When asked about their main challenges in adopting AI over the next two years, C-suite leaders cited data issues as their top ...

AI success hinges on high-quality first-party data. Businesses must build "data strength" by connecting all data sources, maximizing data quality, activating it with AI, and measuring ROI. This ...

Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data ...

Introduction: Why Data Quality Is Harder Than Ever Data quality has always been important, but in today’s world of ...

Transportation Pulse Report 2026 reveals AI is reshaping transportation management, with data quality and network ...

The age of AI has amplified the importance of high-quality data which has long been the backbone of effective marketing. However, algorithms are only as good as the information they process. As these ...

AI is only as strong as the data beneath it. Fragmented, inconsistent or stale data will derail even the most advanced models. My previous MarTech article, “Operationalizing generative AI for ...

Breakthrough capability reduces review rates from 100% to as low as 10% while maintaining rigorous SLA compliance and 95%+ quality scores SAN FRANCISCO, CA / ACCESS Newswire / October 14, 2025 / Sama, ...

Key Insight: Strict data lineage is now central to bank generative AI strategies. What's at Stake: Operational, compliance and reputational risks could translate into lawsuits and financial losses.