Solutions
Ecommerce
Empower customers with self-service, letting your team grow your business.
Replenishment
Scale your purchasing center to boost productivity and expand your network.
B2B Marketplace
Streamline operations, expand reach, and enhance relationships.
DJUST Pay
Choose seamless and customised B2B payments
Customers
Partners
Company
About us
Meet the team
Careers
Resources
Blog
Simplify B2B eCommerce and boost productivity with our strategies and insights.
eBooks
Download free B2B eCommerce ebooks with tips, guides, and best practices.
White Paper
Discover B2B growth strategies with case studies and expert insights.

Webinar
Explore webinars on B2B trends, expert advice, and the DJUST platform.
Glossary
Discover key B2B eCommerce terms, their definitions, and their relevance for your business.
EN
FR
Request a demo
Blog
Order Management
AI in supply chain & logistics integration
Order Management
6
min read

published on

March 17, 2025

AI in supply chain & logistics integration

Start using our RFP template

In this article:

Book a meeting with our product experts and understand how DJUST can transform your business.
Request a demo

AI-powered order management system and supply chain synchronization

The rapid advancement of artificial intelligence (AI) is transforming supply chain management, particularly in the synchronization of order management systems (OMS) with logistics networks. AI-powered solutions enable real-time communication, predictive analytics, and automated decision-making to enhance efficiency, reduce errors, and optimize workflows. These innovations are essential for any b2b ecommerce platform looking to streamline b2b inventory management and improve supply chain planning.

How AI improves OMS and supply chain communication

  1. Real-time data processing: AI facilitates seamless data exchange between OMS and supply chain networks, ensuring that inventory levels, demand forecasts, and order statuses are updated in real time (Ivanov & Dolgui, 2021). This is particularly relevant for enterprise ecommerce platforms that require accurate stock updates.
  2. Predictive analytics: Machine learning algorithms analyze historical and real-time data to forecast demand fluctuations, allowing businesses to adjust procurement and production accordingly (Choi et al., 2022). This contributes to ecommerce automation, reducing human intervention and errors.
  3. Automated order fulfillment: AI enhances automation in warehousing and logistics, reducing manual intervention and improving order accuracy (Speranza, 2018). This is a key part of any b2b ecommerce strategy.
  4. AI-driven decision support: AI assists supply chain managers in making data-driven decisions, such as rerouting shipments to avoid bottlenecks or identifying the best fulfillment center for an order (Min, 2022). This level of efficiency is crucial for b2b wholesale operations.

Case study: Amazon’s AI-integrated supply chain

Amazon’s AI-driven fulfillment system integrates machine learning to predict demand, manage inventory, and optimize last-mile delivery. This results in faster shipping, reduced costs, and increased customer satisfaction (Brynjolfsson & McAfee, 2017), setting a benchmark for b2b marketplace optimization.

 

Reducing delivery delays with AI in order management

Delivery delays pose a significant challenge for businesses and consumers. AI enhances order management by predicting potential disruptions and proactively rerouting shipments to ensure timely deliveries, a must-have feature for any ecommerce growth strategy.

AI’s role in reducing delays

  1. Demand-supply forecasting: AI predicts demand spikes and adjusts inventory allocation to prevent stockouts and overstock situations (Fahimnia et al., 2015). This supports supply chain planning for b2b sales.
  2. Dynamic routing optimization: AI-powered route optimization systems adjust delivery routes in real-time based on traffic patterns, weather conditions, and unforeseen disruptions (Tan et al., 2020). B2b shipping providers use this to ensure efficient logistics.
  3. Proactive issue resolution: AI-driven anomaly detection identifies potential delays by analyzing logistics data and triggers automated contingency plans (Baryannis et al., 2019). This is critical for b2b partner programs that rely on seamless logistics.
  4. Autonomous last-mile delivery: AI integrates with autonomous vehicles and drones to improve last-mile delivery efficiency, reducing reliance on human drivers (Winkenbach, 2021). This technology plays a role in b2b digital transformation.

Example: DHL’s AI-enhanced logistics

DHL uses AI-powered predictive analytics to anticipate shipment delays, allowing the company to take preemptive action. This has improved on-time deliveries and enhanced customer satisfaction (Christopher, 2016). Such advancements can also aid in b2b payment processing by ensuring smoother transactions and accurate delivery estimates.

