AI Revolutionizing Transportation & Logistics Back-Office Operations
This story first appeared in the July/August issue of Supply Chain Xchange, a journal of thought leadership for the supply chain management profession and a sister publication to AGiLE Business Media & Events’ DC Velocity.
Despite transportation and logistics’ (T&L) critical role in global commerce, the industry has long struggled with inefficiencies, particularly in back-office operations. Manual invoice processing, for instance, remains a major pain point, with discrepancies in freight rates, accessorial charges, and payment terms requiring labor-intensive reconciliation—often delaying settlements by weeks. Similarly, shipment tracking often relies on fragmented systems, forcing employees to cross-reference emails, spreadsheets, and legacy databases to resolve exceptions like delays or damaged goods. Even routine tasks, such as carrier contract compliance checks or customs documentation, are prone to human error, leading to costly penalties and operational bottlenecks.
Given these persistent challenges, could artificial intelligence (AI) be the answer? By automating repetitive tasks—such as invoice validation, exception alerts, and document processing—AI has the potential to streamline workflows, reduce errors, and free up teams to focus on strategic decision-making.
A recent report by research firm Deep Analysis, sponsored by document automation specialist Hyperscience, sheds light on the current state of AI readiness in T&L back-office functions. Titled “Market Momentum Index: AI Readiness in Transportation and Logistics Back-Office Operations,” the report drew on findings from a survey of T&L professionals to reveal both the challenges and opportunities for automation and AI adoption. (For more information about the research and methodology, see sidebar, “About the research.”)
This article summarizes some of the key findings and offers some actionable recommendations for supply chain professionals looking to harness the power of AI to drive efficiency and competitiveness.
THE CRITICAL ROLE OF THE BACK OFFICE
Back-office operations are the administrative core of supply chain processes, encompassing tasks such as order processing, inventory management, billing, compliance documentation, and communications with vendors and carriers. While these tasks are not visible to end consumers, they are vital to maintaining the smooth flow of goods and ensuring on-time deliveries. Furthermore, these operations are typically complex, involving numerous transactions and partners, and, as a result, are often plagued by fragmented processes, duplicated efforts, and misaligned data. Yet, most transportation and logistics companies still depend on manual processes and paper-based systems for their back-office operations, which often lead to errors, delays, and inefficiencies.
For example, the industry relies heavily on documents such as invoices, bills of lading, shipment tracking forms, and compliance records. Many organizations, however, use manual or semi-automated processes to manage these documents. Survey respondents indicated that the manual handling of supply chain documentation is a significant challenge that can have a large impact on overall supply chain efficiency (see Exhibit 1). For instance, missing or incorrect paperwork can cause customs delays, incur fines, or disrupt critical supply chain timelines. Additionally, document handling involves multiple touchpoints, which increases the risk of errors and operational delays. Furthermore, the lack of standardized document formats complicates data sharing and collaboration.
The survey found that many companies have implemented digital tools such as enterprise resource planning (ERP) systems, supply chain management (SCM) systems, transportation management systems (TMS), and warehouse management systems (WMS). These systems were initially marketed as comprehensive solutions capable of automating business processes, improving efficiency, and providing real-time data visibility. However, their effectiveness has been limited by several key challenges. First, high implementation costs and complex integrations often lead to partial deployments, where critical functions remain unautomated. Second, rigid system architectures struggle to adapt to dynamic business needs, forcing employees to rely on manual workarounds—particularly in Excel—to fill functionality gaps. This reliance on spreadsheets introduces high data-entry error rates, inconsistent reporting, and limited data visualization capabilities. Additionally, ineffective user training and resistance to change further hinder adoption, leaving many organizations unable to fully leverage these systems. As a result, despite their potential, ERP, WMS, and similar tools frequently fall short of delivering the promised operational transformation.
THE GROWING INTEREST IN AI
Given the lack of success with other technology tools, there is a perception that supply chain organizations in general—and T&L firms in particular—might be resistant to or uninterested in AI. So it came as a bit of a surprise that the survey results indicated a growing interest in automation and AI within the T&L sector. Over 70% of respondents expressed a willingness to invest in AI-optimized systems, recognizing the potential for these technologies to transform back-office operations.
