Organizations are hard-pressed to fine-tune their greater data science and AI strategy based on their learnings from the turbulence of 2020 and its impacts on the business (and, notably, models in production). They are resolute, focused on untapping new ways to bridge the gap between “business value generation” as a buzzword phrase and actually putting it in practice in a way that is collaborative and sustainable for the long term.
While business value creation will ultimately end up looking different at every organization, at its core, business value comes down to improving business outcomes to make key processes and functions better, faster, or more cost-effective. In The Business Value Guide for AI, we introduce various ways — across six key drivers — that organizations can drive net new and ongoing business value from their AI efforts.
Each driver includes best practices and tips for implementation, helping organizations connect the dots between accelerating their AI maturity and generating value, both of which will pave the way for additional use cases and knowledge sharing to enhance democratization and enterprise-wide adoption. Check out the infographic below for the highlights before diving into the full guidebook!
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