The future of logistics: How generative AI and agentic AI is creating a new era of efficiency and innovation

The logistics industry has been the backbone of global trade but has been facing a growing list of challenges: economic uncertainty, supply chain disruptions, rising costs, and increasingly complex regulatory requirements are putting pressure on businesses. At the same time, operations remain highly fragmented, making it difficult for companies to maintain efficiency and agility.

Historically, logistics has lagged other industries in digital transformation. More than 75% of industry leaders acknowledge that their sector has been slow to embrace digital innovation. Instead of prioritizing digital transformation, companies have traditionally focused on incremental improvements in operational processes. But in today’s fast-moving market, this approach is no longer enough as customer expectations have also evolved dramatically. A staggering 91% of logistics firms report that their clients now demand seamless, end-to-end logistics services from a single provider.¹

AI has become a game-changer for the industry to help overcome challenges and fulfill customer expectations. From enhancing customer experiences—such as shipment planning and service requests—to driving productivity in core supply chain operations and demand forecasting, AI presents a massive opportunity. AI can also improve safety, sustainability, and workforce reskilling, giving employees more time to focus on customers. The numbers speak for themselves: AI-powered innovations could reduce logistics costs by 15%, optimize inventory levels by 35%, and boost service levels by 65%. Over the next two decades, AI adoption in logistics could generate between $1.3 trillion and $2 trillion per year in economic value.²

Microsoft for travel and transportation

In fact, the AI revolution in logistics is already underway, and Microsoft is at the forefront, empowering businesses with Azure’s cloud capabilities and cutting-edge AI solutions.

With this article, Microsoft releases two new reference architectures—Adaptive Cloud for Logistics and Supply Chains and AI-enhanced experiences for Logistics and Supply Chain, enhanced functionalities in Dynamics 365 for Supply Chain, and showcases partner-led offerings.

The use cases

What are the use cases that AI can impact in logistics? The answer is simple: Almost everywhere along the value chain. This covers inbound logistics and outbound logistics as well as supporting activities, see the overview below:

Diagram of multiple AI use cases possible across the logistics value chain.

Inbound logistics

One of the most critical use cases in supply chain optimization is demand forecasting. Accurate predictions by AI can serve as the foundation for downstream activities—driving efficiency and enhancing overall optimization. For example, precise demand forecasts play a key role in inventory management and storage optimization within warehouse management systems.

SPAR Austria, a leading food retailer with over 1,500 stores, has significantly improved its demand forecasting capabilities through AI-powered solutions built on Microsoft Azure in collaboration with Microsoft partner Paiqo. This advanced implementation has achieved more than 90% forecast accuracy, leading to a 15% reduction in costs by minimizing waste.

AI-based route optimization can lead to significant fuel cost reductions, which is a substantial cost-saving measure for logistics companies and contributes to sustainability goals. Load management algorithms and real-time data analytics maximize space utilization in trucks, vessels, and warehouses.

Additionally, AI-based scheduling, booking, shipping, and invoicing have significant impact on flexibility, cost, and operational process efficiency.

Dow Chemical, a global leader in materials science, faced significant challenges with its existing freight invoicing system, which involved up to 4,000 daily shipments and various types of invoices. A newly developed invoice agent built with Microsoft Copilot Studio streamlines the company’s freight invoicing process by monitoring incoming emails for attached invoices, structures the data for analysis, and scans for billing inaccuracies. This automation helps Dow manage its logistics spending more efficiently, reducing potential overpayments and improving operational efficiency.

Outbound logistics

AI and robotics play a crucial role in optimizing picking and packing processes. Additionally, advancements in technology enhance order processing and returns management—streamlining operations and driving cost reductions.

Cutting-edge technologies like natural language processing (NLP) and machine learning are transforming customer interactions by reducing handling times and associated costs. With the deployment of virtual assistants and every day customer support, businesses can improve response times significantly.

Global sports retailer Decathlon, in partnership with Microsoft partner Parloa, has successfully leveraged AI to enhance customer service. By implementing AI-powered solutions, the company has reduced the number of calls forwarded to live agents by 20%, demonstrating the power of automation in improving efficiency and streamlining customer interactions.

Supporting activities

AI and emerging technologies are transforming key support processes across the logistics value chain. In procurement and pricing, for example, AI-powered agents streamline the request for proposal (RFP) and request for quote (RFQ) process. Additionally, dynamic pricing capabilities optimize revenue management, while AI-powered advancements enhance traditional finance and controlling functions. AI also plays a crucial role in simplifying customs management and ensuring seamless regulatory compliance.

Below is an overview of solutions from independent software vendors (ISVs) and partners that can be leveraged out-of-the-box for selected use cases:

Wandelbots: Robotics for picking and packing
Paiqo: Demand forecast
InstaDeep: Load optimization
Fareye: Route planning and optimization
Parloa: Customer service
Coneksion: Messaging
CH Robinson: Mail AI agents
Cosmotech: Supply chain simulation

3 building blocks for a digitized state-of-the-art logistics

From a Microsoft perspective, there are three key building blocks for logistics and supply chain companies to build an AI-ready platform that can enable a variety of use cases:

Adaptive Cloud: The modular base infrastructure
Microsoft adaptive cloud unifies siloed teams, distributed sites, and sprawling systems into a single operations, security, application, and data model across hybrid, multi- cloud, edge, and Internet of Things (IoT) environments.
Microsoft Dynamics 365 suite: Microsoft’s comprehensive business suite
Dynamics 365 suite, including Supply Chain Management, offers comprehensive solutions to enhance visibility, streamline procurement, optimize fulfillment, and improve planning.
AI and agentic AI: Solutions to automate business processes
Microsoft offers advanced agentic AI solutions which enable the creation and orchestration of agent- and multi-agent systems for enhanced productivity and automation.

