AI in 3PL: Reinforcing the Backbone of Modern Commerce

Used by about 46% of third-party logistics providers (3PL), AI in 3PL has become a major transformative force across the industry. Equipped with exclusive personalization and data harnessing features, the technology allows third-party companies to keep up with the ever-evolving demands and increasing complexity of businesses’ supply chain, while revealing opportunities for new strategies and approaches.

This article provides comprehensive insights into the current status of 3PL AI, its role in the sector, breaking down the key advantages and use cases.

The role of AI in modern logistics

The application of artificial intelligence in logistics is primarily associated with robotics, painting pictures of self-driving vehicles, fully automated warehouses, and robots taking over the most hazardous tasks. While companies actively explore the prospect of robotization and autonomous truck fleets, this part of AI extends well beyond these directions.

The main challenge of logistics is pressure. The landscape is very dynamic, companies and manufacturers constantly have to deal with new variables, so its highly important to be responsive. Artificial intelligence makes this possible by effectively speeding up every process and supplying you with unseen data that turns the tables on your logistics operations.

Dmytro Ivanov, Machine Learning Engineer at Trinetix 

The idea of robots and autonomous vehicles is appealing, but currently, transportation remains mostly a task performed by humans—and it's likely to stay that way.

According to the DHL Logistics Trend Radar, the main AI-powered changes are happening in several other areas, enabling greater clarity, readiness, and security.

AI in logistics use cases

• Improving forecasting with AI analytics
  Accurate prediction of behaviors, risks, and external factors (such as weather events, political, or social conflicts) requires massive amounts of data collected from diverse sources and analyzed within seconds. Modern AI models and systems are capable of accomplishing these tasks and translating data into ready-to-use forecasting insights for logistics services. This enables logistics companies to plan ahead, optimize operations, resources, and inventories, and remain resilient to potential challenges.
   
  
  
• Preventing workplace accidents and thefts with computer vision
  With a 20% increase in serious injury rates between 2018 and 2022, warehousing and transportation are recognized as some of the most risk-prone areas for workers. Additionally, cargo theft cases rose by 23% in 2024, with total losses exceeding $455 million. These issues are worsened by limited visibility in warehouses and insufficient monitoring amid ongoing labor shortages. Fortunately, technology offers logistics companies effective countermeasures. By using computer vision, companies can identify inefficiencies and promptly alert workers in dangerous situations. For theft prevention, smart systems can detect and respond to suspicious behavior, instantly notifying security personnel and managers.
  
  
  
• Identifying anomalies with audio AI 
  Another vital aspect of maintaining workplace safety in warehouses and factories is detecting malfunctions before they result in accidents. However, many maintenance issues are difficult to identify in their early stages, especially in noisy and busy environments. This is where AI systems trained to analyze sounds for anomalies take center stage. From analyzing vehicle vibrations for maintenance planning to processing machinery sounds to detect hidden defects, audio AI offers a solution that can save time, resources, and—most importantly—lives.
  
  
  
• Facilitating inventory management with GenAI
  Praised for its robust content generation capabilities, GenAI has proven extremely effective in inventory management, prompting around 57% of wholesale, packaged goods, and retail executives to include GenAI tools in their planned budgets. This positive reception stems from the technology’s ability to accelerate a wide range of inventory-related processes, including product description generation, goods and layout visualization, report creation, space optimization prototyping, and customer interaction.
   
  
  
• Enabling data security with AI ethics 
  A recent breach at National Public Data, one of the largest data brokers serving multiple industries, exposed approximately 2.9 billion records to potential criminals. In addition to financial losses totaling $501.7 billion, the breach has long-term consequences that threaten the integrity of supply chains and businesses worldwide. This incident is one of many—and with cybercriminals increasingly weaponizing AI, businesses must stay ahead by leveraging AI and establishing ethical frameworks. These frameworks help identify counterfeits, prevent unauthorized access, and add critical layers of security to sensitive business data.
  
  
  
  

Key applications of AI in 3PL and logistics

AI in 3PL (Third-Party Logistics) is an umbrella term for the use of artificial intelligence technologies to automate and streamline numerous aspects of logistics operations within a 3PL provider's service offerings. This definition is important to understand and keep in mind when evaluating the need for technology and identifying the appropriate niche for its application.

 Dmytro Ivanov, Machine Learning Engineer at Trinetix 

In regard to 3PL optimization AI, the impact of technology is particularly significant. If 4PL services are responsible for the overall strategy, 3PL providers oversee the lifeblood and core of supply chains—transportation and warehousing.

Therefore, 3PL AI is often focused on maintaining robust performance in these vital areas, helping third-party providers address their key needs with surgical precision.