 

AI-driven sustainability in order management

Sustainability is a growing concern in supply chain management. AI-driven solutions optimize packaging, routing, and fulfillment strategies to minimize environmental impact while aligning with b2b ecommerce trends.

AI’s contribution to sustainable order management

  1. Eco-friendly packaging optimization: AI analyzes order compositions to recommend minimal and sustainable packaging materials, reducing waste (Björklund et al., 2016). This is crucial for b2b product marketing and responsible supply chain operations.
  2. Carbon footprint reduction via route optimization: AI-powered logistics software minimizes fuel consumption by selecting the most efficient delivery routes (McKinnon et al., 2018), an essential feature for b2b lead generation strategies focused on sustainability.
  3. Smart warehousing for energy efficiency: AI optimizes warehouse layouts and automation to reduce energy consumption (Van der Vorst & Beulens, 2018). This contributes to ecommerce security and compliance.
  4. AI-enabled reverse logistics: AI streamlines return processes, promoting circular economy practices and reducing landfill waste (Govindan et al., 2015), a feature that enhances b2b customer experience.

Example: UPS’s AI-driven sustainability initiatives

UPS employs AI in its ORION (On-Road Integrated Optimization and Navigation) system to optimize delivery routes, reducing fuel consumption and CO2 emissions significantly (Speranza, 2018). This innovation can serve as a model for b2b personalization in logistics.

 

AI’s integration into supply chain and logistics management is revolutionizing order management, reducing delays, and promoting sustainability. Companies leveraging AI-powered OMS and logistics synchronization gain competitive advantages by improving efficiency, reducing costs, and meeting environmental goals. This is critical for companies engaged in digital transformation and those leveraging ecommerce personalization to optimize operations.

 

References

  • Baryannis, G., Dani, S., & Antoniou, G. (2019). Predictive analytics for supply chain risk management. International Journal of Production Research, 57(7), 2212-2229.
  • Björklund, M., Martinsen, U., & Abrahamsson, M. (2016). Sustainability in logistics and supply chain management. Business Strategy and the Environment, 25(6), 389-401.
  • Brynjolfsson, E., & McAfee, A. (2017). Machine, Platform, Crowd: Harnessing Our Digital Future. W. W. Norton & Company.
  • Choi, T. M., Wallace, S. W., & Wang, Y. (2022). Big data analytics in operations management. Production and Operations Management, 31(3), 1201-1215.
  • Christopher, M. (2016). Logistics & Supply Chain Management. Pearson.

Frequently Asked Questions

No items found.
About the author
Arnaud Rihiant
Founder & CEO @ DJUST

Expert in topics on B2B, eCommerce, market trends, business strategy

Explore:
Order Management
AI
Payments
B2B Sales
eCommerce
DJUST News
B2B Marketing
Operations
Payments
8
Min read
Published on
March 27, 2025

Why CFOs Should Rethink the Role of Payments in Business Growth

In many companies, payments have been treated as little more than a mechanical necessity — the final administrative step in the transaction cycle. But that perception is rapidly changing. In an era where digital commerce is the default, CFOs are beginning to understand the power of payments not just as a financial function, but as a lever for business growth, customer loyalty, and competitive advantage. Reframing payments in this way isn’t just about digitizing processes — it’s about transforming how the business thinks about value creation.
AI
6
Min read
Published on
March 26, 2025

How AI-Powered Sustainable Supply Chains Are Reshaping B2B Commerce

As the pressure mounts on businesses to reduce their environmental impact, sustainability is no longer a soft ambition but a hard requirement—especially in B2B commerce, where supply chains are vast, complex, and often opaque. Artificial Intelligence (AI), long heralded for its potential to streamline operations and reduce costs, is now stepping into a new role: sustainability enabler.From predictive demand planning to real-time emissions tracking, AI technologies are beginning to recalibrate how B2B organizations design and manage their supply chains. But how far can algorithms go in driving environmental impact, and what does this mean for procurement, logistics, and operations leaders?
Payments
6
Min read
Published on
March 26, 2025

How CFOs Can Turn B2B Payments into a Growth Strategy

In many companies, payments have been treated as little more than a mechanical necessity — the final administrative step in the transaction cycle. But that perception is rapidly changing. In an era where digital commerce is the default, CFOs are beginning to understand the power of payments not just as a financial function, but as a lever for business growth, customer loyalty, and competitive advantage.Reframing payments in this way isn’t just about digitizing processes — it’s about transforming how the business thinks about value creation.