About

Every data leader is facing the same reality: AI is fundamentally changing how data platforms, pipelines and products are built. Teams that successfully embrace AI-assisted engineering are accelerating delivery at unprecedented rates, while others risk falling behind. Yet speed alone creates a new challenge. As more engineers adopt coding agents, copilots and automation tools, organisations are discovering that productivity without governance can quickly lead to inconsistency, technical debt and operational risk.

In this session, Snap Analytics will explore the next evolution of the AI-Augmented Data Team. Drawing on real-world delivery experience, we will show how leading organisations are integrating AI across the data delivery lifecycle, from requirements and modelling through to engineering, testing and deployment. We will also examine why governance, standardisation and agent orchestration are becoming essential foundations for enterprise-scale adoption.

Attendees will leave with a practical blueprint for accelerating delivery, improving engineering quality and building a governed approach to AI-powered data platform development.

Takeaways: 

• The New Reality of Data Delivery: Understand how leading technology organisations are already using AI to transform software and data engineering, and what this means for the future role of data teams.
• The AI-Augmented Delivery Lifecycle: Learn how AI can be integrated across requirements gathering, modelling, engineering, testing and deployment to dramatically increase delivery throughput without increasing team size.
• From AI Productivity to AI Governance: Discover why enterprise teams need more than coding agents, and how governance, quality controls and standardised operating models prevent AI-driven technical debt and inconsistency.
• A Blueprint for Enterprise-Scale Adoption: Leave with a practical framework for assessing your organisation’s AI delivery maturity and implementing a governed, scalable approach to AI-powered engineering.