Start with one recurring workflow.
Look for the specific point where quality, repeatability, ownership, or trust breaks down.
Framework The Five Gaps
The Five Gaps explain why AI adoption stalls. They are a diagnostic lens, not a mandatory service sequence. Different workflows may require education, process redesign, quality controls, software configuration, automation, or no intervention.
01 How to use the lens
Look for the specific point where quality, repeatability, ownership, or trust breaks down.
Education, redesign, controls, configuration, and engineering solve different problems.
Compare realistic cases with an agreed baseline, then scale, revise, automate selected steps, or stop.
02 The diagnostic
A workflow can be blocked at one gap, several gaps, or none of them. The lens helps frame the question; evidence determines the intervention.
Gap 01
Do people understand what the tools can and cannot do?
What may be happening
People may know that AI exists without understanding its practical limits, data implications, or relevance to a specific piece of work.
What this gap usually requires
Clear, credible education may be enough. Free vendor education, internal guidance, or a focused briefing can help people form a useful mental model before any workflow changes are considered.
Gap 02
Can people use AI reliably inside the work they already own?
What may be happening
General knowledge does not automatically become a repeatable method. Instructions, context, source material, review criteria, and human decisions may still live in one person’s head.
What this gap usually requires
Role-specific practice and workflow design may be appropriate: map the task, define AI and human responsibilities, create reusable context, and test the method on realistic examples.
Gap 03
Can more than one person run and review the workflow consistently?
What may be happening
Useful methods often remain personal. Quality varies, managers cannot compare approaches, and the work depends on undocumented prompts or individual judgment.
What this gap usually requires
Shared standards, management support, named ownership, common context, review roles, and documented operating methods may be needed before broader adoption makes sense.
Gap 04
Can the workflow operate dependably beyond a controlled test?
What may be happening
A promising prototype may still lack stable inputs, monitoring, exception handling, integration, security review, or a person accountable for its ongoing performance.
What this gap usually requires
Software configuration, engineering, monitoring, failure handling, and operational ownership may be required. Some workflows should remain human-operated rather than automated.
Gap 05
Can the work be reviewed, governed, and defended?
What may be happening
AI-assisted output can create risk when source requirements, approval authority, sensitive-data boundaries, and escalation conditions are unclear.
What this gap usually requires
Evaluation criteria, governance controls, source verification, human review, approval gates, and escalation rules may be appropriate. The client retains accountability for professional decisions.
03 Solution-neutral by design
The same visible symptom can have a different cause in a different workflow. A responsible recommendation stays open until the work is understood.
Useful when the blocker is understanding. It may be a vendor resource, an internal briefing, or role-specific practice.
Useful when the task itself needs clearer inputs, human decisions, context, review steps, or ownership.
Useful when quality, source verification, data boundaries, approvals, or escalation conditions are weak.
Useful only when the workflow evidence supports it. Some steps may merit automation; others should stay manual or be left alone.
Have a recurring workflow that is expensive, repetitive, or difficult to review?
See the Trusted Workflow PilotChoose one workflow to test
Bring one recurring workflow. We will determine whether it is a suitable candidate for a measured pilot.
30 minutes · No pitch deck · Honest fit check