Abstract Submission deadline extended to 30.09.24. For submission click here

Themes & Tracks

Theme of the Conference and Specific Tracks

Theme

The theme "Reimagining Human Resources and Workplace in the world of Artificial Intelligence" explores the integration of AI in different HR functions to enhance efficiency, decision-making, and employee engagement. It suggests a data-driven approach to talent management, where AI's predictive capabilities and HR analytics inform personalized experiences. The theme also covers the ethical considerations and impacts on workforce dynamics, as human intuition and AI coexist. The conference serves as a platform for thought leaders to discuss the strategic integration of AI tools, harmonizing technology and human elements, and creating a resilient, technologically empowered workplace.

Specific Tracks

Track 1:
Algorithmic HRM and Intelligent Technology: Implications for Work, Organizations and People

This conference track invites research papers related to the impact of AI-driven algorithmic management on organizational operations and employee relations, examining the efficiency gains it presents. We invite papers that cover the following areas:

  • 1.1 Algorithmic Human Resource Management (HRM)
  • 1.2 The Rise of Intelligent Technology like chatbots and virtual assistants in the Workplace
  • 1.3 The Rise of Intelligent Technology like generative AI in the Workplace
  • 1.4 Changing Nature of Work in the AI Era

Track 2:
HR Analytics and Technology in HR

The "HR Analytics and Technology in HR" conference track focuses on leveraging data analytics and technology to enhance HR practices, aiming to transform HR from a cost centre to a strategic, value-adding element of business. We invite papers that cover the following areas:

  • 2.1 Data-Driven Decision-Making in HR
  • 2.2 Predictive Analytics for HR functions
  • 2.3 Big Data in HR: Collection, Storage, and Analysis

Track 3:
AI Applications in HR Functions

The "AI Applications in HR Functions" conference track urges participants to contribute to the integration of AI in HR to improve various HR functions. With a focus on various AI applications in HR functions, the track invites research papers on the integration of AI in the following HR functions and roles:

  • 3.1 AI in Talent Acquisition /Engagement / Retention
  • 3.2 AI in Learning & Development
  • 3.3 AI in Performance and Rewards Management
  • 3.4 AI in Leadership and shaping the DEI agenda

Track 4:
Ethical and Legal Implications of AI in HR

This conference track addresses the critical concerns surrounding the ethical use and legal boundaries of AI in human resource management, focusing on privacy, bias, and regulatory compliance. We invite participants to engage in this vital discourse and contribute their perspectives to the following topics:

  • 4.1 Ethical Considerations in AI-driven HR Practices
  • 4.2 Bias and Fairness in AI Algorithms
  • 4.3 Data Privacy and Security in AI-HR Systems
  • 4.4 Transparency and Explainability in AI in HRM

Track 5:
Future trends and innovations in AI-HR solutions

The "Future Trends and Innovations in AI-HR Solutions" conference track not only throws a spotlight on the latest developments in AI for HR but also strategizes on how organizations can proactively adopt these innovations to stay ahead of the curve in a rapidly evolving digital landscape. We invite thought leaders and innovators to contribute their insights in the following topics:

  • 5.1 Integrating emerging technologies like AR, VR and Blockchain with AI-HR solutions
  • 5.2 Personalization of employee experience with AI-HR Solutions
  • 5.3 The Future of Work: Human-AI Collaboration in HR and the Workplace

* We invite a 400-600 word abstract followed by a full paper of 4000-6000 words

* Submissions are not restricted to the specific tracks outlined, papers are welcome on research areas that align with the broad focus of HRM

  • call us

    044-28177100

  • Mail us

    aihrconf2025@liba.edu

  • location

    LIBA, Loyola College Campus, Chennai - 34