BMP5017 AI in Freight Transport and Logistics: Research Analysis

Abstract

This research has analysed the aim and objectives of the topic, along with the discussion of the literature review, explaining each theme and gap in that. Appropriate methodologies have been used in the research to showcase the importance of AI in freight transportation and logistics. For instance, this research has used an interpretivism research philosophy and a deductive approach. Also, this research has used a qualitative research strategy and an explanatory design to arrive at the answers to the research topic. Moreover, simple random sampling has been applied to interview 3 managers of Bestof5 Transport LTD CARE. Apart from this, this research has included thematic analysis based on the findings of the secondary and primary research. 

 

Chapter 1 Background of the Organisation
 

1.1 Introduction
 

In this modern world of business, AI is becoming rapidly famous in every sector as it helps companies to boost the efficiency of work, improve decision-making capabilities, reduce costs, and more. According to Kumarage (2021), freight transport can de defined as the physical movement of goods among various types of locations, and logistics involves several activities, such as warehousing, customs clearance, managing and preprocessing of orders, and more. Now, various transport businesses are implementing artificial intelligence (AI) and machine learning (ML) methods to become more advanced and lead the market with their increased efficiency. This research will analyse the importance and implementation of AI in freight transport and logistics, as it helps the organisations to forecast the requirements more accurately, leading to faster and quicker deliveries, and more. Furthermore, this study will have an analysis of the company, Bestof5 Transport LTD CARE. The company was founded in 2018 and has its headquarters located in Felixstowe, UK (GOV.UK, 2025). It is a private limited company which provides transportation facilities across the UK, specifically freight transport by road.
 

1.2 Statement of the problem
 

The problem that this study will look into is related to the context of AI incorporation in freight transport and logistics, despite having significant benefits and transformative potential of AI. Therefore, the chosen company faces various types of substantial challenges for its successful integration and implementation.
 

1.3 Research Question
 

The key research question that the study would be answering is: “What is the importance of artificial intelligence (AI) in freight transport and logistics of Bestof5 Transport LTD CARE?”
 

1.4 Rationale of the research
 

This research is about improving the efficiency of the work and reducing the costs in the field of transport for the company by implementing AI and ML methods. It actually enhances the responsiveness of the business, visibility, and influence towards sustainability goals. This will help get insights that can be used to improve implementation of AI in freight and logistics operations. 
 

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Chapter 2 Aims and Objectives of your mini-research project 

2.1 Aim
 

This study aims to identify and analyse the importance of artificial intelligence (AI) in the field of freight and logistics transport through examining its role in decreasing the cost of operations, improving the decision-making process, and enhancing production efficiency. Through various types of applications, such as predictive maintenance, automated data analysis methods, route optimisation, and more. 
 

2.2 Objectives
 

• To identify the concept of AI in freight transport and logistics

• To analyse the benefits of AI in the field of freight transport for Bestof5 Transport LTD CARE

• To address the key challenges related to implementation of AI freight transport by Bestof5 Transport LTD CARE

• To recommend some future improvements to make AI usage more effective for Bestof5 Transport LTD CARE 
   

2.3 Literature Review
 

2.3.1 Conceptual Framework

 

Figure 1: Conceptual Framework

(Source: Created by the learner)

2.3.2 Empirical Literature

Identifying the concept of artificial intelligence (AI) in freight transport and logistics

According to Mozumder et al. (2024), the rapid growth of AI in the logistics systems of transport has led to the overall supply chain management developing to a next-level territory. The implementation of several AI and ML technologies, which are related to various types of algorithms, from computer vision to natural language processing (NLP), has improved the adaptability and efficiency of work. On the same note, du Plessis et al. (2025) stated that using AI and intelligent logistics in the field of freight transport not only advances this sector, but also all the industries by providing new capabilities and insights, and automated tasks that were not possible in the previous traditional method. Sætra (2022) states that AI can ultimately improve the environmental, social, and economic sustainability through AI and ML capabilities combined with computing power. 
 

