Strategies and practices for responsible AI — TDWI Research

Enterprises are increasingly relying on artificial intelligence (AI) to gain a competitive edge. AI technologies are being deployed across a myriad of applications including churn prediction, disease detection, predictive maintenance, network optimization, and fraud prevention. Generative AI has not only increased the desire to adopt AI in various organizations; it has also introduced new challenges in responsible AI implementation as these entities transition from experimentation to operationalization. The increasing reliance on AI makes it more important than ever that AI is used responsibly, to ensure business outcomes and minimize risk.

With increasing regulation such as the recent EU AI Act, responsible AI is critically important not only in highly regulated industries but across all sectors. The responsible deployment of AI involves a comprehensive approach to mitigating business, legal, and ethical risks across people, processes, and technology—managing model biases, ensuring explainability, and protecting privacy.

Join TDWI, Domino, and NVIDIA to explore strategies and practices that organizations can adopt to navigate the complexities of responsible AI. Topics include:

• The business case for responsible AI
• Key pillars of responsible AI
• Strategies for getting started putting responsible AI strategy into practice
• Best practices for mitigating business, legal, and ethical risks
• Critical up-to-date developments on the EU AI Act