Heavy Construction Equipment Market Assessment, By Machinery Type [Earthmoving Equipment, Material Handling Equipment, Heavy Construction Vehicles, Others], By Propulsion Type [Diesel, CNG/LNG/RNG, Electric], By Horsepower [Below 100 hp, 100 to 500 hp, Ab

Heavy Construction Equipment Market Assessment, By Machinery Type [Earthmoving Equipment, Material Handling Equipment, Heavy Construction Vehicles, Others], By Propulsion Type [Diesel, CNG/LNG/RNG, Electric], By Horsepower [Below 100 hp, 100 to 500 hp, Above 500 hp] By Application [Excavation and Demolition, Heavy Lifting, Material Handling, Tunneling, Transportation, Recycling and Waste Management], By End-user Industry [Building and Construction, Forestry and Agriculture, Infrastructure, Mining, Others], By Region, Opportunities and Forecast, 2017-2031F



India AI In logistics market is projected to witness a CAGR of 31.66% during the forecast period FY2025-FY2032, growing from USD 756.31 million in FY2024 to USD 6828.58 million in FY2032. The market is witnessing an upswing with a growing demand for effective supply chain management and advanced technologies due to the e-commerce boom and the growing need for faster delivery solutions. AI applications are optimizing route, planning inventory management, and demand forecasting. With AI integration, real-time tracking is enabled in IoT devices, and businesses are investing in machine learning algorithms to make smooth decisions and reduce the cost of operations. The government is promoting digitalization and infrastructural development, which further accelerates this growth. With stakeholders increasingly recognizing the potential of AI in streamlining processes and improving customer experience investments, AI technology will accelerate its position in India as a major player in the global logistics landscape. The market has witnessed technological startups and collaboration with traditional logistics companies in aiming to introduce novelty and scalability. Thus, technology convergence with logistics is well poised to change this sector so that it will be able to respond better to the needs of rapidly evolving markets and be much more responsive.

In May 2024, an AI-powered RTO Predictor was developed by Delivery Limited, helping over 4,800 e-commerce businesses, including brands such as Heads Up for Tails and Healthkart, reduce return shipments and logistics costs. This solution is especially effective for cash-on-delivery (COD) orders, which constitute over 60% of e-commerce transactions in India, cutting returns by up to 20%. The RTO Predictor integrates during checkout to mitigate risks, using insights from 2.5 billion shipments to enhance customer intent understanding. After implementing this service, clients such as Minimalist and W for Women have reported improved conversion rates and lower logistics costs.

Demand for Supply Chain to Drive Market Growth

Growing demand for supply chain efficiency is the main driver for AI adoption in the Indian logistics market. E-commerce expansion and customer expectations for faster and more reliable deliveries have increased the pressure to optimize the operations of logistics companies. AI Technology can help meet these requirements by automating and improving important supply chain processes such as reserve management, request requests, and route optimization by reducing costs and increasing service levels. The ability to predict the demand for operation and the fluctuation of optimization reduces nearby places, improving the use of resources and reducing fuel consumption. Additionally, the growing need for real-time tracking and seamless logistics operations is driving the adoption of AI-based solutions that provide better visibility and control across the supply chain. AI has emerged as an important tool for businesses to stay competitive, leading to the rapid growth of the AI-based logistics market in India.

In May 2024, TVS Supply Chain Solutions partnered with Manchester Metropolitan University to advance AI in supply chain operations, demonstrating TVS SCS’s commitment to technological growth. Supported by Higher Education Innovation Funding and an application for a Knowledge Transfer Partnership, the collaboration focuses on integrating AI governance into business practices. This partnership will significantly benefit India’s logistics market, providing advanced AI tools to optimize operations, enhance efficiencies, and support sustainable logistics solutions, which are essential for meeting India’s growing demand for streamlined, tech-enabled supply chains.

Digital Transformation in Logistics to Propel Market Growth

Digital transformation is playing a key role in the growth of India AI in logistics market by modernizing traditional supply chain operations. The adoption of advanced technologies such as cloud computing, Internet of Things, and big data analytics has enabled logistics companies to collect and analyze vast amounts of data in real-time. AI algorithms use this data to optimize key processes such as route planning, demand forecasting, warehousing management, etc., thereby significantly improving operational efficiency and reducing costs. Government initiatives such as Digital India are further reinforcing this change by encouraging businesses to adopt automation and digital solutions. With the growth of e-commerce and consumer demand, AI-equipped logistics solutions can justify these expectations, optimize distribution graphs, and improve customer experiences. Therefore, digital conversion is an important factor in the integration of AI, growth, and innovation in India’s logistics sector.

