Gartner® Report:
A Journey Guide to Deliver AI Success Through AI-Ready Data
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This Gartner guide explains why “AI-ready data” is different from traditional analytics data, and what changes are needed in architecture, governance and skills so AI initiatives actually deliver on their business promises.Click HereLearn why 92% of organizations fail to scale AI, and how to avoid the common pitfalls in data architecture, governance, and operational readiness.Click HereUnderstand the maturity stages of AI-ready data, and what separates organisations that succeed with AI from those that stall.Click Here
Discover how data & analytics leaders can turn AI ambition into real business outcomes by building an AI-ready data practice.
AI projects are moving from experimentation to enterprise scale, but many still stall because the underlying data isn’t ready. This Gartner report explains why “AI-ready data” is different from traditional analytics data, and what changes are needed in architecture, governance and skills so AI initiatives actually deliver on their business promises.
You’ll learn why:
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Organisations without an AI-ready data practice are far more likely to see AI projects miss service levels and be abandoned.
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AI-ready data is not a one-off project, but an ongoing practice aligned to specific AI use cases.
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Boards now rank AI-ready data initiatives as a top investment priority over the next few years.
Explore how Datactics can help you put the principles in this Gartner report into practice, from data quality to AI-ready governance.
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