IMPACT OF AI-POWERED DECISION-MAKING ON BUSINESS INDUSTRY EFFICIENCY: BASIS FOR PROPOSED AI-ASSISTED STRATEGIC PLANNING

Abstract

This chapter presents a study conducted at Teleperformance that explores the enhancement of AI-assisted strategic planning. The research underscores the growing role of artificial intelligence in business decision-making, while also acknowledging key challenges such as data bias and limited transparency in AI processes. One significant issue identified is the absence of a unified dashboard to effectively consolidate and present AI-generated insights. To address this gap, the study proposes the development of a predictive analytics dashboard designed to align AI outcomes with organizational goals, streamline decision-making, and drive operational growth and efficiency. This chapter details the research methodology utilized to examine the role of artificial intelligence in strategic business planning. A quantitative-descriptive research design was employed to gather empirical data. The study involved 133 respondents, primarily composed of corporate professionals and key decision-makers who actively implement AI in strategic processes. Using purposive sampling, participants were selected based on their expertise and direct involvement with AI integration. Data were collected through a structured survey consisting of three key sections: factors influencing AI-driven planning, the impact of AI on decision-making, and challenges in AI adoption. This approach ensured the acquisition of precise and relevant insights into how AI shapes modern strategic planning in the corporate sector. The study found that most of the 133 respondents from Teleperformance are young professionals aged 18 to 34, predominantly employed in customer service roles, and with relatively short tenure in the company. While participants acknowledged that artificial intelligence significantly enhances decision-making accuracy and operational efficiency, they also highlighted several key challenges to its integration in strategic planning. These challenges include concerns over data privacy, resistance to change within the organization, and a lack of sufficient knowledge or training in AI applications. The study concludes that although most Teleperformance employees are young professionals at the early stages of their careers, the effective integration of AI into strategic planning demands targeted training and inclusive mentorship programs. Perceptions of AI-driven decision-making are significantly shaped by concerns about data privacy, safety, fairness, and trust, with varying degrees of influence depending on employees’ roles and experience levels. To ensure successful AI adoption, it is essential to address organizational challenges such as readiness, knowledge gaps, and data security. Moreover, cultivating a culture that values transparency, innovation, and inclusivity will be crucial in maximizing AI’s strategic potential within the organization.