Map the AI Opportunity (for Customer Success)
Step 1 of the 🪜MAKR AI Transformation Staircase 🪜
Map the AI Opportunity: The first stage of AI transformation in the MAKR AI Transformation Staircase
When you hire a new CSM, you don’t just say “We need a CSM.”
You define the role: the tasks they have, the workflows they use, the segment they work with, how you’ll measure success, and how they’ll integrate with the team.
And, as every hiring manager can attest, the better you define the role, the better you can find a candidate that 1) fits what you’re looking for and 2) has the right expectations for the job.
It’s the exact same thing when it comes to introducing AI to your team’s workflows.
Before you “hire” AI into your org, you need to know what that AI will be doing.
That’s where Mapping the AI Opportunity comes in. It’s the work you do that helps you avoid pilots that burn cycles without proving value, and find AI opportunities that are low risk, high impact.
This mapping exercise is your first step onto the AI in Customer Success Staircase. It’s the path from experimentation to transformation.
Three Ways to Map Your AI Opportunity
Workflow Audit (The Obvious One)
Pull up 5 recurring CS workflows (onboarding, renewals, adoption campaigns, escalations, etc.).
For each, map:
Current Actions: what humans are doing today.
AI Candidate Job: what part could AI reasonably do.
Data Inputs: what data AI would need to succeed.
Look for overlap between high manual effort and repeatability. That’s usually your lowest-risk, highest-value AI entry point. It’s also where your CSMs often get bored or frustrated, so it’s a win-win when you find it.
Friction Mapping (Kate’s Favorite)
Go straight to your CSMs: “What’s the work you dread or repeat the most?”
What really shines about this tactic is that it’s human-led and gets your team involved early, which means better adoption later when it’s seen as a bottoms-up initiative rather than top-down.
Document the pain points by workflow (e.g. chasing onboarding forms, manually prepping customer decks, summarizing escalations).
Score each by:
Customer impact (does it directly improve CX?)
Internal impact (does it save real time?)
The sweet spot is where high-friction tasks align with measurable outcomes.
Cross-Functional Opportunities (Great for Showing Impact & Getting Adoption Later)
Sit down with cross-functional stakeholders (Sales, Product, Support) who often interact with CS. Your goal is to find a workflow that AI can help increase cross-functional alignment, which ultimately means a better experience for your customers, your team, and your colleagues.
What I love about this approach is that it breaks down silos.
Ask three simple questions:
What does “good” look like in this workflow?
Do we have the data to prove it?
Would AI save us time or improve customer outcomes here?
You’ll quickly uncover which workflows have enough clarity + data + impact to be realistic AI candidates.
Another critical point is to search for opportunities for transformation that are aligned with your org’s overall vision for AI transformation. For instance, if the emphasis is on breaking down silos, #3 is a great place to start. You don’t want CS to be rowing in the opposite direction of the rest of the org; instead, you want your work to reinforce and expand it.
Mapping Your Opportunity: 5 Core CS Workflows
While every org is unique, most CS motions are pretty common. Here’s a few common opportunities:
Onboarding: Customize coaching, automate reminders, draft personalized plans, flag setup risks.
🚩 If onboarding lives in tribal knowledge, AI just automates confusion.
Adoption: Identify gaps, generate tailored success plans.
🚩 If adoption = “logging in,” AI can’t prove impact.
Renewal & Expansion: Forecast risk, flag upsell signals, generate briefs.
🚩 If renewal is a fire drill, AI only speeds up the chaos (or makes it sound even less sincere).
Escalations: Summarize incidents, suggest resolution steps.
🚩 If you rely on memory, AI has no foundation.
Voice of Customer: Aggregate feedback, surface patterns.
🚩 If VoC = “what we remember,” AI insights will be shallow.
Where This Fits on the MAKR AI Transformation Staircase 🪜
Once you’ve mapped your opportunities, you’re ready to climb the next steps of the MAKR AI Transformation Staircase:
Activate pilots: Test AI in narrow workflows with measurable outcomes and defined impact.
Key up operations: Bake AI into processes and data flows across the org.
Redefine CS: Redesign CS around new AI-driven capabilities.
Most teams want to jump to “operationalize.” Mapping opportunities helps you start where the risk is low and the impact is high—so every step you take builds credibility.
The Bottom Line
AI doesn’t succeed in CS because it’s trendy.
It succeeds when you map the opportunity, define the job, and measure the outcome.
Start with one workflow. Give AI a real job to do. That’s your foothold on the staircase.
From there, the climb begins. 🪜
