Most financial institutions are using AI to do existing things faster. The ones that will matter are using it to become something different. The distinction is not technological. It is strategic, and most boards have not yet been asked the right question.
Financial institutions have made bold declarations of purpose while building cost structures that cannot support them. Closing that gap is not a values question. It is an economics question, and the answer requires a fundamental rethink of where margin actually lives.
The macro forces reshaping financial services: regulation, AI, and the cost of delayed transformation. What boards and executives need to be thinking about now.
For decades, knowing things was a competitive advantage. AI has made knowledge a commodity. The only thing that cannot be automated is the decision about what to do with it, and most organisations are still hiring for the wrong skill entirely.
If you use AI to skip the drudgery, you never internalise the first principles. How do you become a senior expert if you never did the junior work? This is the single biggest structural risk to the next generation's career, and almost nobody is naming it.
The risk of believing a machine because it sounds confident. AI produces fluent, plausible, and wrong answers at scale. The leaders who survive this era will be the ones who can look at a perfect, instant, synthetic answer and say: that is wrong.
A good perspective piece should do more than signal taste. It should change how the reader sees the problem. That is the standard I aim for here, and in client work. New pieces published when they are ready, not on a schedule.