Hiring managers aren't impressed by a list of AI tools. They want to know what you checked, decided and improved.
Every CV in AdTech and performance marketing now mentions AI. Here's how to describe your AI experience so it shows judgement, not just tool use, with before-and-after examples you can borrow.
Key takeaways
- "Proficient in AI tools" now appears on so many CVs that it tells a hiring manager almost nothing.
- What stands out is judgement: what you checked, what you questioned, what you decided and what improved as a result.
- Describe the outcome first, then how AI helped, then the part you owned.
- Be specific about your role. Overclaiming is easy to spot in an interview and hard to recover from.
- Prepare one story where you caught or corrected an AI output. It's often the most persuasive thing you can say.
Read enough CVs in AdTech and performance marketing right now and a pattern appears. Somewhere near the top, usually in the skills section, there's a line that says something like "proficient in AI tools" or "experienced with ChatGPT, Gemini and Performance Max."
It's not wrong to include. It's just not doing anything for you.
When almost every candidate says the same thing, the line stops being a differentiator. And the hiring managers we speak to aren't really asking whether you've used AI. They assume you have. What they want to know is whether you can be trusted with it.
Why "proficient in AI tools" doesn't work any more
AI use in job applications is already mainstream. In a Gartner survey of more than 3,000 job candidates, 39% said they used AI during the application process, most commonly to write CV text. If the CV itself may have been drafted with AI, a claim of AI proficiency inside it proves very little.
There's a bigger shift too. As platforms automate more of the day-to-day work in programmatic and performance media, the value of a person moves from doing the task to judging the result. Gartner's latest guidance for marketing leaders recommends hiring for exactly that: the ability to judge and improve AI-assisted work.
So the question a hiring manager is quietly asking isn't "Can you use the tool?" It's "When the tool gets it wrong, will you notice?"
What hiring managers actually want to see
Across the briefs we work on, the candidates who stand out on AI tend to show four things:
- What you checked. You reviewed the output rather than accepting it.
- What you decided. You made a call the tool couldn't make for you.
- What you improved. There was a measurable result.
- What you owned. It's clear which part was you and which part was the platform.
None of these are about the software. All of them are about you.
A simple formula for writing AI experience on your CV
For each achievement, try this order:
Outcome → how AI helped → the part you owned.
Lead with the result, because that's what the reader cares about. Then explain how AI or automation was involved. Then finish with the judgement you brought to it. That last part is what separates you from everyone else who used the same tool.
Before and after: examples for AdTech and performance roles
Performance marketer
Before: "Managed Performance Max campaigns using AI-driven bidding."
After: "Improved ROAS by restructuring product feed and conversion signals for automated campaigns, after identifying that the algorithm was optimising toward low-margin products."
Programmatic trader
Before: "Used AI tools for campaign optimisation in The Trade Desk and DV360."
After: "Reviewed automated optimisation recommendations weekly, overriding those that conflicted with brand safety requirements, and reduced wasted spend on low-quality inventory."
Account manager
Before: "Leveraged ChatGPT to create client reports."
After: "Cut monthly reporting time by using AI to draft summaries, then rewrote the insight sections so each report ended with one clear recommendation the client could act on."
Ad operations specialist
Before: "Experienced with AI-powered campaign setup."
After: "QA'd AI-generated campaign setups across multiple markets, catching targeting and tracking errors before launch and building a checklist the team now uses as standard."
Notice that every "after" example still mentions AI. It's just no longer the headline. The headline is what you did with it.
Where overclaiming goes wrong
It's tempting to make AI experience sound bigger than it was. In a competitive market, that's understandable. It's also risky.
A few common traps:
- Taking credit for the platform's work. "Increased conversions by 40% through AI optimisation" invites the obvious question: what did you do, and what did the algorithm do?
- Listing every tool you've opened. A long list of AI products reads as breadth without depth.
- Using vague verbs. "Leveraged", "utilised" and "harnessed" tell the reader nothing about your contribution.
- Claiming expertise in something brand new. If a platform launched recently, nobody has years of experience in it. Saying otherwise raises doubts about everything else on the page.
Interviewers in this market are good at following up. If a CV line can't survive two "how exactly?" questions, it's better to rewrite it now.
Your strongest AI story: the time it got something wrong
If you prepare only one example for interview, make it this one: a time an AI tool or automated system produced something that wasn't right, and you caught it.
Maybe the algorithm optimised toward the wrong goal. Maybe an AI-written summary misread the data. Maybe an automated setup had a targeting error. What matters is that you noticed, understood why and fixed it.
It shows exactly what hiring managers are looking for: someone who uses AI confidently but doesn't hand over their judgement.
Should you have a separate AI skills section?
Usually not. A standalone "AI skills" list tends to become a list of tools. You'll get more credit by weaving AI into your achievements, where it sits next to a result.
If a job description specifically asks for certain platforms, by all means include them in your skills section. Just make sure the evidence of how you used them lives in your experience section.
AI on your CV: quick answers
Should I mention AI on my CV at all?
Yes, if you've used it in a meaningful way. Just describe what you achieved with it rather than simply listing tools.
Is it a problem if I used AI to help write my CV?
Not in itself, but read every line back and make sure it's accurate and sounds like you. You'll be asked about it in interview.
How do I describe AI experience if I'm early in my career?
Focus on what you checked and learned. Reviewing AI outputs, spotting errors and improving a process are valuable skills at any level.
What AI skills are AdTech employers looking for?
Less about specific tools, more about judgement: interpreting automated outputs, feeding platforms the right inputs, checking quality and explaining results clearly to clients or colleagues.
If you're preparing for interviews too, our guide on why candidates advance through interviews but don't get offers covers what tends to happen in the final stretch.
Sources
- Gartner, Gartner survey shows just 26% of job applicants trust AI will fairly evaluate them, July 2025
- The State of Brand, Gartner expects AI to wipe out entry-level marketing jobs at most high-performing teams by 2030, September 2026
Want a second pair of eyes on how your CV reads? Send it to chat@uncommonlygoodpeople.com and we'll give you honest feedback.
