Archive · 2 Sep 2025
AI Productivity Puzzle: Why Some Banks See Value, Others Don't
Imagine computers are super-smart helpers, but sometimes they don't make us much more productive.
This is called the Solow Paradox, and it's happening with AI too.
Banks, for example, are using AI, but some aren't seeing big improvements.
The key is how you use the AI.
If you make good decisions, take big risks in areas where you can solve significant problems, automate smart processes, and use good-quality data, then AI can be very helpful.
Otherwise, it might not do much.
It's like a lightbulb: you have to figure out how to use it, not just have it.
The Solow Paradox describes a disconnect between technology use and productivity gains.
AI adoption is experiencing a modern form of the Solow Paradox.
Value from AI depends on decision quality, investment in AI, and good data practices.
Automating processes must be optimal to prevent faster bad decisions.
Businesses must adapt their core model to thrive in the AI era.
- Who
- Businesses adopting Artificial Intelligence.
- What
- Factors influencing the success of AI adoption.
- When
- The Solow Paradox is examined in the context of AI's adoption.
- Where
- Focus is on the banking industry.
- Why
- To understand why some businesses benefit from AI while others do not.
- BCG Survey Finding
- Only 25% of C-suite executives see value gains from AI.
- AI Implementation Focus
- Banks investing in data, AI, and technology are examined.
- Key Factors for AI Value
- Decision quality, AI bets, Automation, Data quality
- AI Benefit
- AI helps predict real-time outcomes by using terabytes of data