Human-AI Collaboration in Financial Strategy: A Study on Trust, Accuracy, and Organizational Agility

Abstract

The increasingly popular adoption of artificial intelligence (AI) in decision making within the financial sector has transformed the strategic planning process of contemporary organizations. Rather than replacing human judgement, AI is currently being installed as an ally, improving analytical skills, prediction, and responsiveness to the changing market environment. In this paper, the author discusses the issues of human-AI cooperation that can be used to facilitate the development of financial strategies, and the focus is specifically on the issues of trust, the inaccuracy of decisions and agility of the organizations. The research is based on the empirical research data of financial professionals and strategic managers working in various industries to examine the position of trust in AI systems and its influence on ensuring the efficient use of algorithmic insights and the quality of strategic financial decision-making. The paper also evaluates whether the AI-advanced financial analysis can increase predictive accuracy and risk evaluation than the human-based procedures. Organizational agility analysis is viewed as an outcome variable, which is the ability of company to respond rapidly to the uncertainty of financial strategy, volatility, and competition pressures. The quantitative research design was employed in the collection and analysis of the data by use of structured questionnaires and statistical analysis to determine the relationship between major constructs. The findings reveal that the human-AI collaboration contributes to the precision of the final decisions made in case human experience is augmented with AI-related analytics, particularly in the complicated and data-intensive financial settings. The critical mediating factor is trust, and user acceptance and reliance on AI products are fundamentally based on it. Besides that, firms successfully using AI in finance strategy are more maneuverable, and as such, are able to plan the scenarios quicker and use resources better informed. The study will contribute to the growing literature on AI-enhanced management by showing the importance of socio-technical alignment in the process of financial strategy. Practically, the findings will be informative to those organizations that are interested in exploiting AI and escaping loss of human judgment, ethical oversight and strategic management. The paper ends off with the significance of having a governance structure that would promote trust and lifelong learning of the financial relationships between humans and AI.