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McKinsey warns AI-driven analysis could slow decision-making, weaken future leadership pipeline

McKinsey warns AI-driven analysis could slow decision-making, weaken future leadership pipeline

New Delhi [India], November 9 (ANI): While artificial intelligence (AI) is making business analysis significantly faster, human decision-making is struggling to keep pace. This mismatch could increase strategic risks and weaken the development of future business leaders, as per a McKinsey report. 
AI is creating new decision-making bottlenecks by accelerating analysis beyond executives' capacity to assess its findings, it noted.
"Leaders who receive a high volume of decision inputs from black box sources may even make decisions more slowly than they used to," McKinsey said, highlighting executives may need additional time to verify AI-generated findings, which further limits the expected efficiency gains from AI investments.
Highlighting three major risks associated with the growing use of AI in strategic decision-making, the report warned that companies prioritising efficiency over scrutiny could face an increased risk of failed strategic decisions.
It stressed, "...companies use AI to generate more and faster analyses, which can bury leaders in a deluge of decisions and divert attention away from more critical problems."
The report further warned that as AI increasingly takes over analytical tasks, junior employees could lose valuable hands-on experience needed to develop judgment, potentially weakening companies' future leadership pipelines.  
It also cautioned that AI-generated analysis could be repeatedly processed by other AI models, creating a cycle of increasing analytical output while reducing human understanding and accountability.
" As AI takes on more analysis and interpretation, people may become less inclined to question its findings. "
Citing an example, McKinsey highlighted that a junior team at one company used AI to produce analytical outputs 10 to 20 times faster and evaluate three to five times as many scenarios for a strategic decision.
However, executives required more time to review the results because they lacked clarity on the underlying assumptions and data sources, demonstrating how faster analysis does not necessarily translate into quicker decisions.
"As analysis accelerates, judgment becomes the new bottleneck. This situation introduces new risks to strategic decision-making," it further stressed. 
To address these challenges, McKinsey recommended three measures: expanding organisational capacity for human judgment, strengthening employees' ability to assess and verify AI-generated analysis, and maintaining accountability for AI-assisted decisions. 
Overall, it stressed, "The winners will not be the organizations that automate the most decisions. They will be the ones that make the best use of AI’s speed while protecting the human judgment that AI cannot replace." (ANI)

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