The Role ofArtificial Intelligence in Trade Analytics

Journal of Research and Development Peer Reviewed International, Open Access Journal. ISSN : 2230-9578 | Website: https://jrdrvb.org Volume-17, Issue-10(IV)| October2025 75 The Role ofArtificial Intelligence in Trade Analytics Dr. Raviprakash Kanaiyalal Mer Assistant professor Shri K.R. Desai Arts & Commerce college, Jhalod Manuscript ID: JRD -2025-171020 ISSN: 2230-9578 Volume 17 Issue 10(IV) Pp. 75-76 October 2025 Submitted: 22 Sept. 2025 Revised:05 Sept. 2025 Accepted:13 Oct. 2025 Published: 31 Oct. 2025 Abstract Trade structures are changing rapidly in the modern global economy. Artificial Intelligence (AI) has emerged as a revolutionary tool in the field of trade analytics amid the growing influence of digitalization and data science. AI technology is playing a major role in business decisions, risk management, price forecasting, supply chain monitoring and consumer behavior analysis. The purpose of this research paper is to present an analytical study on how artificial intelligence can be useful in the field of trade analytics, how it qualitatively improves business efficiency, profitability and decision making, and what opportunities and challenges it poses for developing economies. Keywords-Artificial Intelligence, Trade Analytics, Machine Learning, Supply Chain, Economy, Data Analysis, Digital Transformation Introduction Trade is the main pillar of mankind's economy. Globalization and the development of digital technologies have drastically changed the structure of international trade. Over the last decade, Artificial Intelligence (AI) has revolutionized the way business decisions are made. Trade analytics is a field where large amounts of data are analyzed to make predictions about market trends, price changes, demand and supply structures, and consumer behavior. Here AI provides algorithms that provide faster and more accurate results. Concept of Artificial Intelligence Artificial intelligence is a technology that emulates the capabilities of human intelligence — which can learn, think, make decisions, and improve itself from new information. Major subdivisions of AI: 1. Machine Learning 2. Deep Learning 3. Natural Language Processing (NLP) 4. Predictive Analytics These subsections help in trade analytics to find patterns through data, identify risks, and automate business decisions. Importance of Trade Analytics Trade analytics is an important tool for business organizations as it offers the following benefits: Can understand market trends and sentiment. Can predict customer demand. Optimizing the supply chain. Reduces risks and can increase profits. Provides an information base for international trade policies. The use of AI doubles the accuracy and efficiency in all these areas. Applications of AI in Trade Analytics 1. Price Forecasting: AI can predict future sentiment trends by analyzing past sentiment data through machine learning models. 2. Supply Chain Management: AI helps improve logistics by monitoring every stage of the supply chain. Quick Response Code: Website: https://jrdrvb.org/ DOI: Creative Commons (CC BY-NC-SA 4.0) This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License, which allows others to remix, tweak, and build upon the work noncommercially, as long as appropriate credit is given and the new creations ae licensed under the idential terms. Address for correspondence: Dr. Raviprakash Kanaiyalal Mer, Assistant professor Shri K.R. Desai Arts & Commerce college, Jhalod How to cite this article: Raviprakash Kanaiyalal Mer, (2025) The Role of Artificial Intelligence in Trade AnalyticsJournal of Research & Development,17(10(IV)), 75-76 Original Article Journal of Research and Development Peer Reviewed International, Open Access Journal. ISSN : 2230-9578 | Website: https://jrdrvb.org Volume-17, Issue-10(IV)| October2025 76 3.Risk Management:AI systems provide timely warnings for global risks such as currency changes, political instability, or sudden market shifts. 4.Trade Fraud Detection:AI prevents fraud by detecting anomalous patterns in financial transactions. Data Analytics and Machine Learning in Trade Data is the “new oil” of the modern economy. Machine learning acts as an engine in trade analytics. For example — AI models analyze based on thousands of parameters (such as demand, supply, political situation, weather etc.) to predict crude oil prices in the international market. Benefits of AI in Global Trade Increases efficiency and speed in business processes. Costs are reduced. Human errors are reduced. Increases data-driven decision making. Customer satisfaction increases as service becomes more personalized. Examples of AI-based Trade Platforms 1. IBM Watson TradeLens – For Supply Chain Analytics. 2. Alibaba AI Systems – for market prediction. 3. Amazon Forecast – For forecasting demand and sales. 4. Google Cloud AI – for global business data analytics. Impact of AI in Indian Trade Sector The use of AI is growing rapidly with the growing impact of digitalization in the business sector in India. Especially in the following areas: E-commerce Logistics and Transportation Banking and Financial Trading Export-Import Data Analysis The use of AI technology is also increasing in formulating trade policy under the Government of India's “Digital India” and “Make in India” programmes. Challenges and Limitations 1. Data Privacy and Security 2. Lack of technical skills 3. High investment cost 4. Impact on employment 5. Regulatory and ethical issues Case Studies 1. Amazon India: Success in increasing marketing efficiency by identifying user preferences through AI-based predictive analysis. 2. Tata Consultancy Services (TCS): Developing AI models for analysis of international trade data is a big advantage in the export sector. 3. Maersk TradeLens: Increased transparency in global shipments through supply chain digitization. Future Prospects In the next decade, AI and big data analytics will be central to every phase of business. AI based smart trading systems, blockchain integration, and digital currency trading will revolutionize the trading sector. Conclusion Artificial Intelligence is no longer just a technology, but has become the fuel of the future of business. The use of AI in trade analytics has made trading smarter, faster and more profitable. Despite existing challenges such as data security and skills gaps, AI has reshaped the global business landscape. In times to come, AI-based trade analytics will become an indispensable tool for every country and company. References 1. World Trade Organization (WTO) Reports, 2023 2. OECD Digital Economy Outlook, 2022 3. IBM Watson AI TradeLens Documentation 4. Ministry of Commerce, Government of India, 2024 5. Accenture Report on AI in Global Trade, 2023 6. Deloitte Insights – “AI in Trade and Supply Chain”, 2024 7. Harvard Business Review – “AI-driven Trade Analytics”, 2022