AI Workflow Integration System.
A human-centered operating model for identifying, piloting, and scaling AI-enabled workflows. Built as a strategic artifact for AI adoption, workflow redesign, governance, and measurement — not as a fabricated client case study.
AI adoption fails when it's treated as a tool rollout.
Most organizations sit between leadership pressure to "use AI" and frontline uncertainty about where it actually fits. The result is scattered pilots, abandoned tools, and no shared model for how human + AI work should change. This framework treats AI adoption as a workforce transformation problem — a behavior, workflow, capability, and operating-model shift — not a license rollout.
Six steps from curiosity to measurable adoption.
Map where work actually happens, where friction lives, and where AI could meaningfully reduce time, error, or cognitive load.
Score workflows against the readiness scorecard — workflow clarity, business value, data sensitivity, governance needs, and more.
Choose where to pilot based on impact, fit, and risk — not based on what's loudest in the room.
Redesign the workflow with AI in the loop, not bolted on. Decide what's automated, what's assisted, and what stays human.
Run a structured pilot with enablement, practice support, and feedback loops. Treat it as behavior change, not a tool rollout.
Stand up guardrails, measurement, and a sustainment model so adoption holds — and so the next workflow can move through faster.
Ten dimensions for scoring a workflow before you pilot.
The scorecard makes prioritization explicit. It surfaces which workflows are ready for AI, which need redesign first, and which are too sensitive or too unstable to pilot yet.
Design the human + AI workflow, not the prompt.
Workflow redesign decides what's automated, what's AI-assisted, what's reviewed, and what stays fully human — then sequences the steps, handoffs, and decisions accordingly. The work is human-centered first: protect judgment where it matters, remove friction where it doesn't, and let prompts and tools follow the redesigned flow rather than drive it.
Steps, decisions, handoffs, and where time and error actually accumulate.
What's automated, what's assisted, what's reviewed, and what stays fully human.
Redesign handoffs, signals, and review points so AI fits the work, not the other way around.
Treat governance as a design surface, not a sign-off.
Governance lives inside the workflow — sensitive-data rules, review checkpoints, escalation paths, and the human-in-the-loop decisions that protect customers, employees, and the business. The framework names these as design surfaces alongside capability architecture and measurement, so guardrails shape the workflow instead of getting bolted on after a pilot is already in motion.
Measure adoption, capability, and transformation — not just usage.
The measurement layer tracks four concept dashboards: use-case portfolio, adoption health, workflow transformation impact, and capability architecture. Together they show which workflows are changing, where adoption is sticking, where new capability is forming, and where the operating model needs another turn.
Why this framework exists.
This artifact exists to scope senior AI enablement, adoption-architecture, and workforce-transformation work — and to show the shape of the thinking before the first conversation. It is a strategic artifact, not a delivered engagement.
- Systems thinking applied to AI adoption, not just tool selection
- A repeatable operating model for moving from curiosity to measurable adoption
- Human-centered workflow redesign with AI in the loop
- Governance, guardrails, and measurement treated as first-class design surfaces
- Capability architecture that connects practice infrastructure, readiness, and the broader operating model
Framework · Proof artifact · Not a client case study. This page documents an approach — operating model, readiness, workflow redesign, governance, capability, and measurement — that Liz uses to scope senior AI adoption, enablement, and workforce-transformation work.
Continue exploring
A few next steps. Each one opens another part of the work.