Disengagement at a median-sized S&P 500 company present losses of $228 to $355 million annually (McKinsey). Worldwide annual disengagement costs $8 trillion (Gallup)
The hype surrounding Artificial Intelligence (AI) promises a revolution in workforce productivity. However, a closer examination of the data reveals a more nuanced picture.
The pressure is mounting on middle managers to draw actionable insights from vast information streams. Middle manager layoffs are likely to leave gaps that AI could easily fill.
AI excels at analyzing vast datasets, uncovering hidden patterns invisible to traditional methods. But McKinsey's research shows that traditional analytics have contributed much more in potential aggregate value.
Despite human capital's higher value (2.5 times the combined value of offices, plants, IT and machinery), AI's impact has been felt much more in fixed asset areas. Five things came out of the analysis of 400 use cases across 19 industries reveals some surprising truths:
Traditional analytics methods currently outperform AI in terms of workforce productivity gains.
AI's impact on fixed assets is significantly higher compared to its influence on human capital, a resource valued 2.5 times more.
Learn more at this blog article
Traditional analytics has delivered between 5 and 8 times greater impact on workforce productivity compared to AI powered tools ($0.7 to $0.9 trillion in EVA versus $117 billion to $153 billion)
Despite human capital being valued 2.5 times more than all fixed assets combined (offices, technology, machinery), the impact of AI on fixed assets is 23 to 50 times greater.
Let's move beyond AGI as a hypothetical human replacement. Instead, let's focus on intelligence not mimicry, working with humans with clear goals in the domain
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