In August 2023, Shipsy.io, a leader in SaaS-based logistics management, launched LIA, an AI co-pilot that uses predictive intelligence to enable proactive logistics strategies. Traditional logistics incident management has been reactive, but LIA continuously monitors KPIs and alerts stakeholders in real time to prevent issues such as shipment delays and route deviations. LIA’s shift toward proactive management, improving SLAs, customer experience, and operational efficiency. This innovation is poised to benefit India’s logistics market by reducing delays, optimizing workflows, and empowering companies with real-time, AI-driven insights that meet the rising demand for seamless logistics solutions.

Retail Segment to Dominate the AI in Logistics Market Share

The retail sector holds the major share of India AI in logistics market due to the growth of e-commerce and consumer demand for faster and more efficient deliveries. Retailers are increasingly using AI solutions to optimize supply chains, simplify inventory management, and improve last-mile delivery. AI supports retailers in predicting demand, monitoring actual delivery, automating warehouses, reducing costs, and increasing operation efficiency. The integration of analysis controlled by artificial intelligence provides personalized customer experiences that contribute to the loyalty of the brand. As consumer expectations for speedy deliveries grow, the retail sector’s reliance on AI in logistics is set to expand further, positioning it as a key segment leading the adoption of AI technologies in India's logistics landscape. This transformation is driven by large retail players and startups investing in AI to stay competitive in a rapidly evolving market.

In August 2024, Mahindra Logistics Limited partnered with Sangti Solutions to launch Emission Analytics, an AI-driven tool aimed at optimizing end-to-end supply chain operations and reducing Scope 3 carbon emissions across sectors such as auto, telecom, e-commerce, and manufacturing. This collaboration aligns with Mahindra Logistics’ ESG goals to achieve a carbon-neutral supply chain by 2040, integrating solutions such as carbon-neutral warehousing, EV fleets, and sustainable fuels. Through an accredited SaaS platform, the system provides actionable emissions data, enhancing operational transparency and sustainability. This innovation strengthens India’s AI-driven logistics sector by promoting carbon-efficient practices, making the industry more resilient and environmentally responsible.

Northern India to Dominate the AI in Logistics Market Share

The northern region of India is the leader in the AI-driven logistics market due to its robust infrastructure, governmental support, and proximity to the industrial hubs. Delhi, Gurugram, and Noida have become the innovation centers of technology, and many startups and established firms are investing in AI-enabled solutions for logistics. Good transportation networks, such as highways, railways, and airports, improve the effectiveness of logistics operations. Further government policies such as Digital India and Make in India further promote AI and automation in all sectors, supporting logistics growth. The thrust for decreasing operational costs and optimizing the supply chain has made northern Indian logistics quickly embrace AI technologies, making it an industry leader in this segment.

In June 2024, ClickPost, a logistics intelligence platform for online retailers, secured USD 6 million in Series A funding led by Inflexor Ventures and Athera Venture Partners with participation from Riverwalk Holdings and Rebright Partners. The funding will support the launch of new AI-driven modules, global expansion, and hiring, enabling direct-to-consumer brands to compete against larger players like Amazon. This investment reflects the growing demand for efficient logistics solutions, positioning ClickPost to enhance India’s AI capabilities in logistics, thereby supporting the expanding e-commerce landscape.

Future Market Scenario (FY2025 – FY2032F)

AI enables more efficient supply chain management by forecasting demand, optimizing routes, and managing inventory levels in real time, leading to reduced costs and improved service levels.

The rise of autonomous vehicles and AI-enabled drones will revolutionize last-mile delivery, increasing speed, and reducing labor costs while improving customer satisfaction through faster service.

AI provides vehicle maintenance and equipment predictive analysis and identifies problems before leading to dysfunction, minimizing downtime and reducing dysfunction.

AI can contribute to more individual logistics solutions, provide individual distribution options, and improve monitoring and communication abilities to improve customer participation.

