The International Conference on Applied Artificial Intelligence in Business and Economics (AAIBE 2026) is a premier global event that brings together scholars, industry professionals, researchers, and policymakers to exchange knowledge, share cutting-edge research, and explore the transformative power of artificial intelligence across business and economic domains. AAIBE 2026 aims to accelerate digital transformation by bridging the gap between AI innovation and its real-world applications in business processes and economic systems.
This conference provides a collaborative platform to discuss emerging technologies, tackle current challenges, and highlight how AI-driven insights and intelligent automation are revolutionizing strategic planning, operational efficiency, and decision-making in the modern economic landscape. Participants will gain insights into how businesses and economies can leverage AI for resilience, adaptability, and sustainable growth.
AAIBE 2026 welcomes original research papers, case studies, and thought leadership contributions from academics, practitioners, and industry experts. Whether your focus is on transforming financial analytics, optimizing supply chains, enhancing customer experience, or addressing ethical considerations in AI, this conference is designed to inspire dialogue, foster partnerships, and shape the future of AI in business and economics.
AAIBE 2026 invites original work from the following list of topics (but is not limited to):
1: AI in Economic Modeling and Forecasting
AI for macroeconomic prediction and stability analysis
Machine learning in GDP and inflation forecasting
Deep learning applications in trade and investment modeling
AI in time-series and panel data econometrics
Forecasting business cycles using AI
Real-time economic indicators via big data
Sentiment analysis for economic policy impact
Predictive modeling for economic crisis management
Automated econometric model selection and optimization
Hybrid models combining AI with traditional economics
AI in labor market trend analysis
Energy and resource economics using AI tools
AI-based public finance and taxation modeling
Use of reinforcement learning in economic games
High-frequency data analytics in financial economics
2: AI in Financial Systems and Risk Analytics
Algorithmic trading strategies with AI
AI in credit risk modeling and scoring
Machine learning in anti-money laundering (AML)
Financial fraud detection using neural networks
AI in insurance underwriting and claims processing
AI-based stress testing in banking systems
Blockchain and AI convergence in finance
Financial sentiment analysis using NLP
Real-time risk analytics for portfolio management
AI in financial advisory and robo-advisors
Predictive analytics for loan defaults
AI in cryptocurrency markets and fintech innovation
Risk mitigation through AI in capital markets
Explainable AI in financial decision systems
Behavioral finance and AI-driven insights
3: Intelligent Business Operations and Process Automation
Robotic Process Automation (RPA) in finance and HR
AI in supply chain and logistics optimization
Predictive maintenance using AI and IoT
Real-time inventory optimization using ML
AI in business process reengineering
Digital twins for operational efficiency
Chatbots and intelligent agents in operations
Process mining and AI for bottleneck detection
Smart warehouse and logistics systems
Demand forecasting and order fulfillment
Intelligent ERP and CRM systems
AI in production scheduling and quality control
Workflow automation in customer service
Intelligent document processing
Cost reduction strategies through intelligent automation
4: AI in Marketing, Sales, and Consumer Insights
AI in hyper-personalization of customer experiences
Recommendation engines for e-commerce
Customer journey mapping using AI
Predictive modeling of customer lifetime value
Chatbots and virtual assistants for sales support
Sentiment analysis for brand perception
Real-time marketing campaign optimization
NLP for market trend detection
AI in programmatic advertising and media buying
Visual recognition for retail marketing
Content generation using generative AI
Social media listening and influence scoring
Lead scoring and automated pipeline management
Emotion AI for ad targeting
Customer churn prediction and retention strategies
5: Human Capital and Organizational Transformation
AI for talent acquisition and recruitment analytics
Skill gap analysis and reskilling using AI
AI-driven performance evaluation and management
Workforce planning and predictive hiring
Employee sentiment analysis
AI in leadership development and succession planning
Automation in HR operations
Diversity, equity, and inclusion analytics
AI for virtual collaboration and engagement
Digital twins of the workforce
AI in mental health and employee wellbeing programs
Learning and development platforms powered by AI
Adaptive training and microlearning using ML
Organizational change modeling using AI
Ethical and legal implications of AI in HR
6: Strategic Management and Corporate Governance with AI
Strategic planning using AI and big data
Competitive intelligence via AI analytics
M&A deal analysis using AI tools
Boardroom decision support systems
Predictive governance and compliance monitoring
AI in benchmarking and KPI optimization
AI-driven SWOT and PESTLE analysis
Scenario planning using simulation models
AI for business model innovation
Strategic portfolio management
Predictive analysis of corporate performance
AI for internal auditing and risk mitigation
Role of AI in stakeholder engagement
Crisis management strategies using AI
Corporate social responsibility analysis using AI
7: AI in Sustainable Business and ESG Integration
AI for real-time carbon footprint tracking
Energy usage and efficiency optimization
Waste management and circular economy modeling
Predictive analytics for climate risk assessment
ESG reporting automation
Supply chain sustainability analysis
AI in ethical sourcing and procurement
Social impact analysis using NLP and AI
Corporate sustainability scoring and benchmarking
Green finance and AI-based investment modeling
AI for sustainable agriculture and food systems
Responsible consumption pattern analysis
Environmental policy simulation using AI
Smart urban planning and AI
AI in biodiversity and conservation modeling
8: Policy, Ethics, and Regulation in AI-Powered Economies
Algorithmic accountability and fairness
AI policy development and governance models
Ethical frameworks for AI in business
Regulation of AI in financial and economic systems
Privacy-preserving machine learning
Transparency in AI decision-making
Data ownership and consent in AI systems
Cross-border AI regulatory harmonization
Explainable AI in public services
Risk frameworks for AI deployment
Legal implications of autonomous decision-making
AI and labor displacement policy
Bias mitigation in business algorithms
AI’s impact on taxation and public finance
AI literacy for policymakers and executives
9: AI and Digital Transformation of Industries
Industry 4.0 and smart manufacturing
AI in retail and omnichannel commerce
AI in agriculture and agribusiness
Healthcare economics and AI-driven diagnostics
AI in tourism and hospitality management
Digital banking and AI in customer onboarding
AI in transportation and logistics
AI in legal tech and contract analysis
EdTech and intelligent learning systems
AI in telecommunications and 5G networks
Media and entertainment personalization with AI
Energy sector transformation using AI
AI for public sector transformation
AI adoption in small and medium enterprises (SMEs)
Startups and entrepreneurship in AI-driven ecosystems
10: Education, Knowledge Systems, and AI in Business Schools
AI in personalized learning and adaptive assessments
ChatGPT and LLMs in classroom settings
Business simulations powered by AI
Curriculum design using AI analytics
Intelligent tutoring systems
Digital mentorship and coaching
AI in knowledge management and archival systems
Measuring learning outcomes using AI
Predictive analytics for student performance
AI in online program delivery and MOOCs
Ethics of AI use in education
Institutional strategy powered by AI tools
Automation in academic research management
AI for peer review and academic publishing
Future of management education in the AI era