Application of Artificial Intelligence in Forecasting: A Systematic Review

Abstract

The aim of this reach is to identify how Artificial Intelligence (AI) could be used in enhancing forecasting to achieve more accurate outcomes. The research also explores the influence that forecasting has on global economy and the reasons why it needs to be accurate. Also, the research explains various pitfalls identified in forecasting. Method: This research implements two research approaches which are review of literature and formulation of hypotheses. Seven hypotheses are created. Findings: AI, when integrated with other technologies such as Machine Learning (ML) and when provided with the right computer power, yields much more accurate results than many other forecasting methods. The technology is costly, however, and it is prone to cyber-attacks. Conclusion: The future of business is highly reliant on forecasting, which directly impacts the global economy. But, not every business will have the power to own the forecasting technology due to the cost, and business will need to increase security to protect the forecasting systems.

The Combination of AIs Powerful Data Algorithm Capability and Finance

“…Therefore, artificial intelligence can help financial inclusion, expand the financial market, make more people willing to participate in finance, make investors more assured, and make the market more stable. Artificial intelligence helps people do analytics, which makes business predictions more accurate and allows people to work better with those predictions [7].…”

Forecasting Supply Chain Demand Approach Using Knowledge Management Processes and Supervised Learning Techniques

“…In prior studies, various time series forecasting models have been widely applied in sales forecasting, such as exponential smoothing models, ARIMA models, expert systems, and Nearest Neighbors models. A case study carried out by (Annor-Antwi et al 2019), illustrates that forecasting helps in the future prediction of the market trends, it also helps a business utilize resources more efficiently, manage inventory, remain competitive, evaluate its past and therefore be able to have a clearer focus on the future. According to (Kamble et al 2015), SCM relies on forecasts of future demand for decision making which are used in supply chain design, planning as well as in operations.…”