As the digital transformation reshapes business and organizational landscapes, there is a growing imperative for systems that not only process data but also understand human smartly. Traditional Business Intelligence (BI) platforms excel at numerical insights (tracking KPIs, sales figures, and operational performance), but often fall short in interpreting the exact context that strengthens human behaviour.

The Human-Centric Business Management Systems and Services Conference proposes a pioneering exploration into Intelligent Management Systems (IMS) and Business Intelligent Systems (BIS), an emerging class of enterprise systems that employ AI, LLMs, and affective computing to interpret and respond to emotional cues from employees, customers, and stakeholders. By integrating emotional intelligence (EI) into data analytics, enterprises can unlock real-time insights into organizational health, employee engagement, customer loyalty, and leadership effectiveness.

We invite researchers, practitioners, and technologists to present novel research, applications, and frameworks that combine intelligence with data-driven strategies to enhance enterprise decision-making, crisis response, sales optimization, and digital transformation.

Challenges and Competencies to be Addressed


Emotional Understanding in LLMs and other AI Models – Capturing emotional nuance across textual, visual, and audio channels using multimodal learning and contextual modeling.
Real-time Sentiment Integration in Management Systems – Adapting dynamically to emotional shifts detected from feedback loops, communications, and user interactions.
Ethics, Trust, and Transparency – Managing privacy, ethics, and cultural sensitivity in deploying emotion-aware AI tools.
Scalability and Responsiveness in High-Performance Settings – Processing emotional intelligence data in real-time without bottlenecks.
Bridging Structured BI with Unstructured Emotional Data – Combining KPIs with affective analytics for holistic decision tools.
Topics of Interest

Original papers on all topics related to Human-Centric Management Systems and Services, and Business Intelligent Systems will be welcome submissions, (including but not limited to):

Emotionally Intelligent Executive Dashboards – Embedding sentiment analysis for real-time insight into organizational well-being.
Strategic Workforce Well-being Insights – Detecting stress/disengagement via communication and surveys for proactive HR policy.
Emotion-Driven Customer Intelligence – Leveraging consumer sentiment for product and marketing optimization.
Sales Optimization through Emotional Analytics – Using emotional cues to improve lead qualification and closure rates.
Adaptive Learning for Talent Development – Using attention/sentiment to optimize training content dynamically.
Emotionally-Informed Leadership Decision Tools – Combining financial data with emotional context to support decisions.
Crisis Management with Emotional Foresight – Monitoring sentiment to guide communication and interventions.
Emotionally Intelligent Sales Systems – AI-assisted sales coaching using tone and behavioral cues.
Driving Innovation through BI and EI – Measuring innovation openness through emotional analytics and BI metrics.
Knowledge Management with Emotional Engagement – Measuring emotional engagement in knowledge-sharing systems.
Digital Transformation and Policy Adoption – Assessing emotional readiness during rollouts to increase adoption rates.
Target Audience


Enterprise Architects and Software Engineers
Organizational Behavior and HR Analytics Professionals
Business Intelligence Analysts
AI/ML Researchers and Practitioners
LLM and NLP Specialists
Human-Centered Design and UX Experts
Telecommunications and IoT System Innovators
Ethical AI Policymakers and Strategists
Expected Outcomes


Framework for integrating EI into AI-powered enterprise management
Cross-disciplinary collaboration among AI, business, and telecom experts
Real-world applications and measurable impacts of Emotion AI
Ethical, social, and organizational implications of emotionally adaptive systems
Technical standards and architecture guidelines for future EIMS