Key Players Landscape and Outlook

Companies in India AI in logistics market are using advanced technologies to streamline operations, reduce costs, and improve customer satisfaction. They are focusing on integrating AI-based solutions such as predictive analytics, machine learning, and automation to optimize supply chain processes to improve inventory management and stock planning. Many companies invest in cars, drones, and robots to reduce human intervention and increase work efficiency. The actual surveillance system using AI can enhance transparency when companies minimize delays and disability and speed up supply. Companies are using AI to forecast demand, manage warehouse operations more efficiently, and reduce energy consumption. Strategic partnerships with technology companies are also essential for businesses to stay competitive and adapt to a rapidly changing environment.


1. Project Scope and Definitions
2. Research Methodology
3. Executive Summary
4. Voice of Customer
4.1. Product and Market Intelligence
4.2. Mode of Brand Awareness
4.3. Factors Considered in Purchase Decisions
4.3.1. Technological Advancements
4.3.2. Performance and Capability
4.3.3. Technology Integration
4.3.4. Safety Features
4.3.5. Ease of Use
4.3.6. Durability and Reliability
4.4. Consideration of Privacy and Regulations
5. Global Heavy Construction Equipment Market Outlook, 2017-2031F
5.1. Market Size Analysis & Forecast
5.1.1. By Value
5.1.2. By Volume
5.2. Market Share Analysis & Forecast
5.2.1. By Machinery Type
5.2.1.1. Earthmoving Equipment
5.2.1.2. Material Handling Equipment
5.2.1.3. Heavy Construction Vehicles
5.2.1.4. Others
5.2.2. By Propulsion
5.2.2.1. Diesel
5.2.2.2. CNG/LNG/RNG
5.2.2.3. Electric
5.2.3. By Horsepower
5.2.3.1. Below 100 hp
5.2.3.2. 100 to 500 hp
5.2.3.3. Above 500 hp
5.2.4. By Application
5.2.4.1. Excavation and Demolition
5.2.4.2. Heavy Lifting
5.2.4.3. Material Handling
5.2.4.4. Tunneling
5.2.4.5. Transportation
5.2.4.6. Recycling and Waste Management
5.2.5. By End-user Industry
5.2.5.1. Building and Construction
5.2.5.2. Forestry and Agriculture
5.2.5.3. Infrastructure
5.2.5.4. Mining
5.2.5.5. Others
5.2.6. By Region
5.2.6.1. North America
5.2.6.2. Europe
5.2.6.3. Asia-Pacific
5.2.6.4. South America
5.2.6.5. Middle East and Africa
5.2.7. By Company Market Share Analysis (Top 5 Companies and Others – By Value, 2023)
5.3. Market Map Analysis, 2023
5.3.1. By Machinery Type
5.3.2. By Propulsion
5.3.3. By Horsepower
5.3.4. By Application
5.3.5. By End-user Industry
5.3.6. By Region
6. North America Heavy Construction Equipment Market Outlook, 2017-2031F*
6.1. Market Size Analysis & Forecast
6.1.1. By Value
6.1.2. By Volume
6.2. Market Share Analysis & Forecast
6.2.1. By Machinery Type
6.2.1.1. Earthmoving Equipment
6.2.1.2. Material Handling Equipment
6.2.1.3. Heavy Construction Vehicles
6.2.1.4. Others
6.2.2. By Propulsion
6.2.2.1. Diesel
6.2.2.2. CNG/LNG/RNG
6.2.2.3. Electric
6.2.3. By Horsepower
6.2.3.1. Below 100 hp
6.2.3.2. 100 to 500 hp
6.2.3.3. Above 500 hp
6.2.4. By Application
6.2.4.1. Excavation and Demolition
6.2.4.2. Heavy Lifting
6.2.4.3. Material Handling
6.2.4.4. Tunneling
6.2.4.5. Transportation
6.2.4.6. Recycling and Waste Management
6.2.5. By End-user Industry
6.2.5.1. Building and Construction
6.2.5.2. Forestry and Agriculture
