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The article primarily addresses the gap between rapid consumer AI adoption and sluggish enterprise productivity gains, framing this as an organizational transformation deficit rather than a technical failure. It analyzes data from McKinsey's 2026 survey to illustrate that high economic impact requires end-to-end workflow redesigns, which only a minority of companies have achieved so far. This analysis is central to understanding the practical deployment challenges and economic realities of current AI implementation in business settings.
The paradox at the core of the AI revolution: The faster we innovate, the slower we grow
Fifty years of digital innovation delivered spectacular adoption and declining productivity. Will AI repeat that pattern?
To hear Silicon Valley tell it, artificial intelligence will usher in a glorious new era of abundance. But ask the chief financial officers of the world’s largest companies how AI is transforming their bottom line and, per McKinsey’s 2026 State of AI survey, the answer for 88% of them is: “Not so much.” We have been here before. When the iPhone launched in 2007, pundits predicted a mobile-first transformation of everything. When broadband went mass-market, Businessweek heralded a “New Economy.” When the PC colonized every desk, Robert Solow quipped that you could see the computer age everywhere…
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