Published: 17 October 2022
Drastic disruptions in increasingly unpredictable environments have significant impacts on organizations. For many of them, these changes demand resilience-by-design and adaptive-by-definition. IT leaders need to build adaptive AI systems that can learn and change their behaviors in context.
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The value of operationalized AI lies in the ability to rapidly develop, deploy, adapt and maintain AI models across different environments in the enterprise. Given the engineering complexity and demand for faster time to market, it is critical to develop AI engineering pipelines that are less rigid or build AI models that can self-adapt in production.
Automated, yet resilient, adaptable systems will require composable D&A and AI architecturesthat leverage software engineering to (re)configure or (re)assemble modular, decision intelligence solutions. These compositions can also autonomously self-(re)configure in response to changing circumstances and needs.
Decision making is a core capability for any organization,
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