Elcio Abrahao

Data teams are increasingly using AI tools and agents to accelerate development, documentation, and analysis. While productivity gains are real, they introduce new challenges around governance, security, context, and cognitive load. This panel explores how organisations enable data teams to use AI effectively while maintaining quality, control, and sustainable ways of working.

 Applying AI safely to improve data team productivity

 Managing risk, access, and oversight when using AI tools

 Scaling AI usage across teams without increasing fragility

At Syngenta, data products are being produced, enriched, and consumed by AI agents across the full lifecycle, from data captured in the field to insights delivered in real time. This shift is changing how data is structured, how pipelines are built, and how products are ultimately used. Elcio Abrahao explores how AI-driven workflows are being introduced alongside existing data products, including spec-driven development, agent-enabled pipelines, and real-time applications in agriculture. As this evolves, new challenges are emerging around cost, trust, and variability, particularly where non-deterministic AI outputs replace traditional, rule-based approaches.