Although the term Artificial Intelligence (AI) was coined in the 1950´s, more recently, it has been at the centre of unprecedented attention. Developments in AI technology have created much interest from all areas of society, such as Education, Business and Health. The benefits of deploying AI are being reported transversally in all sectors. Nonetheless, AI’s potential evolves hand in hand with unyielding concerns that cause restraint and limit its widespread use. The International Conference on Artificial Intelligence in Society (AIS) aims to reunite both researchers and practitioners in addressing AI most pressing questions. The conference´s main areas and topics are identified bellow in a non-exhaustive list.
 
1. Core AI Research and Methodologies
• Machine learning and deep learning advances
• Natural language processing and multimodal AI
• Reinforcement learning and autonomous systems
• Explainable and interpretable AI
• Human-in-the-loop and hybrid intelligence systems
• Edge and distributed AI architectures
• AI and Security
• Chatbots and virtual assistants 		

2. AI in Education
• Adaptive learning platforms and personalized education
• AI for assessment and feedback automation
• Educational data mining and learning analytics
• Virtual tutors and AI-assisted teaching
• Ethical implications of AI in learning environments
• AI-enhanced learning technology
		
3. AI in Healthcare
• AI for diagnostics, imaging, and predictive healthcare
• Genomic data analysis and bioinformatics
• AI in mental health and well-being applications
• Medical data privacy and security
• Human-AI collaboration in clinical decision-making
• Data analytics in healthcare
• Personal health assistants 		

4. AI in Business, Industry, and Economics
• Predictive analytics and forecasting
• Generative AI for productivity and automation
• AI in finance, risk assessment, and fraud detection
• Intelligent supply chains and logistics
• AI-driven entrepreneurship and innovation ecosystems
• Customer support and engagement
• Data-driven decision making
• AI-powered business analytics
		
5. AI Ethics and Legislation/Regulation
• Trustworthy and responsible AI
• Ethical AI policies and practices
• Algorithmic bias and discrimination
• Transparency and explainable AI
• Legal frameworks and regulatory compliance
• Privacy and data protection
• Global AI governance and international standards
• AI safety and human-in-the-loop systems
• Intellectual property in AI-generated works 		

6. AI for the Progress of Society
• Democratisation of technological development
• Disaster response and humanitarian aid
• Inclusive and accessible technology
• Social justice and human rights monitoring
• Misinformation and fake news prevention
• Smart cities and urban planning
• Democratic and active citizenship
• Sustainability and environmental protection