Accelerating AI and ML at Enterprise Scale

Released: Aug 03, 2023 |

Length: 10 pages |

Language: English |

Resource: Whitepaper

What’s the cost of the AI/ML scalability dilemma?

The top reasons enterprise analytics projects fail include:

• Inefficient data preparation
• Lack of flexibility to use preferred tools/models
• Difficulty scoring data live at scale

Recent estimates suggested between $9.5 and $15.4 trillion in value could be unlocked with advanced analytics. Artificialintelligence (AI) and machine learning (ML) were highlighted as
crucial drivers of that value.

But despite increased investments in analytics solutions, AI, and ML, companies today are still struggling to capture real value from their analytics projects. Gartner predicts only 20% of analytic insights will deliver business outcomes.

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