Half of all online content is now AI-generated, and a lot of it is garbage. Buyers are revolting against AI slop, seeking authenticity and real human connection instead. For customer marketers, this is actually good news.
Sure, AI can write your first draft. But it can do a lot more than that, dig through customer data, spot patterns you'd never catch manually, auto-generate proof points, and make sure buyers find you when they search for solutions.
In our recent panel on AI-Powered Customer Marketing, Jane Menyo, Sr. Director of Product Marketing - Solutions at Gong, Courtney Dolecki, Director of Customer Experience Marketing at G2, and Natalia Rybicka, explored how to use AI without contributing to the noise. If you're overwhelmed by the tool explosion and unsure where to start, here's what you need to know.
Stop Chasing Tools. Start Solving Problems.
With new AI tools launching daily, it's tempting to demo everything. Some companies have even made AI tool adoption part of performance reviews, which completely misses the point.
"It really is that technology that can empower us to do our jobs better," Jane explained. "If there's something I'm doing that's incredibly repetitive or I'm constantly beating my head against a wall over, how can I look to AI solutions to alleviate that pain?"
The key is starting with the problem, not the tool. If you go out broadly with a corporate mandate to "drive AI adoption," you'll get lost. But if you know you have a specific pain point (eg. creating case study drafts, matching references, consolidating customer feedback), you can find solutions that actually deliver.
"I really just see it as working smarter, not harder." Courtney added.
Her advice for evaluating new tools: ask your network. Talk to colleagues, partners, and peers about what they're using and what success they're seeing. Customer proof applies to your own tool selection too.
The Real AI Unlock: Turning Conversations Into Customer Intelligence
Traditionally, customer marketers relied on surveys, interviews, and direct outreach to gather sentiment. AI changes that equation entirely.
“What's really fascinating is how we've been able to take natural language and turn that into data," Jane said. "Think about how ChatGPT was trained on millions of videos to learn language skills and understand what people are saying, their intents and outcomes. It's similar — how can you better understand your world by taking language and leveraging it as actual data points?”
This is the signal revolution. Instead of being limited to hard-coded fields, NPS scores, and structured feedback, customer marketers can now extract intelligence from conversations happening across the business, including sales calls, emails, support tickets, and reviews.
At Gong, this means using their own call recording technology to get aggregate insights about accounts before ever reaching out. Who's the key stakeholder? Why did they buy? What outcomes are they driving toward?
"When you go to engage with the customer, it's less about that learning and coordination process," Jane explained. "You come in with all of this intel, and you're really just focusing on the relationship building and getting that proof on the record."
At G2, AI helps capture what Courtney called "that unstructured black hole feedback" from calls and converts it into meaningful review content, reducing friction while increasing credibility.
Why Reviews Now Drive Discovery (Not Just Validation)
Here's a shift that should change how customer marketers think about review programs: reviews aren't just badges for your sales deck anymore. They're determining whether buyers discover you at all.
"We are definitely seeing that a lot right now," Courtney confirmed. "LLMs favor natural language and tone, conversational FAQs, question-based headings, anything that's easy to digest, which is exactly what G2 provides."
Search is fragmenting. AI tools are becoming primary search engines, and they're pulling from trusted sources with authentic customer voice. Your G2 reviews, customer quotes, and proof points are now SEO and AEO assets.
This means the customer intelligence you're collecting isn't just for sales enablement—it's powering whether prospects find you in the first place.
Making Customer Proof Actually Discoverable
The best customer proof is pervasive—in every pitch deck, every campaign, every page of your website. But that creates a measurement problem.
"Because you're peanut buttering all of your content, you have no direct ties into influence," Jane acknowledged. "I'm not gonna put a gate on my case study just because I need the credit. That's not the right thing to do for the business."
The solution isn't gating content. It's building systems that make proof findable and trackable.
At Gong, sellers use Peerbound's Slackbot to query for exactly the customer proof they need—no more digging through Highspot pages hoping something's relevant. That gives the customer marketing team visibility into what's being used, what's working, and where the gaps are.
"We not only have better availability to serve them, but we also know where we have gaps and where we need to focus on building more."
Measuring AI Impact: Start Small, Think Like a Scientist
The honest truth: measuring AI's impact on customer marketing is still hard. Courtney compared it to the early days of social media marketing.
"It was really hard to quantify the impact of an Instagram story. You can track engagement, but how does that impact your bottom line? It was a gray area for a long time—and for some companies, it still is."
Her advice: watch the trends. Track SEO traffic versus AEO traffic. Look at how discovery patterns are shifting and connect that to business outcomes over time.
Jane's approach is more experimental. "Go back to your high school chemistry class. Start with a hypothesis. I have an idea, and I want to see if it's correct."
Gong ran a pilot using Peerbound to turn customer conversations into recommended G2 reviews. The results: reviews were 2.5x longer than traditional reviews, had twice as many product mentions, and five times more value prop mentions.
"I don't know how I'm going to quantify the SEO value on that yet. But I do know from the quality of the reviews, that piece is definitely going up."
Tools Worth Watching
When asked about exciting AI capabilities, both panelists pointed to tools that reduce friction and accelerate customer intelligence gathering.
Jane highlighted Gong's new AI Builder feature, which lets marketers create discovery guides, questionnaires, and content grounded in actual customer conversations—segmented by industry, persona, or use case.
Courtney pointed to AI-assisted review tools that turn phone calls into review scripts, plus localization platforms that can push content across markets and languages in seconds instead of weeks.
"That's where I nerd out over AI," Courtney said. "Tools that can really help customer marketers do their jobs quicker."
The Bottom Line
AI isn't going to replace customer marketers. But it is changing what the job looks like. The teams that thrive will be those who use AI to surface customer intelligence faster, make proof more discoverable, and free up time for what only humans can do—building real relationships.
The irony of the AI era: as content gets cheaper to produce, authenticity becomes the differentiator. And nobody owns authenticity like customer marketers.
Key takeaways for using AI in customer marketing:
Start with the problem you're solving, not the tool you want to adopt
Use AI to turn unstructured conversations into actionable customer intelligence
Rethink reviews as discovery assets, not just validation badges
Build systems that make customer proof findable and trackable for sales
Measure AI impact experimentally—start with a hypothesis and track quality metrics
Focus your human time on relationship building, not data gathering
Want to see how customer marketers at companies like Gong and G2 are using AI to surface customer intelligence? Watch the full session here.
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Learn how to use AI for customer marketing without adding to the slop. Tips from Gong and G2 on tools, measurement, and building real customer intelligence.
