AI AGENTS IMPROVE AUTOMATION, IDENTIFY ANOMALIES, AND PREDICT ECONOMIC IMPACTS
Agents powered by artificial intelligence greatly enhance anomaly detection, economic forecasting, and robotization of commercial processes.In order to assess the impact on efficiency and judgement, they are also essential.The incorporation of AI agents can enhance economic forecasting, speed the detection of abnormalities, and simplify business operations.In the end, this results in better decisions and outcomes.Businesses are able to spot problems and predict economic trends more rapidly thanks to their enhanced decision-making and efficiency capabilities.This leads to better, more strategic outcomes.Increased automation, anomaly detection, and economic effect prediction are just a few ways in which artificial intelligence (AI) agents are changing industries.With an expected increase from $5.1 billion in 2024 to $47.1 billion by 2030, the market for automation solutions powered by AI is showing signs of significant adoption and trust in these technologies.AI agents significantly boost productivity; businesses have seen a 90% uptick in process quality and a 40% drop in operational expenses as a result.To guarantee security and operational integrity, AI agents must maintain a 95% accuracy rate in anomaly detection.With a 38% increase in fraud detection rates, this is particularly noteworthy in the financial sector.Artificial intelligence (AI) models include real-time data to help organisations overcome market volatility and make the most of their resources; they exceed traditional approaches by 85% in economic forecasting.The capacity of AI agents to boost growth, enhance accuracy, and optimize efficiency across industries is a clear indication of their revolutionary powers.The significance of artificial intelligence (AI) in the pursuit of operational excellence and strategic benefits in the dynamic digital world is highlighted in this study.
Authors
- Kudisay Kaladhar Babu
- A. Rupaveni
- Vandana Samba
Publication Details
- Journal
- International Journal of Advances in Business and Management Research
- Published
- 2025-01-01
- DOI
- https://doi.org/10.62674/ijabmr.2025.v3isupp1.015
- Primary Topic
- Complex Systems and Time Series Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00