Quick summary: 63% of CS leaders can’t measure AI performance, which leads to more teams still requiring human approval for every recommendation. CS leaders can remove these bottlenecks by reporting on success metrics, starting AI out on low-risk tasks, and performing small experiments to build trust.

Most CS teams don’t trust AI to make strategic decisions, and the reason might be that they aren’t measuring its performance. Teams that can’t measure AI are four times more likely to require human approval for every AI recommendation.

That’s according to ChurnZero’s 2026 Customer Success Leadership Study, which asked nearly 600 revenue leaders about AI usage and impact. The study found that most CS teams stop AI from making decisions, but teams that can quantify AI performance are more inclined to grant it greater autonomy.

You don’t need to hand AI all your big decisions, but requiring human sign-off at every step could be creating unnecessary bottlenecks. To build AI trust and offload some of your strategic decisions, you need to start measuring AI impact.

Why lack of measurement may undermine AI authority

The study identified a correlation between lack of AI measurement and requiring human intervention at every step:

- Four out of five customer growth teams stop AI from making strategic decisions.

- 63% of CS leaders have no consistent method to measure AI performance.

- Customer growth teams that can’t measure AI are four times more likely to require human approval of every recommendation.

This suggests CS teams that don’t measure AI are much less likely to trust its recommendations because they have no way to tell if AI is reliable. They require human interventions at a much higher rate, which means they may not run as efficiently as teams that offload some decision-making to AI.

Why does AI measurement and decision-making matter?

Measuring AI performance and handing off some strategic decisions can make a difference for your team in a few ways:

- Developing AI maturity: When you measure AI impact, you gain insight into how it’s working and where it can go next to make the biggest difference for your team. The more mature your AI is, the fewer manual approvals your CSMs have to do.

- Removing bottlenecks: Work slows down when your team has to approve every single AI decision. Mandatory reviews pile up and your CSMs end up working through a long checklist, which is the type of tedious work that AI was supposed to remove.

- Focusing on high-value work: AI can take on simple, time-consuming tasks like creating presentations, summarizing meetings and emails, and providing recommendations for next steps based on account activity. When you trust AI to handle this work, your CSMs can spend more time deepening the customer relationship.

“If you can’t connect AI to a measurable change in the business, it becomes very difficult to know where to invest more, where to pull back, or where to give AI greater autonomy.” – Cat Lang, Senior Vice President, Global Customer Success and Professional Services, Outreach

How to measure impact and build trust in AI decisions

Start measuring your AI’s performance and roll out decision-making strategically to reduce manual work for your team:

Report on the right metrics

Measuring AI success doesn’t have to be complicated from the start. Use these strategies to start reporting on the results that matter:

- Measure AI results one workflow at a time: Look at the workflows you’re currently automating, or the ones you’re about to deploy. Define the metric that equals success – such as time saved or expansion conversations booked – and start measuring the results. Over time, compare the numbers with AI vs. the numbers without.

Define the parameters AI must follow: “If you want your AI to do more, the work isn’t buying a better model. It’s writing down what ‘at risk’ means at your company, what finishes onboarding, what counts as adoption — and then holding the system to those definitions. Nobody can grade an answer they never wrote a rubric for.” – John Gleeson, Founder, General Partner, Success Venture Partners

- Put AI in your budget: Track how much you’re spending on AI, and make it a line item in your budget. When you have to justify the money you’re spending on AI, you have a compelling motive to show results.

Give AI low-risk, reversible tasks to start

Building trust takes time, and AI can gradually earn your trust when it successfully completes lower-risk tasks. Start by giving AI simple work, like summarizing meeting notes or performing basic account research — and make sure that, at least initially, humans have the ability to reverse a mistake. As you build trust with AI automations that work, you can start developing more complex workflows and strategic decision-making.

“A low-risk, easily reversible task like answering FAQs or engagement nudges, can get automated even inside an Enterprise account. A high-risk, hard-to-reverse moment gets a human even inside SMB.” – Ejieme Eromosele, VP of Customer Growth, Quiq; and Founder, Success In Black

Experiment with small customer segments

Experiment with what your AI tools can do in a controlled setting without any customer-facing actions. Once you’re comfortable with the testing you’ve done, you can start rolling out tests for small batches of customers. Don’t expand to a wider customer base or add in more workflows until the existing automations have proven that they work.

Measure AI results to develop trust and autonomy

CS leaders will find it difficult to trust AI if they can’t accurately say how it’s working for them. When 63% of CS teams can’t measure AI results, it follows that most teams still require human approval for every recommendation. These bottlenecks tie up CSMs with manual reviews, restricting team performance.

To unlock the potential of your AI and your human team members, start measuring AI one workflow at a time, with meaningful metrics that represent your team’s goals. Start with low-risk tasks and experiment with small groups before expanding. As AI proves what it’s capable of, you can start handing off more strategic work so your team can focus on customer relationships.