Every organization wants to move faster with AI. But when an AI application, business team, or data scientist needs new data, the same bottlenecks remain — engineers must interpret the request, locate the sources, build the pipeline, and maintain governance. That process can take weeks. AI operates in seconds.

Agentic data integration could fundamentally change that — but where does it actually work today, and what does it take to trust it in production? In this Techstrong Learning Event, IBM and Futurum Group will explore whether AI agents can safely turn business requests into working data pipelines, where they can reduce engineering work without compromising governance, and how organizations should move from experimentation to production.

Justin Yan will bring a customer-inspired scenario to life through a demonstration — covering ETL pipeline construction, large-scale pipeline operations, and automated governance enforcement using AI agents. Participants are encouraged to question the approach and compare it against their own data challenges. This is not a conversation about doing the same work a little faster. It is a conversation about how the way enterprises deliver data is about to fundamentally change.

Key Takeaways:

1. The AI bottleneck is your data bottleneck — Why incremental pipeline optimization won't close the gap between how fast AI operates and how slowly enterprises deliver data today.

2. Where agents are production-ready now — A grounded look at real customer use cases: automated pipeline construction, pipeline operations and optimization, and AI-enforced governance standards.

3. What responsible adoption actually looks like — The governance and observability considerations that separate a compelling demo from something you can trust at enterprise scale.