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Technical Readiness for AI: What Your Organization Needs to Know

Part 3 in a series on the journey to AI success.


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Is your organization technically prepared to launch an AI initiative? As we established earlier in this series, answering that question begins well before you begin talking about tools and systems — first by pinpointing the problem you’re trying to solve (Part 1) and next by assessing your business readiness to address that problem with AI (Part 2). Only then is it time to talk about being prepared from a technical standpoint.

“Technical readiness is all about getting to the solution for a business problem in the fastest, most optimized manner possible,” says Beena Ammanath, executive director of the global Deloitte AI Institute. Reaching that end goal requires ensuring that your ecosystem, data, infrastructure, processes, and people are all truly up to the task.

This Strategy Guide is filled with expert insights designed to help you gauge your organization’s technical readiness for AI. You’ll also receive a quick introduction to the all-important ModelOps approach, a framework of five key technical considerations for adopting AI, and a handy checklist covering the main issues that should be addressed before embarking on any AI project.

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