This chapter examines humanoid and virtual AI leaders as a new model of enterprise decision-making, with particular focus on the cases of Mika, the humanoid CEO of Dictador, and Tang Yu, the virtual CEO of NetDragon Websoft. The analysis investigates how artificial intelligence is increasingly integrated into strategic, operational, and managerial processes, moving beyond a traditional decision-support function towards a more active role in organisational governance. The study applies a qualitative case study methodology based on corporate reports, public statements, interviews, and secondary academic literature. The findings indicate that AI-based leaders may enhance operational efficiency, support continuous data analysis, improve forecasting capabilities, and optimise resource allocation. At the same time, the analysis identifies significant organisational and ethical challenges related to transparency, explainability, accountability, bias, and human oversight. The chapter further discusses the implications of AI-driven leadership for managerial roles, team dynamics, and enterprise governance structures. It is argued that the effective implementation of humanoid and virtual leaders requires human-centric governance frameworks that combine the analytical capabilities of AI systems with human responsibility, ethical judgment, and organisational control mechanisms.
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.
Zheying Zhang, M. Rayhan, Tomas Herda et al.· International Conference on...· 48 citations· ⚡4
This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.
Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al.· arXiv.org· 44 citations· ⚡2
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al.· arXiv.org· 41 citations
AI is making software generation faster, but speed does not remove the need for expertise. As more work is delegated to AI, tacit knowledge may become one of the most important human advantages in software engineering. The post Beyond Prompt Engineering: The Role of Tacit Knowledge in Software Engineering appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduSep 16, 2026
The “HardFlow” algorithm could help generative AI models produce high-quality outputs that obey strict requirements when “pretty close” doesn’t cut it.
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