Of those respondents whose organizations were already using AI, 98% said they view the technology as useful, important, or vital. As Exhibit 2 shows, these respondents are currently employing AI to accomplish a wide range of goals. The report highlights several key areas where AI adds value, such as:
1. Improved decision-making (31%): AI can analyze large volumes of complex data—such as real-time traffic patterns, weather conditions, shipment tracking, and historical trends—to optimize supply chain decisions.
2. Error reduction (28%): For back-office tasks such as data entry, invoice processing, and document management, AI can automate repetitive processes, drastically reducing human error.
3. Enhanced data quality (37%): AI improves data quality by ensuring consistency, standardization, and accuracy, making the data more reliable for decision-making purposes.
Going forward, automation and AI have the potential to reshape the industry, enabling companies to reimagine workflows, prioritize sustainability, and enhance collaboration.
BARRIERS TO AI ADOPTION
Despite the clear potential of AI, significant barriers to adoption remain. The survey respondents reported several concerns about implementing AI for back-office processes (see Exhibit 3). The most common concerns include:
1. Data security and privacy (54%): Transportation and logistics companies handle a large volume of sensitive data, including customer information, shipment details, and payment records. Ensuring robust security protocols and compliance with privacy regulations is critical for any AI implementation.
2. Cost of implementation (51%): AI technologies require considerable upfront investment in both hardware and software, and many smaller logistics firms or those with tight margins may find it difficult to justify this expense.
3. Integration with existing systems (47%): Many logistics companies still rely on traditional TMS and ERP systems that were not built with AI in mind, requiring substantial and extensive investment in infrastructure upgrades.
ESSENTIAL STEPS
No matter how powerful a technology is, its effectiveness in the real world of business is only as good as the planning and execution of a transformation project. As companies look to implement AI, they must make sure to take essential steps such as standardizing data formats, investing in workforce training, and fostering industrywide collaboration. The report concludes with several recommendations for companies looking to adopt AI and automation in their back-office operations, including:
1. Invest in AI training: Providing employees with training on AI tools and systems will help bridge the knowledge gap and increase adoption rates.
2. Focus on incremental implementation: Starting with pilot projects allows companies to assess the technology’s return on investment (ROI) and build confidence in AI technologies before large-scale deployment.
3. Develop industry standards: Collaborate with industry groups to establish standardized document formats and processing protocols, reducing inefficiencies and errors.
4. Prioritize integration: Select AI solutions that integrate seamlessly with existing systems, minimizing disruption during the transition.
5. Monitor emerging technologies: Stay informed about advancements in AI, such as intelligent document processing (IDP) and robotic process automation (RPA), to remain competitive.
THE TIME IS NOW
The transportation and logistics sector is at a pivotal moment, with significant opportunities to leverage AI and automation to address long-standing inefficiencies in back-office operations. While challenges such as integration, cost, and training remain, the industry is moving steadily toward broader adoption of digital and AI-based solutions. By addressing these barriers and focusing on incremental, strategic implementation, companies can unlock the full potential of automation and AI, driving efficiency and competitiveness in an increasingly complex and indeed volatile market.
Some may be understandably skeptical of AI’s ability to truly transform back-office operations, particularly given past failures to digitize paper-based processes. Certainly, no technology is perfect, and its effectiveness is dependent on how well the organization plans and executes its implementation. However, it’s important to note that huge advances have been made in the ability of AI to read, understand, and process document-based processes. As a result, AI has the potential to make relatively light work of anything from invoices to bills of lading, providing accuracy levels typically far higher than were a human to do the work manually.
For supply chain professionals, the message is clear: The future of T&L lies in embracing digital transformation, investing in AI, and fostering collaboration across the industry. The time to act is now.
About the research
In 2024, the document automation company Hyperscience and the Council of Supply Chain Management Professionals (CSCMP) partnered with the research and advisory firm Deep Analysis on a research project exploring the current state of back-office processes in transportation and logistics, and the potential impact of AI. The report, “Market Momentum Index: AI Readiness in Transportation and Logistics Back-Office Operations,” is based on survey results from senior-level managers and executives from 300 enterprises located in the United States. All of these organizations have annual revenues greater than $10 million and more than 1,000 employees. The survey was conducted in November and December of 2024. The full 21-page report can be downloaded for free at
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