Prepare your data architecture for the demands of generative AI
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5 best practices for making your organization's data AI-ready
By: Informatica
Type: White Paper
AI readiness requires strategic data management for relevant, responsible, and robust AI outcomes. This white paper explores key challenges data leaders face with GenAI initiatives:
• Data management: quality control, system integration, and scaling AI-ready data
• Governance and compliance: data classification, security protocols, and regulatory awareness
• Adoption strategies: workforce training, cultural resistance, and ROI expectations
Successful organizations see AI readiness as an ongoing investment needing:
• Technical expertise and management skills
• Data governance frameworks
• Clear business value metrics
• Strategic use case selection
Read this white paper for best practices.
These are also closely related to: "Prepare your data architecture for the demands of generative AI"
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Navigating data management for compliant AI in a changing world
By: Informatica
Type: White Paper
As AI adoption accelerates, responsible governance and compliance become crucial. This white paper explores AI legislation, including the EU AI Act, U.S. Executive Order, and Singapore's framework.
Organizations face challenges in AI governance, such as data integration, quality, bias mitigation, and privacy protection. The paper outlines principles of responsible AI—transparency, fairness, accountability, and security—and shows how Informatica's Intelligent Data Management Cloud can help:
• Streamline governance and compliance
• Empower users with AI tools
• Enhance data quality and reduce costs
• Automate workflows for efficiencyRead this white paper to learn about responsible AI governance.
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Data strategy guidelines for AI: A practical guide for IT leaders.
By: Informatica
Type: Infographic
IT Leaders' Checklist: Data Requirements for Predictive AI and GenAIAs organizations adopt AI technologies, IT leaders must grasp the data requirements for implementing predictive and generative AI solutions. This infographic offers essential guidance for IT decision-makers in these evolving technologies.
A comprehensive checklist helps IT leaders:
- Evaluate data infrastructure readiness
- Identify data quality and governance needs
- Understand data requirements for predictive vs. generative AI
- Plan scalable data architecture for AI initiatives
- Address data privacy and security considerations
Review this infographic to ensure your organization has the data foundation for AI implementation.
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Want a modern integration service that works?
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See how cloud data integration can deliver a 335% average ROI
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Key vendors in Gartner's data and analytics governance report
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The 2025 Gartner Magic Quadrant for Augmented Data Quality Solutions evaluates 12 vendors offering AI-powered tools to enhance data quality via automation. With 70% of organizations expected to adopt these solutions by 2027 for AI support, these tools are vital for AI-ready data. Review the Magic Quadrant to find the best vendor for your needs.
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