Analysing the benefits of AI for freight transport
 

Ficzere (2023) stated that artificial intelligence (AI) plays an important role in the field of freight transport, which offers several benefits, such as safety, enhancing the efficiency of production, and improving the overall operations sector. As per Munshi (2023), one of the most crucial benefit that AI provides is predictive maintenance of a huge amount of data, avoiding sudden breakdowns, and reducing any kind of disruptions. On the other hand, according to Iyer (2021), incorporation of AI in transport can help in various factors, such as traffic management, trip planning, utilising the mobility, making informed decisions, and most importantly, creating a sustainable system for transport. It can support the transport system through various types of frameworks in AI, which include Genetic algorithms (GA), Artificial Neural Networks (ANN), Fuzzy Logic Model (FLM), and more.
 

Addressing the key challenges faced in the freight transport system through AI
 

According to Samaei (2023), in the field of transportation in big cities, along with a huge range of populated areas, there are some key issues that are faced by the system, which include traffic congestion, air pollution, a lack of various sustainable transportation options, infrastructure decay, safety concerns, parking issues, and more. These issues can be solved by the implementation of AI through AI-based prediction of traffic, route optimisation, producing self-driving cars, promoting electric vehicles (EVs), and more. On the same note, Bharadiya (2023) stated that incorporating fully automated vehicles through AI, providing customised mobility services, advanced safety precautions, and more can address the challenges that are being faced by the system.
 

Recommending improvements in AI to be more effective in future in the field of freight transport
 

Wang and Sarkis (2021) stated that the advancements of technologies in the field of artificial intelligence (AI) and machine learning (ML) have led to continuous improvement in the transport system. Improving areas such as data analytics, blockchain, pervasive computing, and more can be more effective in freight transport. Dikshit et al. (2023) also stated on a similar note that improving AI’s capacity and algorithms can actually minimise the different issues facing the overall transport systems by implementing road network characteristics, involving real-time updates of traffic, and more.  
           

2.3.3 Literature Gap
 

The shortage of certain exhaustive literature in the given study about AI implementation in the context of ensuring long-term economic sustainability and promoting ethical standards in the area of freight transport. The study on the significance and usefulness of AI deployment within the transport system to make it more efficient and easier is well-documented, yet the tricky aspect is that to break the obstacles in the implementation of the techniques, it is essential to spend a lot of money, have a high level of data quality, and lack of professionalism to work with that.   
 

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Chapter 3 Methodology

 

3.1 The value and methodology

 

3.1.1 Research Philosophy
 

Research philosophy is a collection of beliefs, which allow the researcher to achieve the objectives of the research (Mauthner, 2020). Some of the philosophies of the research are positivism, interpretivism and pragmatism. Interpretivism is the research method that has been employed because it focuses on in-depth knowledge and variables considering the understanding of the assumptions and real-life experience of the individuals (Alharahsheh and Pius, 2020). Such a research philosophy is likely to allow a researcher to comprehend the phenomenon under study effectively. 
 

3.1.2 Research Approach 
 

Research approach is the type of procedure and plan of the research, which assists the researcher in creating effective tactics to achieve the objectives and access useful insights and information to support the research (Taherdoost, 2022). Some of the approaches of the research that can be advantageous in justifying and applying to the researcher include deductive, inductive as well as abductive approaches of the research. The deductive approach has been used to carry out this study since it is capable of strategising and employing a strategic plan to do research based on both observation and evidence (Hall et al., 2023). 
 

3.1.3 Research Strategy 
 

Research strategies are the variables that guide the researcher to carry out the research making them more efficient in providing the insights and information. In the context of the research, there are several strategies available, such as qualitative, quantitative and mixed strategies. This study has been conducted using the qualitative research strategy that can help the researcher showcase the importance of AI in freight transport for Bestof5 Transport LTD (Williams, 2025). 
 

3.1.4 Research Design
 

In terms of the design of the research, it can be identified that it is the plan and procedure of the research that helps the researcher to answer all the questions related to the topic (Khanday and Khanam, 2019). Experimental, descriptive, correlational and diagnostic are some of the designs of the research which effectively help the researcher to develop and arrive at the answers related to the topics.  This research has been conducted using the explanatory research design as it effectively delivers the ideas and knowledge to conduct the research, enabling personal inclination for the research. 
 

3.1.5 Data collection 
 

Data collection is known as the process and technique of the research that helps the researcher to gather and collect information and data from multiple sources (Dovetail, 2025). Primary and secondary are several forms of data collection which help the researcher collect and gather information from multiple sources, like scholarly articles and government websites. Moreover, to collect the data for this research, the researcher has used primary and secondary data collection methods. For the primary research, an interview will be conducted, for which the researcher has used managers at Bestof5 Transport LTD. 
 