Benefits of AI for 3PL providers and their clients

The best thing about AI is that its capabilities are unlimited. This is particularly valuable for 3PL companies with industry-specific clients. Take, for example, 3PL providers who specialize in transporting pharmaceutical goods—this is where 3PL AI is used to monitor proper storage temperatures, prevent counterfeiting, and help keep 3PLs out of regulatory trouble.

Dmytro Ivanov, Machine Learning Engineer at Trinetix 

To understand the impact of third-party logistics AI on companies and their clientele, it is important to break down the main challenges of the niche.

• Preserving profitability
  Around 78% of third-party logistics executives name price competition as their greatest barrier to maintaining profits. While shippers demand and expect lower prices, executives face increasing fuel expenses, soaring warehouse rental costs, and labor shortages. These struggles negatively impact their pricing models, rendering them unsustainable—an undesirable outcome in a highly competitive sector.
  
  
  
  
• Adapting to faster fulfillment
  The demand for fast delivery is surging—especially in e-commerce. However, not every 3PL warehouse is equipped to meet this demand. Many warehousing environments lack the tools, technologies, and personnel needed to match the expected speed.
  
  
  
• Supply chain unpredictability
  As the global supply chain bears the brunt of multiple crises, 3PL companies are tasked with navigating new threats and complexities, mitigating risks, and building resilience. Shoppers and buyers expect stability and clarity even in the most uncertain times—and it's the responsibility of shippers and 3PL companies to deliver on those expectations.
  
  
  
• Closing the last mile
  The most critical milestone of the supply chain—the last-mile delivery—is also its most challenging. As products make their way to buyers, they can be delayed by a number of sudden issues—from last-minute route changes to poor infrastructure, to a lack of flexibility during peak season planning. Consistently failing at last-mile delivery can have a devastating effect on both the shipper’s and the provider’s reputation.
  

How does AI in 3PL resolve these challenges and elevate logistics services? 

1. Increased operational efficiency and cost savings

Currently, many businesses across numerous industries operate under the same motto: “Do more with less.” This applies not only to finances but also to other resources—time, fuel, and people.

Companies are expected to spend less money and fewer hours while preserving their employees’ energy for tasks and objectives that deliver exponentially more value, cutting away all the redundancies that drain time and funds. 

While this description may sound bleak, execution can yield many positive results—as long as the right tools are used for the right tasks. For example, 3PL optimization AI streamlines many repetitive manual processes—data entry, report generation, paperwork completion, and invoice creation—helping workers accomplish more tasks in fewer man-hours.

Dmytro Ivanov, Machine Learning Engineer at Trinetix 

3PL AI plays a pivotal role in reducing costs while maintaining high performance and employee satisfaction.

• Unforeseen expense prevention
  Reducing the risk of accidents, thefts, and other incidents that lead to unplanned expenses has a significant impact on a company’s budget and savings. This allows more funds to be directed toward new profit opportunities and meaningful workplace improvements.
  
  
  
• Tackling labor shortages
  From 3PL warehouse automation to conversational assistance, the introduction of AI tools in logistics services facilitates process management. These tools help employees handle more tasks, communicate effectively throughout their work, and stay updated on progress. AI assistants can also support fast and efficient training for new employees by providing a wide range of scenarios and keeping workers informed about relevant laws and regulations.
  
  
  
• Optimizing resource consumption
  3PL AI tools for real-time route monitoring are extremely effective in reducing fuel consumption. Integrated into 3PL workflows, they help truckers and fleet managers track route changes, identify alternative paths, and stay on schedule—while conserving resources.

2. More efficient order fulfillment

A well-informed application of AI can transform a traditional 3PL warehouse into an upgraded hub for modern operations.

Third-party logistics providers can leverage the technology to enhance visibility through analytics, enabling them to plan deliveries down to the smallest detail. At the same time, they can automate time-consuming processes with AI agents and improve quality control and warehouse layouts using computer vision.

Effectively, third-party logistics AI can be implemented at every stage of order fulfillment—ensuring faster checks, greater package integrity, and allowing workers to focus their efforts exactly where they’re needed.

3. Greater supply chain resilience and risk management

Uncertainty is the greatest enemy of modern supply chain management. Fortunately, AI helps keep uncertainty at bay.

Third-party logistics AI includes a wide range of tools and systems for monitoring and analyzing various factors that impact delivery speeds and transportation procedures.  

4. Enhanced customer experience with AI-powered support

Trust is the foundation of successful partnerships. Since 3PL customers are manufacturers and shippers who rely on third-party providers to store and transport their goods safely and on time, maintaining transparency and trust-based communication is crucial for both sides.

