Impact of artificial intelligence on international supply chain management : case study of scurite software company
Singh, Manjinder (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025120833773
https://urn.fi/URN:NBN:fi:amk-2025120833773
Tiivistelmä
This thesis analysed the influence of artificial intelligence (AI) on worldwide supply chain management, utilising Scurite Software Company as a case study. Learn how AI technologies are used at work every day, their benefits, and what prevents them from realising their full potential in cross-border operations. The research showed that supply chains are using more AI for demand forecasting, risk assessment, tracking, documentation, and decision support. It also addressed common issues including poor data quality, technical constraints, and organisational unreadiness. Technology–Organization–Environment (TOE) organises these aspects at the company level.
A quantitative, cross-sectional survey of Scurite workers in overseas supply chains was the study's empirical component. Data was collected using a self-administered online questionnaire and analysed using descriptive statistics in Excel. The results indicated that most survey respondents use AI products frequently and believe AI makes it easier to manage documents, exceptions, and visibility. AI also speeds up cross-border cycle times, according to many respondents.
The data also suggested that many issues recur. The most common problems are data quality and partner integration, followed by process complexity, unclear responsibility, and gaps in training and tool use. Employees also say that delays happen a lot when outside partners do not update systems on time or use different formats. The thesis suggested that data standards and validation should be made stronger, escalation channels should be made clearer, approval flows should be made easier, interaction with key partners should be improved, and focused, practical training should be offered, notably in how to use GenAI and other tools. The study shows that AI is already useful at Scurite, but how useful it depends a lot on having solid data, clear processes, and skilled workers.
A quantitative, cross-sectional survey of Scurite workers in overseas supply chains was the study's empirical component. Data was collected using a self-administered online questionnaire and analysed using descriptive statistics in Excel. The results indicated that most survey respondents use AI products frequently and believe AI makes it easier to manage documents, exceptions, and visibility. AI also speeds up cross-border cycle times, according to many respondents.
The data also suggested that many issues recur. The most common problems are data quality and partner integration, followed by process complexity, unclear responsibility, and gaps in training and tool use. Employees also say that delays happen a lot when outside partners do not update systems on time or use different formats. The thesis suggested that data standards and validation should be made stronger, escalation channels should be made clearer, approval flows should be made easier, interaction with key partners should be improved, and focused, practical training should be offered, notably in how to use GenAI and other tools. The study shows that AI is already useful at Scurite, but how useful it depends a lot on having solid data, clear processes, and skilled workers.