Feeling Behind on AI? You’re Probably Not. Two Hot Takes with Trinity Nguyen, CMO & AI GTM at UserGems

You can’t log into LinkedIn without being inundated with AI in GTM. But just because it seems like everyone has already figured it out, doesn’t mean they have.

Ross Rich, CEO and Co-Founder of Accord, sat down with Trinity Nguyen, CMO & AI GTM at UserGems, to talk about what AI adoption looks like inside GTM orgs. Here are her two hot takes.

Hot Take #1: Don’t Blow Up What’s Working

There’s a lot of pressure on GTM leaders right now to move faster on AI. CEOs and boards have AI mandates, and they expect their teams to show real progress. That pressure makes it tempting to look at everything you’re doing and assume it needs to be rebuilt. But it doesn’t.

“If you got to hundreds of millions of ARR, or billions even, something you did is right,” Trinity says.

AI-native companies have the advantage of building their processes around AI from day one. But if you’re an established company, you already have processes, systems, and teams that got you where you are. So, start there.

You don’t need to reinvent the wheels your company already runs on. Look at what’s working, where you’re getting stuck, and where AI could make something better, faster, or easier. Then build on top of that rather than starting from scratch.

Hot Take #2: Not Everything in Marketing Should Be Automated

Before you start handing parts of your marketing function over to AI, you need to figure out where it can add value and where humans still need to lead.

“Marketing is like seven different disciplines. You can’t master all seven, so you need to figure out your major and minors,” stresses Trinity. “When you talk about the age of AI and how to agentify marketing, you need to figure out the parts where humans will drive 80% and AI will support 20%, and I think brand is one of those.”

A good place to start is by mapping out what your team actually does. Not just the big buckets like content, demand gen, or brand, but the individual tasks that sit underneath them. Then, look at each one and ask:

• Does this require human judgment?
• Does someone need to make a decision?
• Does the quality depend on context, creativity, or relationships?
• Is this repeatable work that AI could reliably take off someone's plate?

You don’t have to do every job yourself, but you do need to understand the work well enough to know what good looks like, where AI can help, and where it might actually hurt.