Unlocking value from data with AI4Data
QuantumBlack, McKinsey’s AI arm, works with organizations to harness AI to fuel innovation, transformation, and sustainable growth. The QuantumBlack, AI by McKinsey, Medium blog highlights how this comes to life in practice, featuring practitioner perspectives and real-world examples across areas such as data science, data engineering, and agentic AI.
One popular topic is the AI4Data solution from QuantumBlack, AI by McKinsey, which improves data quality, unlocks value from unstructured content, and accelerates the creation of reusable data products—an approach that is increasingly important as organizations seek to scale AI using reliable, well-structured data.
AI4Data offerings include the following:
- AI4DQ improves structured data quality by detecting and fixing duplicates, inconsistencies, and missing values, with a novel approach validated by a US patent.
- AI4DQ Unstructured cleans, deduplicates, and organizes unstructured data to improve gen AI performance.
- AI4DX converts unstructured content, such as PDFs and reports, into structured, reusable data assets.
- AI4DP uses gen AI to accelerate the creation of high-quality, reusable data products from raw inputs.
- AI4DD codifies and assesses data sources to improve understanding, visibility, and viability of data for value-add use cases.
- AI4DL develops trusted, scalable data lineage across sectors, solving compliance, integration, and analytics challenges.
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AI4DI leverages an agentic architecture on top of AI4Data assets to rapidly perform tasks serving tech and non-tech users.
To learn more about how AI4Data can help turn data into a competitive advantage, explore the full set of insights on medium.com/quantumblack.
