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CIOs’ lack of success metrics dooms many AI projects

CIO

Many organizations have launched dozens of AI proof-of-concept projects only to see a huge percentage fail, in part because CIOs don’t know whether the POCs are meeting key metrics, according to research firm IDC. The potential cost can be huge, with some POCs costing millions of dollars, Saroff says.

Metrics 187
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When is data too clean to be useful for enterprise AI?

CIO

Once the province of the data warehouse team, data management has increasingly become a C-suite priority, with data quality seen as key for both customer experience and business performance. But along with siloed data and compliance concerns , poor data quality is holding back enterprise AI projects.

Data 211
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What to expect from AI in the enterprise in 2025

CIO

This year saw the initial hype and excitement over AI settle down with more realistic expectations taking hold. This is particularly true with enterprise deployments as the capabilities of existing models, coupled with the complexities of many business workflows, led to slower progress than many expected.

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Valence raises $25M to track team performance with continuous reviews

TechCrunch

Valence lets managers track team performance by certain metrics and, if they deem it necessary, intervene with “guided conversations.” Valence , a growing teamwork platform, today announced that it raised $25 million in a Series A round led by Insight Partners. What constitutes a “teamwork platform,” exactly?

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Interpreting predictive models with Skater: Unboxing model opacity

O'Reilly Media - Data

There is also a trade off in balancing a model’s interpretability and its performance. A deep dive into model interpretation as a theoretical concept and a high-level overview of Skater. There is often a need to verify the reasoning of such ML systems to hold algorithms accountable for the decisions predicted.

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Low code/no code tools reap IT benefits—with caveats

CIO

Low-code/no-code visual programming tools promise to radically simplify and speed up application development by allowing business users to create new applications using drag and drop interfaces, reducing the workload on hard-to-find professional developers. So there’s a lot in the plus column, but there are reasons to be cautious, too.

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AI’s Future: Not Always Bigger

O'Reilly Media - Ideas

The surprise wasnt so much that DeepSeek managed to build a good modelalthough, at least in the United States, many technologists havent taken seriously the abilities of Chinas technology sectorbut the estimate that the training cost for R1 was only about $5 million. Thats roughly 1/10th what it cost to train OpenAIs most recent models.