basis of applications in logistics including automation of processes, planning and forecasting, machine and human collaboration, self driven forklifts, self driven vehicles, etc. Self driven vehicles and self driven forklifts occupy the maximum share at present and autonomous vehicles are expcted to gain maximum traction in future. On the baisis of modes of transport, roadways is expected to embrace AI the maxium, followed by railways, seaways, and airways.

Countries and Vertical Analysis:
The counties covered in report are US, Canada, UK, Germany, France, Nordics, Benelux, China, India. Among these  US and China are expected to grow at a higher CAGR through the forecast period 2017-2023. The popular use case/verticals for the AI in logistics are food, pharma, retail, manufacturing, automotive, and others. Several logistics palyers are testing these technologies to gain an upper edge in the market and improve on the last mile delivery.

Benefits and Vendors
The report contains an in-depth analysis of vendor profiles, which include financial health, business units, key business priorities, SWOT, strategy, and views; and competitive landscape. Companies analysed in the report are Amazon, Google, IBM, and Microsoft. Apart from that several start ups that are focussing specifically on AI in logistics have been analysed.

The study offers a comprehensive analysis of the “AI in Logistics”. Bringing out the complete key insights of the industry, the report aims to provide an opportunity for players to understand the latest trends, current market scenario, government initiatives, and technologies related to the market. In addition, it helps the venture capitalist in understanding the companies better and take informed decisions.

READ MORE
Note: Product cover images may vary from those shown
2 of 5

FEATURED COMPANIES

  • ActiveScalar
  • Amazon
  • Google
  • IBM
  • Microsoft
  • Pluto 7
  • MORE

1 Industry Outlook
1.1 Industry Overview
1.2 Industry Trends

2 Report Outline
2.1 Report Scope
2.2 Report Summary
2.3 Research Methodology
2.4 Report Assumptions

3 Market Snapshot
3.1 Total Addressable Market (TAM)
3.2 Segmented Addressable Market (SAM)
3.3 Related Markets

4 Market Outlook
4.1 Overview
4.2 Regulatory Bodies & Standards
4.3 Government Spending and Initiatives
4.4 Porter 5 (Five) Forces

5 Market Characteristics
5.1 Market Segmentation
5.2 Market Dynamics
5.2.1 Drivers
5.2.1.1 Need for on-time deliveries and instant go to market timings
5.2.1.2 Growing demand for convenience and safety
5.2.1.3 Increased acceptance and implementation of autonomous vehicles
5.2.1.4 Digitization of logistics leading to hyper customization
5.2.2 Restraints
5.2.2.1 Compliance with privacy and data security regulations
5.2.2.2 Increased automation will lead to job losses and can create social tensions
5.2.2.3 Shortage of industry standards
5.2.3 Opportunities
5.2.3.1 Growing amount of data in logistics
5.2.3.2 5.2.3.2 Growth of assisted driving
5.3 DRO – Impact Analysis

6 Trends, Roadmap, and Projects
6.1 Market Trends & Impact
6.1.1 Cloud Hosted Intelligence
6.1.2 Growing Demand for Customization
6.1.3 Multiple collaborations across the supply chain
6.2 Technology Roadmap

7 AI in Logistics Market by Application: Market Size & Analysis
7.1 Overview
7.2 Automation of Ordering and Processing
7.3 Planning and Forecasting
7.4 Machine and Human Collaboration
7.5 Self-driving Vehicles
7.6 Self-driving Forklifts
7.7 Others

8 Logistics by Verticals: Market Size & Analysis
8.1 Overview
8.2 Food
8.3 Pharma
8.4 Retail
8.5 Manufacturing
8.6 Automotive
8.7 Others

9 Geography: Market Size & Analysis
9.1 North America
9.1.1 US
9.1.2 Canada
9.2 Europe
9.2.1 Overview
9.2.2 UK
9.2.3 Germany
9.2.4 France
9.2.5 Nordics
9.2.6 Benelux
9.2.7 Rest of Europe
9.3 Asia Pacific
9.3.1 Overview
9.3.2 China
9.3.3 India
9.3.4 Rest of APAC
9.4 Latin America
9.5 Middle East & Africa

10 Mode of Transport: Market Size & Analysis
10.1 Overview
10.2 Roadways
10.3 Railways
10.4 Seaways
10.5 Airways

11 Vendor Profile
11.1 IBM
11.1.1 Overview
11.1.2 Business Unit
11.1.3 Business Segments
11.1.4 Financial Performance
11.1.5 Geographic Revenue
11.1.6 IBM and AI in Logistics Market
11.1.7 SWOT Analysis
11.1.8 Business Strategies
11.2 Google
11.2.1 Overview
11.2.2 Business Unit
11.2.3 Business Segments
11.2.4 Financial Performance
11.2.5 Geographic Revenue
11.2.6 Google and AI in Logistics
11.2.7 SWOT Analysis
11.2.8 Business Strategies
11.3 Microsoft
11.3.1 Overview
11.3.2 Business Unit
11.3.3 Business Segments
11.3.4 Financial Performance
11.3.5 Geographic Revenue
11.3.6 Microsoft and AI in Logistics
11.3.7 SWOT Analysis
11.3.8 Business Strategies
11.4 Amazon
11.4.1 Overview
11.4.2 Business Units
11.4.3 Financial Performance
11.4.4 Geographic Revenue
11.4.5 Amazon and AI in Logistics
11.4.6 SWOT Analysis
11.4.7 Business Strategies

12 Companies to Watch for
12.1 TransVoyant
12.1.1 Overview
12.1.2 AI Offerings
12.2 ActiveScalar
12.2.1 Overview
12.2.2 AI Offerings
12.3 Pluto 7
12.3.1 Overview
12.3.2 AI Offerings
12.4 Yojee
12.4.1 Overview
12.4.2 AI Offerings
12.5 Teknowlogi
12.5.1 Overview
12.5.2 AI Offerings

13 Expert’s Views
Annexure
Abbreviations

Note: Product cover images may vary from those shown
3 of 5

Loading
LOADING...

4 of 5
  • ActiveScalar
  • Amazon
  • Google
  • IBM
  • Microsoft
  • Pluto 7
  • Teknowlogi
  • TransVoyant
  • Yojee
Note: Product cover images may vary from those shown
5 of 5
Note: Product cover images may vary from those shown
Adroll
adroll