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Seventy percent of employees are already using AI at work without adequate governance in place. Not in some distant future state. Right now, across your organization. The question finance leaders are grappling with isn't whether AI is being used. It's whether anyone knows where, by whom, and with what consequences for the decisions that matter most. That's the operational trust gap. And closing it is quickly becoming one of the defining leadership challenges in finance. Here'

People often say money magnifies character. I think AI does the same thing. In the hands of a highly capable employee, AI can be transformative. Not just making them faster, but making them dramatically more effective. Better analysis. Better communication. Better execution. Better decisions. AI can easily 10x the output of someone who already has strong judgment and discipline. But the opposite is also true. AI in the hands of a poor performer rarely creates a superstar. It

During the pandemic, a fitness company had the data. The machine learning models clearly signaled that demand was cooling. Leadership saw the output and decided to override it and build more. The world reopened, demand collapsed, and the company spent the next year in damage control mode with big financial consequences. You may be familiar with that story, and there are also plenty of examples where AI was wrong and companies paid the price. But here's the part that gets

Most companies have budgeted for AI. They’ve budgeted for software licenses, pilots, consultants, training, automation, and data infrastructure. They’re making room for AI because they know it’s going to reshape how work gets done. What far fewer companies have budgeted for is AI failure. According to recent data from EY, 64% of enterprise organizations reported at least one AI-related incident that cost more than $1 million, with the average financial impact estimated at $4.