It already does. There are many complex tasks which can't even be performed by humans. (e.g. time-series forecasting). The relationships between variables is in a lot of cases so complex that humans simply can't find them on their own. But, we can use ML as a black-box approach to perform these tasks.

Where ML completely blows humans out of the water is when it has some kind of continuous learning scheme. Well known examples are GANs and active learning. Another major technique right now is to use reinforcement learning schemes to improve pre-trained models. By creating another model that gives a preference between two outcomes (original model and finetuned model), a reward can be computed to further improve the model. This is why ChatGPT is so good. Definitely look up Reinforcement Learning from Human Feedback to learn more about this.