Anatomy of an enterprise-scale AI strategy
Looking to move beyond point solutions and proofs of concept? Here’s what it takes to develop to a holistic AI strategy honed for business results.
By Maria Korolov in CIO
When it comes to AI, companies typically test the waters proof of concepts or small-scale use cases, taking advantage of vendor offerings, such as new features in their existing SaaS platforms.
If things go well, they pursue another project, then another — and soon they’re relying on a sprawl of incompatible systems, competing data lakes, problems with cost overruns, duplication of efforts, and an inability to scale, not to mention privacy, compliance or ethics problems.
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At some point, the benefits of AI become obvious enough, and the pain of continuing on their present path so acute, that companies step back to develop a cohesive strategy for an enterprise-wide AI-powered transformation.
"The tendency to get overwhelmed in individual technologies is not only drowning organizations in technical debt but discouraging them because they don't see a path forward to sustainable and scalable AI," said Traci Gusher, partner in data, analytics and artificial intelligence practice at KPMG.
Here’s a look at how organizations can ensure the shift from pilot projects to full-scale AI fluency goes right. .... "
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