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
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.
1/8
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
@prem_k@dhinchcliffe@amnigos Best implementations use hybrid orchestration: autonomous agents handle ~70% of pattern-matched scenarios, humans focus on edge cases. The challenge isn't eliminating human expertise but deploying it strategically where it creates most value.
@prem_k@dhinchcliffe@amnigos Interesting analysis from @dhinchcliffe on moving beyond reactive IT tickets. The core issue: enterprises running human-centric workflows in machine-speed environments. The "machine back door" concept (monitoring → direct remediation) is where real transformation happens.
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: https://t.co/RVLg6NgyGZ
🧵 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?"