Free 30-Minute Diagnostic
7 Places Your Agency's AI Implementation Is Broken
Before you buy another tool or hire another person, run this diagnostic. Find the exact spots where your AI stack is leaking time.
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No pitch. No sales call required. Just clarity on where your stack is actually breaking.
What's inside
7 diagnostic tests. 30 minutes. Clear answers.
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1The Process Documentation Test Whether your workflows are written down clearly enough for AI to follow — or if the whole map lives in your head.
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2The Handoff Audit Every point where ownership transfers in your workflows — and whether those transitions are defined clearly enough for AI to handle.
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3The Adoption Gap Check Three questions to ask your team this week to find out which tools they've quietly stopped using — and why.
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4The Output Quality Baseline How to tell whether your AI outputs are actually saving time or creating a new editing workload that cancels out the gain.
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5The "Is This Really an AI Problem?" Test A 5-question diagnostic to find out if your bottlenecks are technology problems — or process problems that no tool will ever fix.
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6The Prompt Governance Check Whether your team is using consistent, documented prompts — or running parallel experiments without knowing it.
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7The Ownership Gap Whether anyone in your agency is actually accountable for AI performance — or whether "everyone owns it" means no one does.
Who this is for
This is for you if...
- → You're running an ecommerce agency with 5–30 people and you've tried to implement AI — but something keeps not sticking with the team.
- → You've said "we use AI" on a sales call and felt less confident in the follow-up than you wanted to be.
- → You've bought tools. Your team isn't using them the way you expected. You're not sure if the problem is the tool, the training, or something else entirely.
- → You suspect there are gaps in your AI implementation but you haven't had time to look closely — and you're not sure what to look for.
Your Diagnostic
7 Places Your Agency's AI Implementation Is Broken
Check the box next to each item that is true for your agency right now. Leave it unchecked if it's not. Your unchecked items are your breaks.
How to use this: Work through each section in order. Check the box next to every item that is currently true for your agency. Sections where you can't check most items are your priority to fix — before you buy anything new or scale anything that's already running.
Section 1 of 7
The Process Documentation Test
Can your AI actually follow your workflow — or is the map still in your head?
You have written, step-by-step documentation for every workflow you're trying to automate — not just a description of the outcome you want.
Any team member — not just the person who built the workflow — could follow your documentation and produce the same output.
Your documentation defines what "done" looks like at each step — not just what to do, but how to know when it's been done correctly.
Your workflow documentation has been reviewed or updated in the last 90 days.
⚠️ AI can't automate what isn't documented. If your team can't follow the workflow without you in the room, neither can your AI tools. Build the process first — then automate it.
Section 2 of 7
The Handoff Audit
Where ownership changes hands is where work falls apart. AI amplifies bad handoffs — it doesn't fix them.
You've mapped every point where ownership transfers in your top 3 workflows — not just the steps, but who hands off to whom and when.
Each handoff has a defined trigger: a clear signal that tells the next person or tool it's their turn to act.
The output format at each handoff is standardized — the receiving person or tool knows exactly what they're getting, every time.
Your workflows could survive a key team member being out for a week. The handoffs are documented, not just understood by the people currently in those seats.
⚠️ Undefined handoffs create garbage inputs. AI receives whatever you send it. Inconsistent inputs produce inconsistent outputs — and you end up spending your time editing instead of shipping.
Section 3 of 7
The Adoption Gap Check
The tools you think your team is using and the tools they're actually using are not the same list.
You can name, without guessing, which AI tools each team member used this week — and it matches what you expect.
When you ask "what's slowing you down with [tool]?" you get specific, honest answers — not silence, vague complaints, or "it's fine."
No tool in your current stack has gone more than 2 weeks without intentional use by the person it was assigned to.
⚠️ Adoption gaps are the #1 reason AI implementations stall. You may have a training problem, a fit problem, or a workflow problem — not a technology problem. Find out before you invest more in tools.
Section 4 of 7
The Output Quality Baseline
If you don't know what "good" looks like before the AI produces it, you're editing on instinct — not standards.
You have a written definition of what a high-quality output looks like for each AI-assisted task — established before you see the result, not after.
You've measured how long it actually takes to review and edit an AI output vs. completing the same task from scratch.
You're tracking revision rounds on AI-assisted work — and the number is trending down over time, not holding steady.
When you do the math — AI output time plus editing time vs. manual time — the AI-assisted version is actually faster.
⚠️ You may have created a new workload, not eliminated one. Measure before you scale. AI that saves time on the first step and adds it back on the second isn't saving time — it's moving it.
Section 5 of 7
The "Is This Really an AI Problem?" Test
Most AI failures aren't AI problems. They're process problems with a new label.
If you removed the AI tool from this workflow tomorrow, the workflow would still run — just more slowly. If it would break entirely, your process isn't ready for AI yet.
The person responsible for this task has a documented, clear definition of success before they start — not just a rough sense of what good looks like.
This task is executed the same way by every team member who handles it — not "whatever works for them" or "however they learned it."
Your bottleneck here is time — there aren't enough hours to do the work. Quality and consistency problems rarely improve with more AI.
There is one named person who owns the outcome of this workflow. Not a team. Not "leadership." One person.
⚠️ Stop. Fix the process first. No tool will solve what's actually a clarity or accountability problem. Adding AI to a broken process doesn't fix it — it makes the broken parts run faster.
Section 6 of 7
The Prompt Governance Check
If every person on your team writes their own prompts from scratch, you don't have an AI system. You have parallel experiments running without oversight.
Your team uses shared, documented prompts — stored somewhere everyone can access and update them, not buried in individual chat histories.
Your prompts include your brand voice guidelines and quality standards — not just the task instruction.
You can tell, from the output alone, whether the correct prompt was used to produce it.
When a prompt produces a bad result, there's a process for identifying why and updating the prompt — not just re-running it and hoping for something different.
⚠️ Undocumented prompts are the fastest route to off-brand output at scale. Every person improvising their own prompt is running a different version of your agency's standards. Prompt governance isn't bureaucracy — it's how you protect quality as you grow.
Section 7 of 7
The Ownership Gap
"We all own AI" is not an accountability structure. It's how implementations quietly erode until someone notices the tool hasn't been used in two months.
There is one named person accountable for the performance of your AI implementation. Not a committee. Not "the whole team." One person.
That person has a defined, measurable metric they're responsible for — not just "make our AI work better."
Someone on your team has a scheduled, recurring time block to review, tune, and improve your AI workflows. It's on the calendar — not just on the to-do list.
You have a documented escalation path for when an AI output misses the mark — not just "tell someone on Slack and figure it out."
⚠️ Without ownership, AI implementations drift. They degrade slowly and invisibly until someone notices the tool hasn't been opened in two months — and nobody quite remembers why they stopped.
Your Results
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/ 28
items confirmed — complete the checklist above to see your full picture
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