6.2.5.3. Infrastructure
6.2.5.4. Mining
6.2.5.5. Others
6.2.6. By Country Share
6.2.6.1. United States
6.2.6.2. Canada
6.2.6.3. Mexico
6.3. Country Market Assessment
6.3.1. United States Heavy Construction Equipment Market Outlook, 2017-2031F*
6.3.1.1. Market Size Analysis & Forecast
6.3.1.1.1. By Value
6.3.1.1.2. By Volume
6.3.1.2. Market Share Analysis & Forecast
6.3.1.2.1. By Machinery Type
6.3.1.2.1.1. Earthmoving Equipment
6.3.1.2.1.2. Material Handling Equipment
6.3.1.2.1.3. Heavy Construction Vehicles
6.3.1.2.1.4. Others
6.3.1.2.2. By Propulsion
6.3.1.2.2.1. Diesel
6.3.1.2.2.2. CNG/LNG/RNG
6.3.1.2.2.3. Electric
6.3.1.2.3. By Horsepower
6.3.1.2.3.1. Below 100 hp
6.3.1.2.3.2. 100 to 500 hp
6.3.1.2.3.3. Above 500 hp
6.3.1.2.4. By Application
6.3.1.2.4.1. Excavation and Demolition
6.3.1.2.4.2. Heavy Lifting
6.3.1.2.4.3. Material Handling
6.3.1.2.4.4. Tunneling
6.3.1.2.4.5. Transportation
6.3.1.2.4.6. Recycling and Waste Management
6.3.1.2.5. By End-user Industry
6.3.1.2.5.1. Building and Construction
6.3.1.2.5.2. Forestry and Agriculture
6.3.1.2.5.3. Infrastructure
6.3.1.2.5.4. Mining
6.3.1.2.5.5. Others
6.3.2. Canada
6.3.3. Mexico
*All segments will be provided for all regions and countries covered
7. Europe Heavy Construction Equipment Market Outlook, 2017-2031F
7.1. Germany
7.2. France
7.3. Italy
7.4. United Kingdom
7.5. Russia
7.6. Netherlands
7.7. Spain
7.8. Turkey
7.9. Poland
8. Asia-Pacific Heavy Construction Equipment Market Outlook, 2017-2031F
8.1. India
8.2. China
8.3. Japan
8.4. Australia
8.5. Vietnam
8.6. South Korea
8.7. Indonesia
8.8. Philippines
9. South America Heavy Construction Equipment Market Outlook, 2017-2031F
9.1. Brazil
9.2. Argentina
10. Middle East and Africa Heavy Construction Equipment Market Outlook, 2017-2031F
10.1. Saudi Arabia
10.2. UAE
10.3. South Africa
11. Demand Supply Analysis
12. Import and Export Analysis
13. Value Chain Analysis
14. Porter’s Five Forces Analysis
15. PESTLE Analysis
16. Pricing Analysis
17. Market Dynamics
17.1. Market Drivers
17.2. Market Challenges
18. Market Trends and Developments
19. Case Studies
20. Competitive Landscape
20.1. Competition Matrix of Top 5 Market Leaders
20.2. SWOT Analysis for Top 5 Players
20.3. Key Players Landscape for Top 10 Market Players
20.3.1. Caterpillar Inc.
20.3.1.1. Company Details
20.3.1.2. Key Management Personnel
20.3.1.3. Products and Services
20.3.1.4. Financials (As Reported)
20.3.1.5. Key Market Focus and Geographical Presence
20.3.1.6. Recent Developments/Collaborations/Partnerships/Mergers and Acquisition
20.3.2. Volvo CE (Volvo Group)
20.3.3. Komatsu Ltd.
20.3.4. Hitachi Construction Machinery Co. Ltd
20.3.5. Xuzhou Construction Machinery Group Co., Ltd. (XCMG)
20.3.6. SANY Heavy Industry Co. Ltd.
20.3.7. Liebherr-International Deutschland GmbH
20.3.8. HD Hyundai Heavy Industries Co. Ltd.
20.3.9. J C Bamford Excavators Ltd (JCB)
20.3.10. Kobelco Construction Machinery Co. Ltd.
*Companies mentioned above DO NOT hold any order as per market share and can be changed as per information available during research work.
21. Strategic Recommendations
22. About Us and Disclaimer

Download our eBook: How to Succeed Using Market Research

Learn how to effectively navigate the market research process to help guide your organization on the journey to success.

Download eBook
Cookie Settings