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Once the data has been collected and organized, companies can build and scale AI models across their business to glean insights from their data and engage with AI to transform their business.
However, hastiness can create issues with tools, people, and processes. To build AI models you can scale across the organization, you need capabilities across the full AI lifecycle: Build, Run, and Manage.

• Build – The build phase is where you create and train models, and it’s critical to have the right algorithms to solve your business needs.
• Run – Putting your model into production means it’s making decisions and must be retrained as needed
• Manage – Companies need tools that can monitor AI models, detect and correct bias and a drift or degradation in model accuracy (because production data differs from training data), and explain AI outcomes to achieve compliance and minimize risk.