The emergence of new technologies, such as artificial intelligence (AI), is transforming society and changing fundamental beliefs about money, value judgments, and enterprise implications. AI is becoming increasingly prevalent, serving as an exceptional advisor and an omniscient informant. While AI offers great potential to tackle serious global issues, such as climate change, food security, and healthcare, there are also potential hazards and ethical concerns that require careful consideration. The manufacturing industry is grappling with the complexities of improving efficiency, but there is hope in the form of AI. The industry's intricate nature, with variations and interactions among system members, presents challenges in streamlining processes. However, the rapid transformation brought about by new technologies like AI offers opportunities to enhance competitiveness and efficiency. AI can automate operations, optimise production processes, and provide valuable insights that humans may struggle to generate alone. By implementing AI in supply chain management (SCM), companies can mitigate risks and reduce errors, delays, and wastage. AI can also contribute to predictive maintenance, minimising downtime and costly repairs, while process optimization can streamline operations and maximise productivity. Embracing AI in the manufacturing sector holds immense potential for increased productivity, profitability, and overall success. It is crucial to develop specific knowledge and understanding about AI to ensure effective implementation and high-quality decision-making in the future. Providing guidance for the future of AI is crucial, as it holds the promise of solving significant problems and driving innovation. However, its implementation can also present challenges for companies. Accurate forecasting and understanding the implications of AI are essential for navigating this landscape. The successful usage of AI hinges on effective implementation, particularly in complex environments like the supply chain (SC). Therefore, the aim of this thesis is to provide insights and deeper knowledge on how integrating AI into SCM can enhance its operations. By using a qualitative method and the grounded theory in order to analyse the data collection, we have discovered how the implementation of AI can improve SCM as well as its drawbacks. The implementation of AI has the potential to revolutionise production processes, streamline operations, and improve decision-making and forecasting, leading to increased prosperity and cost savings for companies. However, it is important to acknowledge and address several challenges and considerations to ensure the successful implementation of AI. Mainly, the implementation of AI comes at the cost of complex integration, time consuming strategizing and costly investments into the system. Our results highlight the importance for companies to not only implement AI, but integrate it, in order for successful utilisation. Unlike prior research, this study highlights the dynamic nature and variations in SCM operations and the challenges practitioners encounter. In addition, the study confirms previous findings on the positive impacts of AI, such as enhanced productivity, cost reduction, and improved decision-making. However, it emphasises the significant costs and time commitments involved in implementing AI, creating decision-making obstacles for companies. This underscores the importance of thoroughly evaluating the anticipated benefits of AI in relation to the initial investment and time constraints.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:umu-210340 |
| Date | January 2023 |
| Creators | Norgren, Alva, Janzon Hägglund, Wilma |
| Publisher | Umeå universitet, Företagsekonomi |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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