This is especially important in today’s logistics environment, where many organizations are re-evaluating their approaches and becoming more critical of their providers. In 2025, 89% of shippers reported being satisfied with their relationships—a 6% decrease compared to 2024. Additionally, 61% of shippers acknowledged that their 3PL partners’ change management skills played a significant role in their collaboration.

These numbers highlight the following priorities for 3PL providers:

• Preserving customer trust 
  3PL clients aren’t exactly losing trust in their providers, but they are becoming more hesitant—partly due to geopolitical instability and partly because of negative examples where 3PL companies cut corners by reducing spending on essential procedures like safety, quality control, and transportation.
  
  It’s up to 3PL providers to maintain strong relationships with their customers and reassure them of their resilience and commitment. Third-party logistics AI plays a key role in this effort by equipping 3PL supply chains with insights and tools to counter sudden disruptions and mitigate risks.

It’s no secret that every client wants to work with a provider who knows what they’re doing—and who can stay confident and capable even when the broader business landscape is uncertain. 3PL logistics technology enables companies to be that kind of provider. In fact,74% of shippers are willing to reconsider their current partnerships in favor of a 3PL organization with stronger AI capabilities.

Dmytro Ivanov, Machine Learning Engineer at Trinetix  

• Enabling greater transparency for shippers
  Shippers want to stay informed about the status of their shipments every step of the way. They expect to be notified of any changes or updates so they can provide more detailed and confident reports to their buyers—and secure their trust in return. With the help of 3PL AI, third-party providers can make that happen.
  
  By leveraging intelligent virtual assistants that monitor shipment journeys and deliver timely updates, 3PL companies can keep their clients informed and supply them with the information they need to keep their own customers satisfied. 
  
  
  
• Securing greater offerings for clients
  Preserving and expanding partnerships has never been more crucial in the highly competitive logistics industry. 3PL companies need to do more than maintain their current productivity—they must go further, anticipating what their clients (and their clients’ clients) will need in the coming months, and how their demands and expectations may shift due to geopolitical events and other factors. Meeting this challenge requires continuous improvement, which in turn depends on a deep understanding of core supply chain processes and 3PL operations.
  
  In this context, AI in 3PL serves as the provider’s eyes—running detailed analyses of every relevant activity and pattern, monitoring warehouse layouts, and detecting anomalies in real time.

The future of AI in third-party logistics (3PL): preparedness is the key

AI is effectively the future of 3PL logistics technology. It’s no secret that operational complexities and emerging global instabilities will continue to impact supply chains worldwide with long-lasting effects. While third-party logistics organizations can’t eliminate the root causes of these issues, they do have the tools and technologies to adapt and overcome many of the resulting challenges.

3PL AI is expected to evolve rapidly, offering greater capacity and more advanced features to help companies maintain operational efficiency and a competitive edge—no matter how challenging the environment becomes.

The question is: how can 3PL providers prepare and ensure they’re AI-ready?

• Review and prepare enterprise data in advance 
  Third-party logistics AI—especially GenAI—delivers exceptional value by transforming unstructured data into powerful, actionable insights. However, it only works effectively when enterprises have a solid data management strategy in place. On its own, AI can’t identify and process relevant unstructured information—it must be trained to do so.
  
  That’s why AI adoption should be preceded by the implementation of modern data management practices and principles.
  
  
  
• Identify last-mile delivery hurdles
  Optimizing last-mile delivery is essential for logistics enterprises, and AI can be a powerful tool for eliminating inefficiencies. But before deploying AI, organizations need to closely examine recurring issues that disrupt last-mile delivery operations.
  
  By gathering feedback from workers, evaluating warehouse and delivery point proximity, and analyzing this data, companies can build a clearer picture of the problems they want their 3PL AI to solve. 
  
  
  
• Work with trusted technology consultancies 
  Established 3PL providers possess years of accumulated experience and domain knowledge. This expertise is one of their most valuable assets—and it becomes even more powerful when translated into digital capabilities. However, due to labor shortages and resource constraints, not all 3PL companies have the internal capacity to digitize and transfer this knowledge effectively.
  
  That’s where digital transformation consultancies with logistics expertise come in. These partners can provide the talent and support needed to equip 3PL enterprises with knowledge-driven AI solutions.

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If you’re preparing your 3PL company for the current and future milestones, let’s chat!

Operating globally, Trinetix has helped numerous 3PL leaders harness the full potential of GenAI, machine learning, and cutting-edge logistics technology to boost operational capacity, enable smarter management, and drive revenue growth. By partnering with our AI engineers, ML experts, and business analysts, you’ll receive a personalized approach to 3PL optimization AI and a solution tailored to your long-term goals.