Published 1 month ago • Updated 1 month ago

75% of Businesses Will Invest in AI This Year - But Data Quality Issues Threaten Their Ambitions

Summary by AiThority

51% of companies will invest over 10% of their technology budget on AI initiatives. Nearly all (98%) have suffered with AI-related data quality issues. While 74% of businesses plan to invest in AI initiatives this year, less than half (46%) are confident in their data quality. This is according to a survey of 1,050 senior business leaders across the US, UK, and France by Semarchy, a global leader in master data management (MDM) and data integrat…

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IT PRO

Data quality worries are holding back AI adoption among manufacturers, despite optimism over its growth potential

Less than half of manufacturing leaders describe their data as "excellent" while two-thirds question how they're using data for AI

1 month ago

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TecHR

Pluralsight Research Finds More Than Half of Organizations Don’t Have Comprehensive AI Strategies

The findings also uncovered an AI skills gap that is preventing organizations from implementing AI effectively Pluralsight, the technology workforce development company, released survey data from 600 technology decision-makers about the state of their AI strategies, investments and skills. This data was used to create a benchmark for Pluralsight’s AI Readiness Index, a tool that allows companies to gauge where their AI strategies stack up agains…

1 month ago

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itbrief.co.uk

+4 Reposted by 4 other sources

Companies eager to adopt AI face data quality challenges

New research from Semarchy reveals a stark contrast between businesses' ambition to invest in AI and their concerns about data quality, with only 46% trusting their data.

1 month ago

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Digital Transformation & Technology Consulting Services | Gleecus

The Importance of Data Quality in a Data

Data quality is a serious business for enterprises transforming into data-driven organizations. To standardize adherence to data quality by market research firms the Global Data Quality Initiative (GDQ) has launched a pledge. Enterprises planning to exploit the full potential of AI require to be extra cautious about their data quality. Poor data will give false and incomplete results even if the models are perfect. Let us evaluate the importance…

1 month ago

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IT-Online

How data and analytics leaders can scale AI

Through 2025, poor data quality will persist as one of the most frequently mentioned challenges prohibiting advanced analytics such as artificial intelligence (AI) deployment, according to Gartner. Because of this, data and analytics (D&A) leaders must focus on three interdependent journeys to advance enterprises’ AI initiatives. These journeys include business outcomes, D&A capabilities and behavioral change. “AI continues to drive enterprise p…

1 month ago

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AiThority