The MAKR AI Transformation Staircase

Written By Kate Reed

A new study from MIT’s Center for Information Systems Research (CISR) has put numbers to what many B2B SaaS leaders already feel in their gut: 95% of generative AI pilots are failing to deliver measurable business outcomes.

The findings are based on interviews with 150 executives, surveys of 350 employees, and reviews of 300 publicly disclosed AI projects. The verdict is sobering: most AI onboarding efforts sputter out, stall in pilots, or never scale beyond experiments.

If you’re in Customer Success, this probably sounds familiar.

  • One of your team members is a self-appointed “agent builder,” creating automations without safeguards.

  • Another has flat-out refused to use the new AI copilot because hallucinations made it harder, not easier, to do their job.

  • Meanwhile, your CEO is forwarding you every AI think-piece they find, with vague directives to “just use AI.”

And then there’s you, the CS leader. You’re stuck between pressure from above, experimentation from below, and your own bandwidth and skills gap in making sense of AI’s chaotic landscape. All while trying to hit your number.

The potential of AI in CS is real: it can streamline workflows, coach teams, and scale engagement. But the MIT data proves what many have suspected: without structure, most AI adoption fails.

That’s why I created the MAKR AI Transformation Staircase: a four-stage model, adapted from the MIT CISR framework, tailored specifically to the realities of Customer Success.

It’s a playbook for moving from scattered, high-risk experiments to intentional, outcome-driven AI adoption.

The four stages of the MAKR AI Transformation Staircase, which guide CS leaders from initial assessment through successful transformation with AI in Customer Success.

The 4 Stages of the MAKR AI Transformation Staircase

🗺️ Stage 1: Map the AI Opportunity Landscape

📍 How do you know you’re here?

  • Each team (or individual) has their own process

  • Leaders don’t know where to start

  • Everyone is either throwing random AI tools at the wall or ignoring them completely

  • Customers receive uneven experiences

This is what the MIT CISR framework calls “silos and spaghetti.” Even if individuals succeed, the org as a whole doesn’t get more efficient. If you stay here too long, CSMs will begin to distrust AI entirely.

🚚 The Solution: Map your AI opportunities through a structured assessment.
This might include:

  • Running an AI readiness check across people, processes, and data

  • Identifying high-friction workflows and the easiest, highest-impact places to start (capturing low hanging fruits to get started to demonstrate viability and path to success)

🎯 The goal: Find low-risk, high-impact starting points that directly improve efficiency and customer experience. Done right, you’ll move from overwhelm to clarity with a structured roadmap that creates alignment and trust.

✈️ Stage 2: Activate the AI Pilots

📍 How do you know you’re here?

  • You’ve identified opportunities but stall over cost, compliance, or ROI

  • Struggling to get buy-in across teams

  • Pilots are random tool trials with no measurement

  • Initiatives die in procurement

The result: your team doesn’t trust AI, customers see no improvement, and the CEO keeps demanding “AI literacy” while competitors pull ahead.

🚚 The Solution: Launch narrow, intentional pilots tied to strategy and measurable outcomes.
Examples include:

  • AI playbook recommendations for a specific pod

  • Agents that coach CSMs through saves, measuring impact on churn

  • Standardizing LLMs for call planning and follow-up

  • Custom health score agents surfacing risks and opportunities

🎯 The goal: Validate AI’s impact with measurable business outcomes and continuously iterate to find the best use cases. Early wins build trust, secure budget, and position CS as the model for AI transformation.

⚙️ Stage 3: Key Up AI Operations (KeyOps)

📍 How do you know you’re here?

  • Pilots succeed but remain in silos

  • No governance, no scaling plan, adoption fizzles

  • CSM experience with AI varies drastically across teams

  • Customers still see inconsistencies

You know AI can unlock value, but without scaling, the wins evaporate.

🚚 The Solution: Codify and operationalize what works.
That means:

  • Embedding AI-driven actions into every workflow

  • Setting governance policies that are actually adopted

  • Creating standardized AI playbooks across the org

  • Deploying dashboards to track adoption and performance

🎯 The goal: AI becomes part of the CS operating system. Teams work consistently, customers see predictable value, and CSMs get to focus more on being proactive and strategic.

🚀 Stage 4: Redefine Customer Success Criteria

📍 How do you know you’re here?

  • AI is embedded and makes teams efficient

  • CSMs use predictive health scores, automated prep, proactive nudges

  • But CS is still measured only on traditional metrics (renewals, churn, growth)

This is not future-ready. Efficiency matters, but AI’s true potential lies in reshaping CS into a strategic growth function.

🚚 The Solution: Redefine CS around AI-native capabilities.
Examples:

  • Deliver predictive benchmarks back to customers

  • Use CS intelligence to shape product and go-to-market strategy

  • Position CS as a revenue-generating, strategy-defining function

  • Create AI-driven value streams that didn’t exist before

🎯 The goal: Future-proof CS. With AI as the foundation, CS becomes the engine of growth, competitive advantage, and strategic customer value.

How to Get There

AI transformation doesn’t happen by accident. It requires structure, momentum, and a clear path forward.

The MAKR AI Transformation Staircase gives Customer Success leaders a way to move from scattered experiments to sustainable, measurable impact. By mapping opportunities, running focused pilots, scaling what works, and redefining the role of CS, you can future-proof your team and turn AI into a growth driver (rather than a shiny new tool).

✨ Next Step for You: Where is your team on the AI Transformation Staircase?

If you want help accelerating the journey, you can check out how MAKR works with CS leaders on AI transformation.

Further Reading

Here are some of the best starting points if you want to go deeper into AI and Customer Success:

Kate Reed
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