“Staff functions have the authority to slow a project regardless of executive support, and they respond to governance rather than persuasion. Bring them in early with a mandate, and several of them will convert from blockers to enablers.”
Is this the difference between co-creating solutions vs being asked to comply with a directive someone else has designed?
John, yes! The bottleneck is usually the organization and not the tech. Teams can improve their odds by focusing on change management and process redesign.
The 77% invisible work stat is the one that should end every "just buy the tool" conversation - change management, data quality, and process redesign don't show up in the budget, but they decide the outcome. The model was never the bottleneck.
Important to have your data well-structured and ready. We invested in https://melow.ai/ to solve that issue
Pretty insightful read, John!
I also liked the lead image a lot, it caught my eye.
I’m curious what this looks like in practice:
“Staff functions have the authority to slow a project regardless of executive support, and they respond to governance rather than persuasion. Bring them in early with a mandate, and several of them will convert from blockers to enablers.”
Is this the difference between co-creating solutions vs being asked to comply with a directive someone else has designed?
very interesting! it would be good to hear an opinion on this from operators who've actually shipped an AI deployment
John, yes! The bottleneck is usually the organization and not the tech. Teams can improve their odds by focusing on change management and process redesign.
Many enterprise AI projects don’t fail because the technology is weak, but because the organisation can’t absorb the change
The 77% invisible work stat is the one that should end every "just buy the tool" conversation - change management, data quality, and process redesign don't show up in the budget, but they decide the outcome. The model was never the bottleneck.