3.1.6 Sampling strategy
 

Sampling strategy is known as the procedure that helps the researcher to illustrate the data and information which represents the whole population’s mindset (Qualtrics, 2025; Makwana et al., 2023). Probability and nonprobability sampling are some of the forms of sampling strategies that the researcher uses to conduct research. This sampling has been conducted using a probability sampling strategy, specifically the simple random strategy as it concentrates on providing an equal chance to every individual in the operations and to put their opinion on the specific topic and research (Simkus, 2023).  
 

3.1.7 Data analysis
 

To conduct the research, the researcher has used thematic analysis focusing on the appropriate application of the information and insights which has been gathered from the sources. Thematic research is a well-known procedure of analysing qualitative data and information to derive insights and conclude them in a descriptive form (Naeem et al., 2023).
 

3.2 Ethical Considerations
 

The ethical considerations of this research include the displacement of jobs from the automation sector, data security and privacy with sensitive information, and the demand for transparency and accountability in AI systems. Maintaining ethics in every industry and sector is defined as the morality and disciplined methods for doing the work, respectfully and legally correct (Chervenak and McCullough, 2021). Some of the ethical considerations include algorithm fairness and bias, environmental and societal impact, human-ai interaction, and more.
 

3.3 Gantt Chart and Timeline
 

List of activities	Start Date	Duration	End Date
Understanding the Topic	06-11-2025	2	08-11-2025
Determining the aim and objectives	08-11-2025	2	10-11-2025
Literature Review	10-11-2025	3	13-11-2025
Conducting methodology	13-11-2025	5	18-11-2025
Data collection techniques	18-11-2025	4	22-11-2025
Recommendations	22-11-2025	2	24-11-2025
Submission	24-11-2025	1	25-11-2025

Table 1: Timeline

(Source: Created by the learner)

 

Chapter 4 Primary and secondary research findings and discussion

4.1 Secondary findings 
 

Title	Author name	Year	Findings
Shaping the Future of Freight Logistics: Use Cases of Artificial Intelligence.	du Plessis, M.J., Gerber, R., Goedhals-Gerber, L.L. and van Eeden, J.	2025	Logistics and transport play an effective role in managing the global economy, and AI in transportation have effective benefits in terms of improving the automation of tasks. AI in transportation and logistics has reduced inefficiency and human errors. Also, AI in the business has helped companies to make their decisions to improve their operational conditions and capabilities to resolve issues and challenges. Apart from this, AI in the business helps companies to assess and predict the future and possible challenges that can occur to the organisation.
Development of artificial intelligence as a modern business technology, using the transport industry as an example.	Romanova, N., Kakhrimanova, D., Semenova, A., Safronova, A. and Belyaeva, E.	2020	There are several benefits of using AI in the transportation and logistics industry, as it can help companies to monitor their roads in terms of detecting objects and related pedestrians, as well as autonomous driving conditions. Apart from this, AI helps transportation companies to manage their road maps in terms of enabling a streamlined process of operations. Moreover, to manage the traffic and signals, AI is being used. It can help companies to generate revenue and financial gains in the competitive business market, enabling an effective approach. Moreover, it can help them gain the trust and loyalty of their targeted customers in the respective industry.
Solutions to the problem of freight transport flows in urban logistics.	Batarlienė, N. and Bazaras, D.	2023	Freight transportation and logistics consist of several challenges and issues in the business regarding intensive pollution, which effectively create challenges to the environment. Also, these types of companies face several other issues in terms of managing their order processing and delivery time in the business and daily operations. It can create challenges for the business in the complicated business environment of transportation and logistics. Apart from this, there are several challenges to the development of the infrastructure, which can help the companies to manage their operations, enabling more revenue for the company.
Sustainable technology strategies for transportation and logistics challenges: an implementation feasibility study.	Sumbal, M.S., Ahmed, W., Shahzeb, H. and Chan, F.	2023	To solve the challenges related to transportation and logistics, companies need to manage their distribution and the skills of their employees, which can help the companies manage their operations in the competitive business market. Also, companies need to optimise their distribution channels along with the cost of operations, which can help them mitigate the issues and challenges. Apart from this, managing the supply chain and process of the operations can be identified as an effective strategy for improving the business of logistics and transportation. In addition to this, companies can effectively incorporate smart logistics systems like Aerial Vehicles and cloud computing for effective operations, enabling more value in the process of the operations.

