An Appraisal of the Implementation of Artificial Intelligence in Sales Forecasting: A Study of Retail Businesses in Plateau State
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Background of the Study
Artificial intelligence (AI) has emerged as a transformative tool in sales forecasting, enabling businesses to analyze vast amounts of data, identify trends, and make accurate predictions. By employing AI techniques such as machine learning, predictive analytics, and natural language processing, retail businesses can optimize inventory management, improve decision-making, and enhance profitability (Olawale & Ibe, 2024).
In Plateau State, retail businesses are exploring AI to overcome traditional forecasting challenges, such as reliance on historical data and human intuition. This study evaluates the implementation and effectiveness of AI in improving sales forecasting accuracy and operational efficiency.
Statement of the Problem
Despite the proven benefits of AI, its implementation in sales forecasting faces obstacles such as high implementation costs, limited expertise, and resistance to change. These challenges result in inconsistent adoption and underutilization of AI capabilities in retail businesses in Plateau State.
This study appraises the implementation of AI in sales forecasting, identifying its impact, benefits, and associated challenges.
Objectives of the Study
1. To assess the level of AI implementation in sales forecasting among retail businesses in Plateau State.
2. To evaluate the impact of AI-driven forecasting on inventory management and decision-making.
3. To identify challenges faced in implementing AI in sales forecasting.
Research Questions
1. What is the extent of AI implementation in sales forecasting in Plateau State's retail businesses?
2. How does AI-driven forecasting impact inventory management and decision-making?
3. What challenges hinder the effective implementation of AI in sales forecasting?
Research Hypotheses
1. AI is not widely implemented in sales forecasting among retail businesses in Plateau State.
2. AI-driven forecasting does not significantly impact inventory management and decision-making.
3. Challenges in implementing AI do not significantly affect its effectiveness in sales forecasting.
Scope and Limitations of the Study
The study focuses on retail businesses in Plateau State, analyzing AI implementation and its effects on sales forecasting. Limitations include differences in business size and readiness to adopt AI technologies.
Definitions of Terms
• Artificial Intelligence (AI): The simulation of human intelligence in machines to perform tasks such as learning, reasoning, and problem-solving.
• Sales Forecasting: The process of estimating future sales using historical data and market analysis.
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