AI-Driven Approaches to Enhance Budgeting and Forecasting: Transforming Financial Planning in Organizations

Artificial Intelligence has fundamentally transformed organizational budgeting and forecasting, introducing unprecedented capabilities for financial planning in complex business environments. By leveraging machine learning algorithms, predictive analytics, and natural language processing technologies, organizations across manufacturing, financial services, healthcare, and retail sectors have achieved significant enhancements in forecast accuracy, planning efficiency, and strategic alignment. These AI-driven approaches enable dynamic scenario evaluation, rolling forecast implementation, sophisticated variance analysis, real-time financial health monitoring, automated financial statement generation, and strategic resource allocation optimization. Despite compelling benefits, implementation requires overcoming substantial challenges including data quality issues, algorithm transparency concerns, organizational resistance, potential algorithmic bias, system integration difficulties, and regulatory compliance considerations. The evidence demonstrates that successful AI implementation in financial planning creates transformative capabilities that directly improve competitive positioning through enhanced agility, resource optimization, and strategic alignment. As these technologies continue evolving, their impact will likely accelerate, fundamentally reshaping financial planning practices and establishing new standards for excellence in increasingly dynamic business environments.

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Publication Details

Journal
European Journal of Computer Science and Information Technology
Published
2025-04-15
DOI
https://doi.org/10.37745/ejcsit.2013/vol13n234351
Citations
1
Primary Topic
Forecasting Techniques and Applications
Type
article
Field-Weighted Citation Impact
2.11
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article

AI-Driven Approaches to Enhance Budgeting and Forecasting: Transforming Financial Planning in Organizations

Siva Prasad Marri
1 citations
European Journal of Computer Science and Information Technology
Forecasting Techniques and Applications
2.11
article

AI-Driven Approaches to Enhance Budgeting and Forecasting: Transforming Financial Planning in Organizations

Siva Prasad Marri
article en
1 citations

Abstract

Artificial Intelligence has fundamentally transformed organizational budgeting and forecasting, introducing unprecedented capabilities for financial planning in complex business environments. By leveraging machine learning algorithms, predictive analytics, and natural language processing technologies, organizations across manufacturing, financial services, healthcare, and retail sectors have achieved significant enhancements in forecast accuracy, planning efficiency, and strategic alignment. These AI-driven approaches enable dynamic scenario evaluation, rolling forecast implementation, sophisticated variance analysis, real-time financial health monitoring, automated financial statement generation, and strategic resource allocation optimization. Despite compelling benefits, implementation requires overcoming substantial challenges including data quality issues, algorithm transparency concerns, organizational resistance, potential algorithmic bias, system integration difficulties, and regulatory compliance considerations. The evidence demonstrates that successful AI implementation in financial planning creates transformative capabilities that directly improve competitive positioning through enhanced agility, resource optimization, and strategic alignment. As these technologies continue evolving, their impact will likely accelerate, fundamentally reshaping financial planning practices and establishing new standards for excellence in increasingly dynamic business environments.

European Journal of Computer Science and Information TechnologyVol. 13(23)
Sri Venkateswara University (IN)
Openalex Percentile: Top 14%
Forecasting Techniques and Applications
2.11
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