Multi-cloud used to be a dirty word — something that happened to you through mergers, shadow IT, or teams gone rogue with corporate cards. But the walls came down, the standards converged, and best-of-breed finally seemed within reach. Then AI arrived with a whole new layer of complexity.

Or did it?

In this episode, we explore how agentic AI might actually solve the thing that made multi-cloud hard in the first place. Three cloud experts—Jack French from World Wide Technology, Alex Kozaris from Softchoice's AWS practice, and Ron Espinosa from Softchoice's Google Cloud team—break down what's changed, what matters for mid-market teams, and why the "gold record" might finally be possible.

Key Takeaways:

• Why 90% of organizations are already multi-cloud (whether they planned to be or not)

• How abstraction layers and platform engineering help smaller teams manage complexity

• What each major cloud does best: AWS for builders, Microsoft for productivity, Google for data/AI

• The compliance curve ball forcing some organizations into multi-cloud for AI governance

• How agentic AI creates "connective tissue" that makes integration problems irrelevant

Featuring:

• Jack French, Senior Director of Cloud, World Wide Technology

• Alex Kozaris, Public Cloud Leader for AWS, Softchoice

• Ron Espinosa, Google Cloud Category Director, Softchoice

The Catalyst by Softchoice is the podcast dedicated to exploring the intersection of humans and technology.