International Conference on Modern Artificial Intelligence & Data Science Systems

Abstract

Industrial AI systems are transforming modern industries, from manufacturing and energy to logistics and process control, enabling data-driven decision-making and operational efficiency. As these systems move from research prototypes to real-world deployment, ensuring trustworthiness becomes critical.

This keynote examines the current practice of industrial AI systems, highlighting successful implementations, common challenges, and lessons learned. It explores trusted AI principles: robustness under uncertainty, interpretability, and alignment with industrial processes.

Through real-world case studies, the talk demonstrates the impact of deploying trusted AI systems in industrial environments, emphasizing the enhancement of human confidence in AI-driven decisions.

Abstract

This talk presents a new vision of Frugal, Social, and Sovereign Artificial Intelligence, where Artificial Intelligence is conceived as a driver of human, economic, and social development rather than an end in itself. The approach emphasizes Augmented Intelligence and Digital Twins to address real-world challenges such as climate change, healthcare, education, sustainable development, and the Sustainable Development Goals (SDGs).

Focusing on the Moroccan context, the proposed model promotes energy efficiency, ethical and inclusive Artificial Intelligence, data sovereignty, and locally adapted solutions. By strengthening human and collective intelligence, this vision positions Artificial Intelligence as a catalyst for equitable growth, environmental responsibility, and long-term societal impact.

Abstract

Once typically used for critical applications and services, biometric technologies are now pervasively permeating our everyday life enabling seamless and convenient identification and authentication (e.g., passport control, smart phone unlocking, voice command, automatic photo tagging).

Artificial intelligence has been shown effective to extract the relevant knowledge from biometric data in order to increase the performance and deal with less-constrained and on-the-move acquisition of biometric traits.

The broad availability of biometric data challenges personal identity and privacy and imposes the need of biometric data protection to prevent misuse and impersonation. This lecture will illustrate the main biometrics techniques and the use of artificial intelligence, their strengths, limitations, and applications.

Abstract

Agentic AI marks a shift from reactive systems to autonomous agents capable of reasoning, planning, and acting toward defined goals. By integrating large language models with memory, tool use, and feedback loops, these agents exhibit adaptive intelligence suited for dynamic environments.

However, deploying them in production presents major challenges—ensuring reliability, ethical alignment, and control over emergent behavior. Scalability, data drift, and long-term memory management add technical complexity. Overcoming these hurdles demands combining adaptive RAG, reinforcement learning, and human oversight to create AI systems that act responsibly and augment human decision-making across real-world applications.

Abstract

This talk explores the advanced digitization of smart factory automation, highlighting the transition beyond traditional Industry 4.0 and 5.0 approaches. It focuses on digital transformation enabled by SAP Business AI, artificial intelligence, generative and agentic AI, as well as quantum technologies, including quantum AI and quantum machine learning, to address critical production challenges in battery manufacturing.

The presented approaches enable real-time data analysis, predictive maintenance, and efficient integration of legacy systems, significantly reducing downtime and improving resource management. By combining cutting-edge AI, quantum technologies, and business innovation concepts, this talk demonstrates how smart factories can achieve sustainable, efficient, and responsive manufacturing while strengthening supply chain performance and decision-making processes.