Table 2: Primary Findings

(Source: Created by the learner)

4.2 Primary findings
 

Questions	Manager 1	Manager 2	Manager 3
What is the base concept of AI in freight transport and logistics?	Yes, I am aware of the AI in the business and in the industry of logistics and transportation. Our company use AI and technologies like this in several aspects of the business and operations to perform better in the business. It helps our company to streamline the operations, enabling effective traffic management.	Well, it is a very interesting question and has helped our company to improve and develop our operational strategies while reducing the issues and challenges. It has helped our company to streamline the process of operations, enabling more revenue and competitiveness in the respective industry.	I am aware of the AI that our company uses to operate the business, enabling more revenue in the competitive industry in the UK. Also, it has helped to improve the logistics and transportation process and operations.
What are the benefits of AI in the field of freight transport for Bestof5 Transport LTD CARE?	AI in Bestof5 Transport LTD CARE benefits in several aspects, as it helps the company to generate revenue in the competitive industry while reducing the challenges and managing the autonomous driving conditions. It can help the company to improve its condition while gaining the trust and loyalty of the customers.	There are several benefits that the company have faced in their daily operations, such as improving operational conditions and driving state to gain the competitiveness and trust of the customers to generate revenue and financial gains.	Well, AI in transportation and logistics has helped the company to gain a financial advantage by optimising the inventory and operational patterns in a more automated way, which helps the company to be more competitive in the UK industry.
What are the challenges and issues the company have faced in managing operations?	A few challenges have been identified in the organisation, as it creates intensive pollution and due to the lack of knowledge of the employees in the respective industry in the competitive business market, in terms of enabling more revenue and finances. It has created several regulatory issues and challenges for managing the inventory and supply chain.	Some of the challenges that the company have faced are managing the delivery systems and optimisation of the inventory and supply chain, which created hurdles to the operations in the UK. Infrastructure development is an issue that the company have faced in their business and operations, and for that, AI can help to gain the appropriate insights and information to mitigate the challenge.	Bestof5 Transport LTD CARE have faced several issues and challenges in the business due to the usage of AI in the business, as it reflected and caused regulatory and compliance issues while managing the cyber-attacks. Thus, the transportation and logistics industry faces several issues and challenges, like managing and reducing pollution to operate the business effectively in the competitive business market and the respective environment.
How does Bestof5 Transport LTD CARE make improvements in its business?	Bestof5 Transport LTD CARE have used AI in their business to mitigate the challenges and issues of the business for understanding the insights and carbon footprints that the company is causing in their operations. The company uses AI to gain future insights and regulatory standards to reduce the challenges and issues of the business while streamlining the process of operations.	Well, the company uses AI in its operations and to manage the business, enabling more sustainable processes with the implementation of new and advanced insights for appropriate application to gain a competitive advantage.	Several benefits and improvements that the company have incorporated in the business using AI in the business while monitoring the operations and detecting the traffic lights and signals effectively to satisfy the needs and demands of the targeted customers in the competitive business industry in the UK.

Table 3: Interview table

(Source: Created by the learner)

4.3 Discussion 
 

AI in freight transport and Logistics 
 

According to du Plessis et al (2025), logistics and transportation have played an effective part in managing the economy of the business and industry. In this industry, AI has made several changes and improvements in terms of reducing the ineffectiveness and errors that humans and individuals of the organisation cause in their daily operations to manage their daily activities. It helps the company to generate revenue and competitiveness in their respective industry. 
 

Streamlined operations and effective monitoring 
 

In the opinion of Romanova et al (2020), AI has made several transformations in the transportation and logistics industry and for the companies in terms of managing an effective and inclusive monitoring process of the operations and conditions of the operations to gain a competitive advantage. It can help companies to improve their finances and customer service while understanding the future risks and challenges in the competitive business market. Apart from this, it has also helped the companies to manage the road maps and signals to satisfy the demand and needs of the customers and generate revenue in the industry. 
 

