Abstract/Description

The integration of Artificial Intelligence (AI) into business operations has ushered in a new era of innovation, efficiency, and growth, enabling organizations to streamline processes, enhance decision-making, and unlock new revenue streams. However, the widespread adoption of AI also brings with it significant ethical challenges that must be addressed. These concerns include algorithmic bias, data privacy infringements, lack of transparency in decision-making, and the displacement of human workers due to automation. These challenges have raised critical questions about how AI can be implemented in a way that not only advances business goals but also aligns with broader societal values and ethical principles. This study aims to explore the role of ethical AI in driving people-centered transformation in businesses. By employing a mixed-methods research design, this study investigates the ethical dilemmas businesses encounter during AI implementation and the strategies they adopt to address these concerns. The research is divided into two components: qualitative case study analysis and quantitative survey data collection. The qualitative component involves an in-depth analysis of three case studies from diverse industries, including healthcare, finance, and retail, where AI technologies are currently being implemented. These case studies provide real-world insights into the ethical challenges faced by businesses and the mechanisms used to mitigate these challenges. The quantitative component consists of a survey administered to 250 business leaders and AI professionals across various sectors. The survey aims to capture data on their awareness of ethical AI principles, the ethical challenges they encounter, and the steps taken to implement AI responsibly within their organizations. The findings from both the case studies and the survey are used to develop a comprehensive framework for ethical AI governance. This framework emphasizes the importance of aligning AI deployment with principles of fairness, accountability, transparency, and inclusivity. The research proposes that businesses must take a holistic approach to AI implementation, incorporating both technical efficiency and ethical considerations, to ensure that AI contributes to people-centered transformation. By focusing on equity and social responsibility, the study provides valuable insights into how businesses can use AI to drive positive, sustainable change while minimizing the risks of harm.

Keywords

Ethical AI, People-Centered Transformation, Business Ethics, AI Implementation, Fairness and Transparency

Track

Marketing

Session Number/Theme

Marketing - Session II

Session Chair

Dr. Mahar Ali

Start Date/Time

14-6-2025 10:55 AM

End Date/Time

14-6-2025 12:35 PM

Location

MCC -15 2nd Floor, AMAN CED Building

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Jun 14th, 10:55 AM Jun 14th, 12:35 PM

Ethical AI in Business: Leveraging Technology for People-Centered Transformation

MCC -15 2nd Floor, AMAN CED Building

The integration of Artificial Intelligence (AI) into business operations has ushered in a new era of innovation, efficiency, and growth, enabling organizations to streamline processes, enhance decision-making, and unlock new revenue streams. However, the widespread adoption of AI also brings with it significant ethical challenges that must be addressed. These concerns include algorithmic bias, data privacy infringements, lack of transparency in decision-making, and the displacement of human workers due to automation. These challenges have raised critical questions about how AI can be implemented in a way that not only advances business goals but also aligns with broader societal values and ethical principles. This study aims to explore the role of ethical AI in driving people-centered transformation in businesses. By employing a mixed-methods research design, this study investigates the ethical dilemmas businesses encounter during AI implementation and the strategies they adopt to address these concerns. The research is divided into two components: qualitative case study analysis and quantitative survey data collection. The qualitative component involves an in-depth analysis of three case studies from diverse industries, including healthcare, finance, and retail, where AI technologies are currently being implemented. These case studies provide real-world insights into the ethical challenges faced by businesses and the mechanisms used to mitigate these challenges. The quantitative component consists of a survey administered to 250 business leaders and AI professionals across various sectors. The survey aims to capture data on their awareness of ethical AI principles, the ethical challenges they encounter, and the steps taken to implement AI responsibly within their organizations. The findings from both the case studies and the survey are used to develop a comprehensive framework for ethical AI governance. This framework emphasizes the importance of aligning AI deployment with principles of fairness, accountability, transparency, and inclusivity. The research proposes that businesses must take a holistic approach to AI implementation, incorporating both technical efficiency and ethical considerations, to ensure that AI contributes to people-centered transformation. By focusing on equity and social responsibility, the study provides valuable insights into how businesses can use AI to drive positive, sustainable change while minimizing the risks of harm.