Adaptive cloud: The modular base infrastructure

Within the logistics domain, adaptive cloud can address multiple areas for increased efficiency such as quality control, warehouse operations, damage detection, or robotics automation. With the capabilities of the full Azure stack on the edge, IoT operations, and a data fabric, adaptive cloud is the essential lever for improving business both in the cloud and on the edge.

Diagram of Adaptive cloud and connected facilities

Adaptive cloud shifts organizations from a reactive posture to one of proactive evolution, enabling people to anticipate and act upon changes in market trends, customer needs, and technological advancements ahead of time. This strategic foresight enables businesses to pivot quickly, embrace continuous improvement, and integrate new technologies smoothly. By building resilience into their operational models, businesses can optimize resource usage and mitigate risks before they manifest.

The adaptive cloud can be adapted or selectively applied to multiple customer scenarios. We map how commitments and promises are realized by system skills and capabilities below:

Operate with AI-enhanced central management
Elevate IT capabilities and focus on strategic work by abstracting resources from distributed locations into one operations and management layer with AI assistance and automation.
Critical capabilities:
- Universal AI assistant, portal, and tools
- Consistent configuration management
- End-to-end observability
- Governance at scale
- Built-in security and control
Rapidly develop and scale applications across boundaries
Bridge OT and IT gap to transcend legacy system constraints with composable cloud-native tool chains, containers, and data services everywhere.
Critical capabilities:
- Kubernetes everywhere
- Hyperscale cloud services to the edge
- Central application deployment
- Global orchestration and resiliency
- Streamlined DevOps integration
Cultivate data and insights across physical operations
Supercharge physical operations with a unified data foundation, enabling efficient workflows, predictive insights, and cost-effective resource utilization from edge to cloud.
Critical capabilities:
- Common data foundation
- Actionable insights with AI Coordinated workflow orchestration from edge to cloud
- Contextualized data to information
- Centralized device management

Dynamics 365 suite: Microsoft’s comprehensive business suite

The Dynamics 365 Supply Chain Management portfolio outlines various stages and components of the supply chain process, divided into several categories, from design to decommission to record to report. The table below indicates the bandwidth of the suite capabilities:

Microsoft Copilot enhances supply chain management by leveraging AI and automation. By integrating Dynamics 365 with AI-powered Copilot, organizations can significantly enhance their supply chain management processes. The combination of advanced AI capabilities and comprehensive business applications ensures that supply chain operations are efficient, responsive, and adaptive to changing conditions.

The new Warehouse Management Only Mode is a specialized feature within Microsoft Dynamics 365 Supply Chain Management (and can also be used standalone) designed to cater specifically to warehouse management processes. This mode allows businesses to set up a legal entity dedicated solely to warehouse operations, providing warehousing services to other legal entities within Supply Chain Management or even to external enterprise resource planning (ERP) and order management systems.

AI and agentic AI: Solutions to automate business processes

The new AI-enhanced reference architecture for logistics brings it all together—from the connection to existing data systems to AI-enhanced experiences for various user groups like end-customers, warehouse managers, fleet managers, or customer service:

A diagram of Industry Reference Architecture for Logistics and Supply Chain

The user-facing applications layer describes some of the common front-end experiences that can be built using Microsoft services. End users require mobile and web applications built using services such as Azure API Management, Azure App Service, and Azure Functions. Developers create AI-powered user experiences leveraging services such as Azure OpenAI Service. These applications can be deployed in Azure tenants and can scale to millions of users.

Business users leverage Dynamics 365 (including Dynamics 365 Customer Service, Dynamics 365 Finance, Dynamics 365 Project Operations, and Dynamics 365 Customer Insights) to manage business operations such as claims, promotions, and ticketing. Dynamics 365 has built-in custom agents for many common business use cases such as customer service, sales, finance, field service, and customer insights.

Front line workers are fully integrated into the business with customized workflows and automated operations with custom AI, tailored to their needs and the ergonomics of their workplaces, whether fixed terminals, mobile devices, or augmented reality. 

Microsoft Copilot Studio facilitates the creation of custom AI agents to support their work. Power Apps enable the creation of custom user interfaces, while Power Automate enables the creation of business workflows. With Microsoft 365 Copilot, employees can collaborate and communicate using Microsoft products such as Microsoft Teams, SharePoint, and Outlook.

The operation of supply chain and logistics generates large amounts of data. The data storage and analytics layer describe how to securely store business data to support operations and create insights.

Microsoft Dataverse is a scalable data platform that securely stores and manages business data. The data model is a structured framework that organizes data in tables with relationships. It is possible to use industry models to harmonize and integrate business data across multiple applications. 

Microsoft Fabric is an end-to-end data and analytics platform that includes real-time analytics capabilities. OneLake is a unified logical data lake that centralizes and simplifies data management, with multiple analytical engines and workspaces. Fabric enables organizations to process and analyze data for timely insights and decision-making. Supply chain and logistics are established businesses. It is important to integrate existing data systems, such as connected assets as well as existing systems.

Messaging services on Azure enable connectivity to assets and devices using standardized communication protocols such as Message Queuing Telemetry Transport (MQTT) with Azure Event Grid, or data streams like Apache Kafka using Azure Event Hubs. Serverless solutions like Azure Functions provide compute to process messages.

Get in touch with us

Customers can work directly with Microsoft Industry Solutions teams on custom projects that offer a short go-to-market time. Whether you choose ready-to-deploy partner solutions or bespoke projects with Microsoft partners or Microsoft Industry Solutions, we provide the expertise and support to ensure your success.

Visit Microsoft for travel and transportation or contact our team to learn more and take the next step in your Microsoft AI journey.