Solow Paradox: AI's productivity puzzle can be cracked

AI adoption must improve decisions and not end up automating suboptimal processes

- DEEP MUKHERJEE

In 1987, having monitored the computer usage boom for over a decade, Nobel Laureate Robert Solow commented, "You can see the computer age everywhere but in the productivity statistics." This phenomenon of extensive use of advanced technology without an expected increase in productivity is called the 'Solow Paradox'. This particular paradox was resolved in the 1990s, led by industries like technology, banking and retail showing productivity gains thanks to their adoption of information technology (IT), supported by process redesigns and re-imagined product and service offerings.

Today, the adoption of artificial intelligence (AI) may be suffering from its own version of the Solow Paradox. BCG's AI Radar (January 2025), which surveyed 1,800 plus C-suite global executives, found that only 25% see value gains from AI. What may be amiss? Let's consider the case of banking, an industry with large investments in data, AI and technology, to grasp why some banks vouch for AI benefits while others do not.

Whether an organization captures value from AI tends to depend on four interconnected factors. When these factors form a mutually reinforcing virtuous cycle, it offers the organization market dominance, higher margins and strategic moats.

Focus on decision quality: Real-time AI-driven predictions, run on terabytes of data, do not improve decision-making on their own. This is a function of decision-making process discipline; AI only plays a supportive role. A high-quality decision is one whose post-facto assessment shows that a better decision could not have been taken, given the available information and trade-offs.