Enterprise adoption of AI
A few points about Enterprise adoption of AI... To discuss.
These are excerpts from this post from gai insights at:
The Real Story: Convergence
These aren't isolated trends. They're converging:
- Edge devices running focused, low-cost models
- Agents orchestrating end-to-end workflows
- Distributed architectures replacing centralized, human-centric ones
This is a new operating model: distributed, agentic, and economically scalable.
The executive question isn't "Should we experiment with AI?" It's: Are we redesigning our operations for agentic, edge-first architectures—or optimizing yesterday's workflows?
Now extend that logic: procurement agents negotiating contracts, service agents resolving the majority of tickets, finance agents running close processes. Not pilots. Production systems. Companies that redesign workflows around agents in the next 12 months will build compounding cost and speed advantages. This is capability-building, not experimentation.
The firms that move now—re-architecting workflows, pushing intelligence outward, and adopting cost-optimized models—will build advantages that laggards won't catch. This window is measured in months, not years.
many organizations still treat GenAI as a pure tech purchase, but value comes from redesigning work, fixing "workflow debt," and building AI-ready operating habits, not just running upskilling programs
David
617-331-7852
David@DavidCutler.net
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