Your legacy applications and infrastructure don't have to be a liability. In this session, discover how leading enterprises are converting tech debt into modern cloud advantages that unlock AI capabilities, cut costs, and accelerate innovation. The path to AI starts with migration and modernization. We'll walk through the complete transformation journey: infrastructure, applications, data, and AI-ready business outcomes. You'll see how new agentic AI automation is making migration and modernization faster, simpler, and more cost-effective. We'll explore proven pathways for your most critical workloads (Microsoft, VMware, SAP, and mainframe), backed by 20 years of AWS expertise.
What this session is about
Playbook
Editorial commentary · what to actually do about this on Monday
The concept
Migration + modernization unlocks AI capabilities that legacy infrastructure can't run. The path to AI starts with migration.
Why it matters
AI workloads need scale and architectural primitives that mainframes and on-prem VMware don't provide. Migrating *is* the AI strategy in many cases.
The hard parts
Mainframe migration is risk-laden. "Move-and-improve" is hype; lift-and-shift just becomes technical debt with new bills.
Playbook moves
(1) Score workloads on AI-readiness (data accessibility, API surface, ability to scale horizontally). (2) Migrate high-AI-leverage workloads first, even if they're not the cheapest. (3) Build the AI use case for each workload before migrating it — that frames the modernisation choices.
The surprise
The best migration ROI argument to the board isn't cost savings — it's *capability unlock*. Frame the budget ask accordingly: "we cannot do X, Y, Z on the current stack." Cost-only arguments lose to "wait six months and revisit." Capability arguments don't.
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Independent editorial perspective — not an official AWS or speaker statement. Designed for executives evaluating what to brief their teams on next.
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