The AI In Economic Analytics Market is being driven by Intensifying demand for predictive and prescriptive economic intelligence
The AI In Economic Analytics Market is expected to grow at a CAGR of 36.2% during 2024 and 2029. During this period, the market is also expected to show a growth of USD 39382.6 million. The global AI in economic analytics market is experiencing a significant shift, with the increasing maturity and integration of Generative Artificial Intelligence (AI) and Large Language Models (LLMs) leading the way. This transition signifies a paradigm change from conventional econometric and statistical models to more nuanced, context-sensitive systems. The primary consequences of this evolution are twofold: the automation of intricate analytical narratives and the enhancement of predictive forecasting via advanced scenario simulations. Key players in the financial sector, government agencies, and corporations in North America and Europe are spearheading the adoption curve, utilizing these advanced technologies to secure a competitive edge and inform informed decision-making.
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The market is segmented based on
According to Technavio, There are several factors that are causing the market to flourish during the forecast period, which are as follows:
However, the market also witnesses some limitations, which are as follows:
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Market Scope |
|
Report Coverage |
Details |
Page number |
248 |
Base year |
2024 |
Historic period |
2019-2023 |
Forecast period |
2025-2029 |
Growth momentum & CAGR |
Accelerate at a CAGR of 36.2% |
Market growth 2025-2029 |
USD 39382.6 million |
Market structure |
fragmentation |
YoY growth 2024-2025(%) |
34.1 |
Key countries |
US, China, Germany, Canada, India, UK, Japan, France, Australia, and Brazil |
Competitive landscape |
Leading Companies, Market Positioning of Companies, Competitive Strategies, and Industry Risks |
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In the realm of AI for Economic Analytics, neural network architectures are utilized, alongside data preprocessing methods and feature engineering techniques, to prepare data for analysis. Model evaluation metrics, validation strategies, and parameter optimization methods are employed to assess model performance. Hyperparameter tuning, cross-validation techniques, backtesting methodologies, and Monte Carlo simulations are used for model refinement. Bayesian inference, Markov chain models, agent-based modeling, and system dynamics modeling are advanced techniques for economic forecasting. Econometric software packages, statistical programming languages, data wrangling techniques, data cleaning procedures, and data transformation methods facilitate data manipulation. Data visualization libraries, database management systems, and cloud storage solutions ensure efficient data management. Data security protocols and privacy preserving techniques protect sensitive information. Model interpretability methods and explainable AI techniques enhance model understanding. Model deployment strategies and monitoring systems ensure continuous improvement.
In the IT software industry, the economic analytics market is a significant segment, encompassing machine learning models, economic forecasting models, predictive analytics tools, and time series forecasting. This market falls under the application software category, focusing on specialized business applications. Technavio's market analysis covers revenue generated by companies providing these advanced analytics solutions, contributing to the overall IT software market size. These firms specialize in enterprise and technical software, as well as cloud-based solutions, excluding those in the interactive home entertainment or systems software sectors.. Industries are leveraging the products belonging to the market for customer engagement, transactional notifications, and promotional offers.
Technavio Research
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