About the Journal

Aim And Scope

Engineering driven Businesses can now make data-driven decisions more effectively, leading to enhanced productivity and cost savings. AI-driven analytics and predictive modelling allow companies to gain deeper insights into customer behaviour, market trends, and operational performance, enabling them to tailor products and services more effectively and respond to changing market dynamics with agility. IJAIMD seeks to provide a scholarly platform where researchers can contribute the latest studies on the impact that AI technologies have within business and management domains and support decision making policies to yield maximum profit. AI utilization in business is crucial as it not only enhances operational efficiency and decision making, but also generates vast datasets, creating a rich source for research. IJAIMD is abided to publish only high-quality research papers of different categories original Research Articles, Review Articles, Survey Articles, Case studies, Technical Notes, and Short Communication. Through rigorous peer review and a commitment to academic excellence, this journal offers invaluable knowledge to academics, industry professionals, students, and innovators seeking to harness the power of AI for competitive advantage on a global scale.

Scope

IJAIMD is an interdisciplinary refereed journal focusing on management aspects related to smart computing, decision making policies to support business and promote their future growth. The IJAIMD welcomes the original, unpublished high-quality manuscripts for publication in the following topics (but are not limited to the following):
  • AI and ethics in decision-making
  • AI in financial modeling and investment analysis
  • AI-driven fraud detection and prevention
  • AI in policy making for strategic markets
  • AI-enhanced cybersecurity for business protection
  • AI-enhanced data analytics for business intelligence
  • Explainable AI for regulatory compliance
  • Human resources management with AI for recruitment and talent retention
  • Logistics and supply chain management
  • Machine learning for customer segmentation and targeting
  • Natural language processing in chatbots for customer support
  • Predictive analytics for demand forecasting
  • Quality control and production optimization
  • Recommendation systems for e-commerce
  • Robotic process automation (RPA) in business processes
  • Robotics and AI in manufacturing processes
  • Sentiment analysis in financial markets
  • Supply chain optimization with AI
  • Decision support systems
  • Knowledge driven expert systems
  • Neural Networks and algorithms for bioinspired systems