This story appeared for the first time in the July issue of Xchange supply chainand Thought leadership magazine for the supply chain management profession and the publication of a brother to the media and commercial events DC speed.
Despite the transportation and logistics “(T&L) is a decisive role in global trade, the industry has long struggled with inefficiency, especially in the rear office operations. The handling of the manual bill, for example, is still a large pain point, with variations in shipping rates, administrative fees, and the conditions for payment that requires intense employment-delaying settlements for weeks. Likewise, the shipping tracking often depends often on the most often on Featured systems, forcing employees to reference emails, data devices, and old databases to solve exceptions such as delay or damaged goods.
Given these ongoing challenges, can artificial intelligence (AI) be the solution? By automating repeated tasks-such as verification of the authenticity of the bill, exclusion alerts, and document processing-AII, the ability to simplify the workflow, reduce errors, and edit teams to focus on strategic decisions.
A recent report from Deep Analysis, sponsored by a document automation specialist, sheds light on the current status of artificial intelligence in the functions of T & L Entitled “The Momentum in the Market: AI preparedness in rear transport and logistics operations”, the report was based on results from a survey of T & L professionals to detect both challenges and opportunities for automated operation and adopting artificial intelligence. (For more information about research and methodology, see sidebar, “about search”.)
This article summarizes some of the main results and provides some implemented recommendations to the supply chain professionals who are looking to harness the strength of artificial intelligence to push efficiency and competitiveness.
The decisive role of the back office
Back office operations are the administrative nucleus of supply chain operations, which include tasks such as requesting requests, inventory management, bills documents, compliance documentation, communications with sellers and carriers. Although these tasks are not visible to the final consumers, they are vital to maintaining the smooth flow of goods and ensuring delivery processes on time. Moreover, these processes are usually complicated, and include many transactions and partners, and as a result, they often suffer from fragmented operations, repeated efforts, and wrong data. However, most transportation and logistical services companies are still dependent on manual processes and paper systems for back office operations, which often lead to errors, delays and inefficiency.
For example, the industry depends greatly on documents such as bills, shipping bills, charging tracking models and compliance records. However, many organizations use manual or semi -automatic processes to manage these documents. The respondents indicated that the manual handling of the supply chain is a major challenge that can have a major impact on the efficiency of the total supply chain (see Figure 1). For example, lost or incorrect paper leaves can cause customs delay or fines or disable the streams of the critical supply chain. In addition, the treatment of documents includes multiple contact points, which increases the risk of errors and operational delay. Moreover, the lack of standard documents formats holds data and cooperation.
The poll found that many companies have implemented digital tools such as ERP resource planning systems (SCM), TMS management systems, and warehouse management systems (WMS). These systems were initially marketed as comprehensive solutions capable of automating commercial operations, improving efficiency, and providing data vision in actual time. However, its effectiveness was limited by many major challenges. First, high implementation costs and complex integration often lead to partial publications, as critical functions remain unannounced. Second, the strict structures of the system are struggled to adapt to the dynamic work needs, forcing employees to rely on manual solutions – especially in Excel – to fill functional gaps. This dependence on data schedules provides error rates in high data entry, inconsistent reports, and limited data visualization capabilities. In addition, the training of ineffective users and resistance to change hinders its adoption, leaving many institutions unable to fully benefit from these systems. As a result, despite its potential, ERP and WMS and similar tools often are not less than the presentation of the promised operational transformation.
The increasing interest in artificial intelligence
Given the lack of success in other technology tools, there is a perception that the supply chain organizations in general – and T & L companies in particular – may be resistance or not interested in artificial intelligence. So it was a little surprising that the results of the survey indicated a growing interest in automation and AI in the T&L sector. More than 70 % of the respondents have expressed their willingness to invest in improved AI systems, while realizing the possibility of these technologies to transfer the rear office operations.
Among the respondents whose organizations have already used artificial intelligence, 98 % said they view technology as useful, important or vital. As Figure 2 also displays, these respondents are currently using Amnesty International to achieve a wide range of goals. The report highlights many major areas where artificial intelligence adds value, such as:
1. Improving decision -making (31 %): AI can analyze large quantities of complex data-such as actual time traffic patterns, weather conditions, freight tracking, and historical trends-to improve supply chain decisions.
