When I asked Insiders what they wanted from this report, one question came up directly: How should I be thinking about AI?

AI is a market trend, much like anything else in SaaS. Being able to speak to it shows you understand where the industry is right now.

When I ask people if they're AI fluent, many say yes and some say not at all. So I wanted to understand what companies actually want when they talk about AI in Customer Success job descriptions.

This analysis is based on the full job description text of 742 Customer Success job postings shared on the Job Drop from June through mid-October 2026.

About 55% of Customer Success job descriptions mention AI. When they do, it shows up in three specific ways, and which one you'll see depends on your career level.

It seems like every company is an AI platform for something right now:

For many companies, AI stops at company branding. They talk about themselves as an AI company, and AI shows up in the feature set, but it doesn't show up meaningfully in the job requirements or responsibilities.

That doesn't mean you won't use AI or need to know anything about it. It means it's not a hard requirement for you as a CSM, at least not in the job description.

About 50% of the postings that mention AI only mention it to describe the company. This is especially true in the Mid-Career category.

About 65% of Break Into Success and Associate postings don't mention AI at all. When they do, it's usually basic, like being comfortable with AI tools.

About 30% of postings that mention AI expect you to use it to be a better, more productive CSM.

The team already has AI workflows, and you'll step right into them. Look for “we use” and “we give you”:

Where you'll see it: Mid-Career, including SMB & Digital and Onboarding. AI asks are lighter here, and when they show up, most teams want you at the fluency level they already have.

They want someone who brings new AI skills and helps the team build better ways of working. Look for “test,” “iterate,” “build” and “shape”:

Where you'll see it: Senior and Strategic. When AI comes up at these levels, about 50% of the time it's asking you to use it.

A growing number of companies are truly AI-native: AI is embedded in the product and in the work itself.

AI is the product, and your success is measured on how customers adopt it and get value from it.

Your job is getting customers to adopt AI-specific features.

You lead the AI transformation inside your own org.

Where you'll see it: Leadership and Operations. When AI shows up in a leadership posting, more than 50% of the time it's part of the job, and in Operations, it's about 65%.

When AI shows up in how you'd work, or as the job itself, the job description usually asks for some version of “AI fluency,” or describes the company or the role as “AI-native.” These have become catch-all terms, and there's no consensus on what they mean.

Most job descriptions don't define them at all, and only about 5% name a specific tool. A few do spell it out:

Hiring managers are just as split. One survey found 45% of U.S. employers set the AI fluency bar at basic tool awareness: knowing a tool exists and being able to name it in an interview.

Some companies have built their own definitions. Zapier built an AI fluency rubric for hiring that breaks it down by team and role, and it's a good look at how AI-forward companies are thinking about it.

The key is how you can demonstrate it. In your job search, the best way to demonstrate AI fluency is to build something. Using ChatGPT isn't enough. Using it for your resume and interview prep isn't enough. You need to build something that solves a Customer Success problem.

I built this rubric to define AI fluency for you and help you in your job search. It's connected to Customer Success roles, it's built from how companies are talking about AI in these job descriptions, and it's specific to what you'll actually be asked about.

You haven't used AI in a major way. You haven't tried it, or you tried once and moved on. Unfortunately, in the tech industry, where AI is the dominant conversation, this could be perceived as avoidant. Based on how hiring managers are perceiving AI familiarity right now, my recommendation is to get to a 2 as quickly as you can.

AI-knowledgeable
You use AI like a better search engine: ask a question, get an answer. You've used it to polish things, mostly your email, your resume or your interview prep. Every conversation starts from scratch.

AI-literate
AI is a regular part of your week, and you're comfortable prompting. You summarize call notes, draft talking points for a QBR, or analyze a usage export to find accounts that need attention. You reuse the prompts that work, and you're starting to build things.

AI-fluent
You solve problems with AI. You build reusable things: a Claude skill, a custom GPT, a project loaded with context, or an automation that connects your tools. You know which tools are good for what, and you can architect a workflow end to end.

AI-native
You've automated, built or improved a real Customer Success process, like:

You can speak to the before and after: time saved, more accounts covered, or risk caught earlier.

The big divide is between familiarity and outcomes. Levels 1 and 2 mean you're comfortable using AI: you're AI-knowledgeable, then AI-literate. Levels 3 and 4 mean you've built something with results: you're AI-fluent, and at level 4, AI-native. Some roles only need familiarity, so not every job asks you to be a 4.

Since every company defines these terms differently, put a name to your level when you talk about AI. Instead of just saying “I'm AI fluent,” say what that means: what you've built and what it changed.

Most people I speak with are probably somewhere around a 2, and the real opportunity is building something that has a clear and measurable outcome that you can speak to in an interview.

Rate yourself honestly. Then try something a little more challenging than you have been, and take it from there. We're not even close to hitting the limits of these tools, and as the tooling gets better, it's easy to get comfortable with what you already know.

The best way to show AI fluency in an interview is to build something with a clear, measurable outcome. It can be easy to build a tool or process for your job search and use that as your project. It's a very common idea among job seekers, and unfortunately, it's not setting you up as successfully as you think. Hiring managers don't really want to hear about your job search. They want to hear about problems, and solutions to problems, relevant to their customers.

That's why there's no level 4 job search. Level 4 is about Customer Success processes, and that's where to put your energy. If you're in a role, build it into your real work. If you're not, build a portfolio project.

One person I worked with landed a job fairly quickly after building a customer health score simulation with Claude. It used dummy data and a lot of assumptions, but it showed exactly how he thinks about a book of business.

What makes a strong project:

This analysis is based on the full job description text of 742 Customer Success job postings shared on the Job Drop from June through mid-October 2026. A posting counts as mentioning AI if AI shows up anywhere in the description, not counting notes about AI in the hiring process.

To sort postings into the three ways AI shows up, I read a sample of 120 AI-mentioning postings by hand, 20 at each level. The level breakdowns are directional, so I've rounded the percentages.

All of this comes from job postings, not surveys. That means it shows what companies are actually willing to put in writing when they hire.