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Why 95% of Enterprise AI Projects Fail to Deliver ROI: A Data Analysis

Recently, enterprise AI projects are delivering little measurable ROI, as 95% of companies report no bottom-line impact and a Capital One survey found 73% cite data quality as a key barrier.
Fragmented records and missing entity resolution mean corporate databases capture about 20% of critical information, while 80% remains in unstructured data, creating entity resolution challenges like `Acme Corp` variants.
Zillow's 2021 iBuying case lost $500 million and cut 25% workforce, while a mid-sized B2B technology services company faced AI lead-scoring errors recently.
Executives making build-or-pause decisions must consider rebuilding data infrastructure, which takes six months, as 80% of sales teams adopted relaunch efforts in that time.
As agentic AI spreads, enterprises face a build-versus-buy dilemma while ZoomInfo analysis shows firms with advanced business intelligence platforms registered five times revenue growth, 89% higher profits, and 2.5 times valuations.

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The Billings Gazette

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Why 95% of enterprise AI projects fail to deliver ROI: A data analysis

ZoomInfo reports that 95% of enterprise AI projects fail to deliver ROI due to inadequate data infrastructure. Successful implementations focus on specific problems, integrate into workflows, learn from feedback, and leverage real-time data.

2 days ago·Billings, United States

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journaldunet.com

Roi of Ai: Data Quality as a Decisive Factor

The success of AI depends above all on the quality and governance of data, much more than on algorithms. Without a solid data base, ROI collapses and risks explode.

2 days ago

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