Thread: Why your AI pilots aren't scaling (and what actually works)
Most enterprises are stuck in "pilot purgatory"—dozens of AI experiments, but no enterprise impact.
This isn't a technology problem. It's an orchestration problem.
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8/ Bottom line:
ERP winners weren't the ones with the best modules—they orchestrated business processes
Cloud winners weren't the ones who tested workloads—they re-architected systems
AI winners won't have the best models—they'll build the best ecosystems
9/ TL;DR: Previous tech winners (ERP, cloud) succeeded through orchestration, not better tools. AI will be the same.
What are you seeing?
#AI#CIO#CTO#DigitalTransformation
🧵 Observing an interesting pattern: AI isn't just expanding capabilities—it's systematically shifting the logic of obligation in competitive contexts.
Some examples of what I mean by "deontic transformation": 1/8
7/ FOR ORGANIZATIONS:
The question isn't "should we adopt AI?" but "which of our current assumptions about reasonable timelines/verification/quality are about to become competitive liabilities?"
8/ WORKING ON A FRAMEWORK for systematically identifying these shifts before they become obvious.
Early indicators often visible in:
Procurement RFP timelines
Investor due diligence requirements
Professional liability standards
Full analysis: sriravula.substack.com/p/the…
1/7 After implementing AI systems for Fortune 500s and building 60,000 lines of ops automation code in 4 days, here's what actually breaks AI projects (thread) 🧵