Track 10: Data Science & Artificial Intelligence (CDSA)

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Call for Papers

Organizations are undergoing a profound transformation, propelled by advances in artificial intelligence, machine learning and real-time data processing. These advancements are redefining how organizations operate, compete and create value in an increasingly data-driven world. This track invites rigorous empirical, theoretical and methodological contributions that deepen our understanding of AI-driven transformation. We are particularly interested in advancements in data science and AI with a focus on business, policy and societal outcomes.

We invite submissions on a broad range of topics, including but not limited to the following:

AI and Organizational Transformation

• AI-driven business models and digital transformation

• Human–AI collaboration and augmentation of work

• AI in strategic decision-making and leadership

• Organizational design in the age of automation

Machine Learning and Advanced Analytics

• Predictive, prescriptive, and causal analytics

• Deep learning, reinforcement learning, and generative AI

• Explainable and interpretable AI 

• Scalable and real-time analytics systems

Data-Driven Decision-Making

• Data governance, data quality, and data infrastructure

• Decision intelligence and algorithmic management

• A/B testing, experimentation, and causal inference

• Behavioural implications of data-driven systems

AI Applications Across Domains

• Marketing analytics and personalization

• Finance, fintech, and risk modeling

• Operations, supply chain, and logistics optimization

• Healthcare analytics and digital health

• Public policy, governance, and smart cities

Ethics, Fairness, and Responsible AI

• Bias, fairness, and accountability in AI systems

• Privacy, security, and regulatory frameworks

• Societal and economic implications of AI adoption

• Responsible innovation and AI governance

Emerging Frontiers

• Generative AI and large language models in organizations

• AI for sustainability and ESG outcomes

• Platform ecosystems and data marketplaces

• AI in emerging markets and developing economies