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.

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.

Organizations often struggle to collaborate across analytic silos. By treating metrics as data products as part of a franchise delivery model, data leaders can improve the quality and consistency of analytic content across the organization.

Data and analytics leaders can use the concept of a “franchise” to communicate the optimal organizational model, data architecture and governance framework that large enterprises require to scale self-service analytics programs.

With new pressures coming from AI, CDAOs must be agile in implementing and enabling business innovation. But, with quick adaptation, inevitably comes stress on traditional D&A delivery processes and practices. Join this interactive session to lean how to: clarify strategies to support business innovation, design adaptable and scalable delivery models and collaborate with business units to ensure value of D&A capabilities and services.

D&A value is not possible without data storytelling that offers a better way to engage communication findings than just BI reporting or data science notebooks. Join this session to know about the fundamentals of data storytelling and how to fill the gap between data science speakers and decision makers. It further discusses how to tell the best data storytelling and how to upscale data storytelling for future in landscape of GenAI.

Data and analytics leaders can use the concept of a “franchise” as a metaphor to communicate the optimal organizational model, data architecture and governance framework that large enterprises require to scale self-service analytics programs.

Analytics and Business Intelligence (ABI) Platforms are being transformed by AI. Data insights are more likely to be discovered by machine learning. Natural language generation will turn dashboards into data stories. Natural language query will make data more accessible. This session will show how ABI Platform vendors are incorporating AI and how analytic leaders can manage the additional cost and risk these trends will bring.