2. mistake discount (28 %): For rear office tasks such as data entry, bill processing, and document management, AI can automate repeated operations, which greatly reduces human error.
3. Founding data quality (37 %): AI improves data quality by ensuring consistency, unification and accuracy, making data more reliable for decision -making purposes.
Moving, automation and AI have the ability to reshape the industry, enable companies to re -perceive the workflow, set sustainability priorities, and enhance cooperation.
Burns in front of adopting artificial intelligence
Despite the possibilities of artificial intelligence, large barriers remain in front of adoption. The respondents reported many concerns about the implementation of the artificial intelligence of the rear office operations (see Figure 3). The most common concerns include:
1. Safety of data and privacy (54 %): Transport and logistical services companies deal with a large volume of sensitive data, including customer information, shipping details and payment records. Ensuring strong security protocols and compliance with privacy systems is very important to any artificial intelligence.
2. The cost of implementation (51 %): Artificial intelligence technologies require a great investment in both devices and programs, and you may find many smaller logistical services or those that have narrow margins that are difficult to justify these expenses.
3. Integration with current systems (47 %): Many logistical services companies still depend on the traditional TMS and ERP systems that have not been built, taking into account artificial intelligence, which requires large large -scale investments in infrastructure promotions.
Basic steps
Regardless of the strength of technology, its effectiveness in the real world of business is only good like planning and implementing the transformation project. Since companies are looking to implement artificial intelligence, they must ensure that basic steps such as standardizing data formats, investing in workforce training, and enhancing cooperation at the level of industry. The report concludes with several recommendations for companies looking to adopt artificial intelligence and automation in their rear operations, including:
1. Invest in artificial intelligence trainingProviding employees with training on artificial intelligence tools and systems will help to fill the knowledge gap and increase adoption rates.
2. Focus on additional implementation: Starting with experimental projects, companies allow for investment technology return (ROI) and confidence in artificial intelligence technologies widely before publishing.
3. Industry standards development: Cooperation with industry groups to create uniform documents and processing protocols, which reduces inefficiency and errors.
4. Giving priority to integration: Define artificial intelligence solutions that are smoothly integrating with the current systems, which reduces the disorder during the transition.
5. Emerging technology monitoring: Keep awareness of developments in artificial intelligence, such as treating smart documents (IDP) and automating automatic operations (RPA), to remain able to compete.
The time now
The transportation and logistics sector is in a pivotal moment, with great opportunities to benefit from artificial intelligence and automation to address long -term inefficiency in the rear office operations. While challenges such as integration, cost and training, the industry steadily moves towards a broader dependence on digital and artificial intelligence solutions. By addressing these barriers and focusing on additional strategic implementation, companies can open the full capabilities of automation and AI, and to lead efficiency and competitiveness in the already increasingly complex and volatile market.
Some people may be concept skeptical of the ability of artificial intelligence to truly transform the background office operations, especially given the previous failures in the digitization of paper operations. Certainly, there is no perfect technique, and its effectiveness depends on the organization’s plans and implementation. However, it is important to note that significant progress has been made in the ability of artificial intelligence to read, understand and process processes based on documents. As a result, artificial intelligence has the ability to make a relatively light work from anything from bills to shipping bills, providing much higher accuracy levels than a person to do the work manually.
For professionals in the supply chain, the message is clear: the future of T & L lies in adopting digital transformation, investing in artificial intelligence, and enhancing cooperation throughout the industry. It’s time to work now.
About research
In 2024, a partnership with the Excessive Documentation Automation Company and the Council of Supply Series Management Specialists (CSCMP) with the deep analysis of the research and consulting company on a research project that explores the current situation of the rear office operations in transportation and logistics services, and the potential impact of the spontaneous organization. The report, “Market Money Index: Artificial Intelligence’s Ready to Rear Transport and Logistics Operations”, depends on the results of the survey from managers at the higher level and executives of 300 institutions located in the United States. All of these organizations have annual revenues of more than $ 10 million and more than 1,000 employees. The survey was conducted in November and December 2024. The full report of 21 pages can be downloaded for free on https://explore.hyperscience.ai/report-ai-feadiness-in-ransportation-logistics.
