Diarmuid Curran

Delve into the critical aspects of risk management for AI models and agents in analytics and AI. Bring your questions and learn how to identify potential risks, triage and prioritize them, and implement effective mitigation strategies to safeguard your organization’s digital assets to be able to deliver AI projects.

This session discusses whether AI will replace business intelligence (BI) or simply transform it. As BI interfaces become gateways to AI analytics, trust and precision are crucial — users won’t tolerate AI errors. Join this session to explore if AI will deepen insights and automate action, or will BI adapt and survive in a changing landscape.

Analytics has always been "ground zero" for citizen developers and the low-code/no-code movement. However, the shift toward generative AI and the avalanche of analytics content will overwhelm current analytics operating models, which are already struggling to scale delivery.

Analytics and business intelligence (ABI) platforms are increasingly integrating AI agents to transform how data is analyzed and insights are delivered. Data and analytics leaders need to proactively understand these shifts to maximize AI's business impact and ensure organizational readiness. Join this session to learn more.

Analytics has always been "ground zero" for citizen developers and the low-code/no-code movement. However, the shift toward generative AI and the avalanche of analytics content will overwhelm current analytics operating models, which are already struggling to scale delivery.

The AI tech sandwich is a popular way to sketch out how you can plan to allocate resources for AI within your organization. Learn how to mix your spending and skill ambitions among bought, embedded and built AI by using the order card and menu board.