Your business has two options to solve this siloed, unusable data problem: one, build the data infrastructure internally to support this, which is a resource-heavy commitment. Or two, choose a technology partner who offers a plug-and-play solution for this. POWER-UP TIP: The trace data from your decisioning, when fed into your AI models, will drive performance optimization. Whichever data path you choose make sure you have the power to harness your decisioning data! Manageable AI Data scientists could devote an entire eBook to this section alone, but we’ll keep this a high-level look at why businesses fail to deploy AI projects and how to overcome this. The right tool (model) for the job : If you’ve ever investigated AI platforms, you’ll know that models aren’t in short supply, in fact there’s an overabundance of models. Why is this a problem? Because it requires your team to know which one to use when, adding in additional time and resource needs. It’s like having to guess which weapon is effective against threats, instead of the game telling you which tool to choose. It’s like trying to have your hero cross a ravine using a spade instead of a whip. It’ll be game over at record speed. There are solutions available that will automate this process for you. They use automatic testing to select
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