Cybersecurity and regulatory issues 
 

Freight transportation and logistics have faced several challenges and issues in the business, including pollution and cybersecurity (Batarlienė et al., 2023). Also, companies like Bestof5 Transport LTD CARE have faced these types of issues and challenges in their operations, as some of their managers have confirmed the information. The managers of the company have also stated that these are some of the challenges and issues that the company is facing in their business and operations due to a lack of skilled employees. 

 

Improvement suggestions 

Fortunately, these issues can be resolved with the use of AI, as the companies can effectively use this technology to understand and assess the conditions of the supply chain and inventory, which can help them reduce the future challenges and issues of the organisation (Sumbal et al., 2023). Thus, AI can benefit and improve the conditions of the operations while offering effective skill training to the employees for managing the distribution channels. 
 

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Chapter 5 Conclusion and Recommendation
 

5.1 Conclusion
 

The importance of AI is rapidly growing in this modern generation of businesses in every sector, and all business companies are using it to increase their productivity, efficiency and effectiveness of the work, along with making it more cost-effective. Implementing AI in freight transport and logistics can help organisations to enhance their efficiency through automated operations, prediction, and optimisation, improve the satisfaction level of customers, and promote sustainability. This research provides a recommendation to incorporate AI and ML frameworks to track real-time traffic disruptions and address several issues that are being faced by the systems nowadays. According to Okrepilov (2022), artificial intelligence technologies can be defined to develop the business processes, which particularly help the operational performance. With the help of AI and ML methods, the system of transportation can have its businesses uplifted to a higher position in the market, along with meeting the necessary requirements of the customers with faster delivery. The use of AI in this sector can help the industry identify fraud, along with managing higher quality, which will increase the value of the organisations. Various large corporations, such as Amazon, have been actively developing advanced AI technologies in their transportation sector, as well as in the development of new products and shifting their business models.
 

5.2 Recommendations
 

Nowadays, some other large companies are also using AI in their business models to make their brand value and image even better to attract potential customers. They are using these frameworks to make their work, operations, and production even more efficient and, most importantly, easier to handle and manage the applications. Some researchers have found that by 2030, the domination of artificial intelligence (AI) will increase by 14% across the world, and the Global Consultant McKinsey Institute have also found that 70% of the organisations will use any one type of AI framework actively in their business purposes by 2030 (Okrepilov, 2022). According to Tariq (2024), introducing smart transportation systems (STS) can help transport systems achieve a strong market position through advanced technologies and various types of data to promote sustainability and solve traffic problems. This can be the modern solution to address the modern issues that are being faced by freight transportation and logistics systems. Integrating advanced AI technologies, autonomous vehicles, and the Internet of Things impacts the STS on different factors, such as public transport, traffic management, and social and environmental sustainability. 
 

Various companies are trying to develop these smart transportation systems (STS) as they cover a huge variety of applications, such as congestion pricing, service mobility, traffic monitoring, optimisation of public transport, and more. The companies are prioritising traffic management as the most urgent because it causes heavy problems in delivering goods and supplying materials. To address these, companies are incorporating a traffic management system with the help of AI because it uses predictive analytics and real-time data to analyse and monitor the traffic instantly, identify the disturbances, and solve the issues by adjusting the signal timing to continue the flow and decrease congestion. The demand for management strategies, which includes dynamic tolls and congestion charges, aims to encourage and regulate the demand for traffic to decrease the environmental and congestion impacts. One of the important goals of developing STS is to influence sustainability practices and promote them in urban areas. It offers different benefits in promoting sustainability, including energy savings, improved mobility, reduction of carbon emissions, and economic efficiency (Tariq, 2024). Additionally, it promotes the usage of various alternative transport modes, which include walking, cycling, and public transport, to contribute to the reduction of carbon congestion and emissions, and to improve mobility and accessibility. 
 

Zemmouchi-Ghomari (2025) stated that AI is increasing, as the safety concerns and congestion are also increasing, along with the increasing environmental pollution in the infrastructure of transportation systems. Traditional systems are not up to the mark in this rapidly growing world of business, which is why the implementation of AI is extremely necessary for making informed decisions and using real-time management tools. In the field of freight transport, AI algorithms can significantly enhance the work and operational efficiency. AI and ML frameworks identify and analyse a large amount of data from several sources to optimise traffic management strategies. By the process of implementation, it faces some challenges, such as maintaining the same high quality, computational costs, public acceptance, a lack of talented and skilled professionals for managing it, security vulnerabilities, and more. 
 

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