Trusted AI 101: Tips for Getting Your Data AI-Ready

In a rapidly evolving competitive landscape, businesses are keen to leverage AI to enhance productivity, offer personalized services, and innovate for a competitive edge. However, the rush to adopt AI without proper preparation has led to notable failures, highlighting the necessity of AI powered by trusted data.

Trusted data requires data integrity, characterized by maximum accuracy, consistency, and context, which is essential for AI’s effectiveness. Many organizations face challenges in achieving data integrity, including integrating data swiftly, ensuring its responsible use, maintaining its quality, enriching it for deeper context, and securing privacy.

The eBook presents a sobering reality: according to a 2023 Gartner IT Symposium Research Super Focus Group, only 4% of organizations believe their data is AI-ready. It emphasizes the limitless benefits of AI applications trained on trusted, AI-ready data and explores six AI use cases that succeed with data integrity:

• AI recommendations
• AI-powered workflows
• Machine learning applications
• Foundation Model training
• Chatbots
• AI assistants using retrieval augmented generation (RAG)

Furthermore, it addresses top AI challenges solvable with data integrity, including overcoming incomplete data, compliance struggles, and lack of context for AI outputs. The eBook outlines three key data integrity considerations for trusted AI, emphasizing the collaboration between Precisely and Amazon Web Services (AWS) to achieve accurate, consistent, and contextualized data for reliable AI outcomes.

The eBook underscores the importance of prioritizing data integrity for high-performing, reliable AI initiatives that produce quality outputs. It encourages organizations to embark on the data integrity journey to future-proof their AI applications and unlock their full potential.