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In 1907, America was on the brink of financial ruin. It all started when Otto Heinze hatched a plan to corner the copper market. It failed spectacularlycausing the collapse of his brokerage house.

The ripple effect was devastating: over the next seven days, bank panic swept across the country, with New York City becoming nearly insolvent. James Pierpont Morgan quickly realized what was happening.

He responded by locking the bank presidents in his office library until they found a solution. His actions were narrowly avoided a more widespread crisis.

The episode – which would eventually be known as the Panic of 1907 – highlighted the need for regulation and ultimately led to the creation of the Federal Reserve. Then, as is the case today, many resented the introduction of additional red tape, feeling that it caused undue friction and consternation.

But regulation is a good thing. Somewhat counterintuitively, well-designed regulations can increase innovation, productivity and growth. While the imposition of regulations has often been seen as a drag on business efficiency, it turns out that their compliance could be the driving force behind a quiet revolution in technology and innovation, particularly in the field of artificial intelligence.

Think about banking compliance teams. They have long been at the forefront of innovation. Long before ChatGPT became a household name, banks were already deploying natural language processing at scale to combat insider trading, money laundering, and other financial crimes.

Banks did this in part because of the regulations, not in spite of them. Every financial institution is required by regulation to safeguard its commercial communications, whether from employee to employee or from employee to customer. These regulations have not only made markets safer; they also laid the foundation for some of the most advanced technology solutions used today, including enterprise-grade AI.

What can we learn from this journey? The AI ​​is powerful and works very well. Modern compliance teams are tasked with sifting through a haystack of corporate communications to find a needle of risk that may indicate financial crime.

Without AI, this is almost impossible. Using AI, businesses can accurately assess risk and business intelligence from their data. These tools are applicable well beyond financial services and can generate new revenue streams as well as risk reduction.

Through trial, error, and innovation, financial institutions have learned to harness artificial intelligence reliably and responsibly. These are not a flashy demonstration or a parlor trick: these are large-scale production systems.

Other industries should take note: Outside of financial services, most companies have little idea about what’s really going on inside their business. The ability to separate signal from noise can provide real-time insights into the risks they face every day. Beyond that, it can also reveal opportunities, including highlighting ways to improve customer experiences and create better, more productive work environments.

As with any energy source, there is also peril. AI can be biased, poorly trained, and used for purposes that are not in the best interest of the collective good. The combination of power and peril is nothing new: we test and regulate planes, drugs, and power plants. From there, we learned three pillars of responsible innovation.

First, the technology must be resilient and reliable. These systems constitute critical infrastructure and deserve to be treated as such.

Second, AI must be subject to careful risk management. Misjudgments spread quickly. By putting proper processes and testing in place, we gain the joint benefits of scalability and reliability. Beware the hype: these systems are difficult to create but worth using.

Finally, businesses must choose responsible use cases. As with any new technology, compromises will be necessary between stakeholders. AI may be more prone to bias and poor training than other technologies. We don’t need to be afraid, but we need to be smart.

Few technologies inspire a broader mix of fear and excitement than AI. People are rightly worried that their jobs will be eliminated or that they will be stuck in the machine without being able to reach a human.

As such, regulation runs the risk of being politicized. The White House recently outlined its vision for AI surveillance, echoing the European Union’s efforts with its AI law.

In particular, it is reasonable to assume that this is only the beginning. New regulations are coming, and financial services should adopt them. With the infrastructure, talent, opportunities and careful oversight, financial institutions are poised to become leaders in this space.

For the banking industry, AI is quickly becoming an indispensable tool not only for compliance, but also for driving innovation and market leadership. We have no choice but to do things right. However, regulation and innovation are not mutually exclusive. If 1907 is a lesson, it is that chaos breeds bad progress. It’s better to lay a solid foundation now rather than find yourself locked in a library later, looking for a last-minute solution.