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Carlos Mattos's avatar

The idea that “estimates reflect expectations, but only the final result is proof” can be applied to various sectors beyond the investment market.

Companies that adopt artificial intelligence solutions face a gap between what is planned and what actually happens in practice. Launching a pilot project is just the beginning. Actual implementation occurs when the project continues to operate in production after twelve months, having passed the company’s security and governance tests.

In the financial sector, this process does not always yield positive results. The problem isn’t the technology—we know that projects work well during the testing phase. The difficulty arises when the system needs to move to the production environment, where it is put to the test under different and more rigorous rules, and this impacts the costs projected at the start of the project.

The situation is more complex than it seems. It’s not just about whether investors can turn the company’s innovation into actual profit; what’s most important is verifying whether the customer who purchased this solution has already been able to derive value from it in practice.

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