Optimisation of Big Data and Artificial Intelligence Driven Digital Intelligence in Manufacturing Budget Management

DOI

10.2991/978-94-6463-734-2_59How to use a DOI?

Keywords

Budget management; Digital transformation; Big data

Abstract

With the advancement of manufacturing industry’s transformation to digital intelligence, budget management, as an important part of corporate financial management, is gradually integrated into big data and artificial intelligence technology, ushering in new opportunities for digital intelligence transformation. This essay discusses the challenges and opportunities faced by manufacturing budget management in the process of digital and intellectual transformation, focusing on how big data and artificial intelligence technology drive the optimisation of budget management. In the budgeting process, dynamic budgeting and rolling budget mechanisms combined with real-time data and AI forecasts are used to achieve flexible budget adjustments and improve the ability to respond to market changes. In budget enforcement, the use of BI systems and visual dashboards as well as real-time deviation analysis, timely detection of budget deviations and provision of adjustment recommendations, significantly improving the efficiency and transparency of execution. In budget evaluation, introduce a multi-dimensional evaluation framework that combines financial, non-financial and external environmental factors, and dynamically adjust evaluation weights through artificial intelligence to make the evaluation more comprehensive and accurate. Through these optimisation strategies, the manufacturing industry can achieve more efficient and accurate budget management, and promote the improvement of overall operational efficiency and sustainable development.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Xinyue Chang
PY  - 2025
DA  - 2025/05/27
TI  - Optimisation of Big Data and Artificial Intelligence Driven Digital Intelligence in Manufacturing Budget Management
BT  - Proceedings of the 2025 10th International Conference on Social Sciences and Economic Development (ICSSED 2025)
PB  - Atlantis Press
SP  - 517
EP  - 530
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-734-2_59
DO  - 10.2991/978-94-6463-734-2_59
ID  - Chang2025
ER  -