AI could undermine managers judgment unless used carefully, study warns

Billy Odell Tucker-Robinson Founder & Host — Banking With Billy Network • Intelligence Network • Data Science • AI Research • World News
Published: 2026-09-05T08:40:28.163Z • Permanent link

Experts at the prestigious Harvard Business Review have issued a warning that generative artificial intelligence (Gen-AI) could undermine managers' judgment unless used carefully. This comes at a time when AI is increasingly being integrated into various aspects of business, including decision-making, strategy development, and performance evaluation. According to a recent study published by the Harvard Business Review, managers who rely too heavily on AI may struggle to build moral insights, contextual understanding, and the know-how to make informed decisions. Researchers at the University of Oxford, led by Dr. Elif Aydogan, have found that AI systems can perpetuate biases and reinforce existing power structures, further exacerbating social inequalities.

The warning comes as major corporations, including Google and Microsoft, are already investing heavily in AI-powered decision-making tools. For instance, Google's AI-powered recruitment platform has been shown to discriminate against women and minority groups, highlighting the need for more nuanced approaches to AI development. Meanwhile, regulators in the European Union are grappling with the implications of AI on employment and the labor market. In the United States, the Federal Reserve has launched a study into the potential impact of AI on financial stability, recognizing the need for policymakers to stay ahead of the curve.

The stakes are high, as managers who fail to adapt to the changing landscape of AI may find themselves struggling to compete with more technologically savvy rivals. For instance, in the airline industry, AI-powered systems have been shown to optimize flight routes and schedules, leading to significant cost savings and improved efficiency. However, this also raises concerns about the potential for job displacement and the need for workers to develop new skills.

The potential consequences of relying too heavily on AI-powered decision-making tools are far-reaching and could have significant implications for companies, research communities, and markets. For instance, the financial services sector is already experiencing the impact of AI, with some firms using AI-powered systems to detect and prevent financial crimes. However, this also raises concerns about the potential for AI to perpetuate existing biases and reinforce social inequalities. In the healthcare sector, AI-powered systems are being used to diagnose diseases and develop personalized treatment plans, but this also raises concerns about the potential for AI to exacerbate existing health disparities.

The impact of AI on research communities is also a pressing concern, as the technology has the potential to disrupt traditional methods of data analysis and research. For instance, AI-powered systems have been used to analyze large datasets and identify patterns and trends that would be difficult or impossible to detect using traditional methods. However, this also raises concerns about the potential for AI to perpetuate existing biases and reinforce social inequalities. In the world of finance, AI-powered systems are being used to analyze market trends and make predictions about future market behavior, but this also raises concerns about the potential for AI to exacerbate existing market volatility.

The rise of AI-powered decision-making tools is part of a larger pattern of technological disruption that is transforming various aspects of business and society. For instance, the use of blockchain technology has the potential to revolutionize supply chain management and financial transactions, while the rise of the gig economy has led to significant changes in the way we think about work and employment. In the world of finance, the use of AI-powered systems has the potential to disrupt traditional methods of investment analysis and portfolio management.