Risk-proofing the AI supply chain: Building trust and integrity in an automated world
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Don’t let poor data integrity derail your AI ambitions. Join our expert panel to learn how to build a documented, high-quality data supply chain that mitigates risk and ensures your automated systems are built on a foundation of trust.
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As the rush to adopt AI accelerates, many organisations are discovering a hard truth: your AI is only as reliable as the data feeding it. Without a foundation of high-quality data integrity, even the most ambitious AI projects risk escalating costs and ultimate failure.
To move from hype to actual business value, you need more than just sophisticated algorithms—you need a documented, trustworthy data supply chain. Watch this session to discover how to vet your data sources, manage the risks of "data poisoning," and create a comprehensive map of your information landscape to ensure your automated future remains secure and compliant.
What you will learn:
- Building a trustworthy supply chain: how to identify, vet, and document both internal and external data sources to ensure reliability.
- Mapping your data: practical methods for creating a visual "map" of your data supply chain to improve oversight and governance.
- Navigating security threats: strategies to protect against emerging risks like data poisoning and the complexities of data localisation.
- Ensuring integrity: why rigorous data quality is the essential safeguard against project failure and unforeseen costs in AI implementation.
Speakers:
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