Whitepaper
Leaders are under mounting pressure to implement AI that drives business results. How can they ensure their data is ready to fuel AI models that succeed?
Read this white paper to learn:
Why AI-ready, quality data is critical to AI initiatives
How to create a roadmap for AI strategy (and common pitfalls to avoid)
Best practices for aligning people, process, and technology in support of AI projects
This strategy guide is designed for data management experts who want to learn how a data intelligence platform can help them prepare their data AI, alongside their people and processes, to lead AI initiatives that drive results.
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As organizations invest in AI, effective governance is crucial to maintain safety and compliance. But did you know it's also critical for creating a consistent framework for innovation? Interac, a leader in digital payments, has partnered with Alation to build a robust AI governance framework. Join Mohit Sirpal and Shubneet Bharwani from Interac as they share expert insights on creating a trusted data environment for AI. Learn how Interac leverages data intelligence to enable self-service, transparency, and traceability in their AI processes, ensuring they are prepared for future AI initiatives.
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In today’s rapidly evolving digital landscape, effective data governance is critical for organizations striving to manage diverse and numerous data types. Ensuring the trustworthiness of AI/ML models requires robust governance of both inputs and outputs.
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As AI becomes increasingly integral to business operations, effective governance is essential to ensure innovation remains safe, auditable, and compliant. According to IDC research, the two top concerns for organizations investing in generative AI solutions are: the lack of GenAI skills or expertise within the organization and the accuracy of AI-generated outcomes. Building AI literacy and leveraging accurate, trusted data are crucial for driving successful AI initiatives.