Key Takeaways
- AI can crank out content fast, but volume isn’t the win. Build advisory agents loaded with your brand voice, tone and format rules so your team ships approved work instead of AI slop.
- Stop chasing traffic and start chasing revenue. Map keywords to buyer cohorts, track landing pages by influenced revenue and prove that content drives pipeline, not just clicks.
As marketers continue to navigate AI use cases — and as they contend with AI-inspired job losses, such as Block’s layoff of 4,000 employees — the question becomes whether and how humans and AI tools can partner to support pipeline and drive conversions.
One well-attended session at B2BMX 2026, powered by Advertising Week, tackled exactly that question. The session, Marketing Fundamentals Under Pressure: Turning Content into Pipeline in the Age of AI, paired Hayley Ho, Senior Director of Content at WordPress VIP, with Gillian Hinkle, Senior Director of Growth and Digital Marketing at Salesforce.
Their premise was straightforward: Use AI to build stronger content, choose key terms that actually drive pipeline, and operationalize the whole thing into a flywheel.
Impact of AI on Content and Business
The packed room was split between content marketers and demand gen pros, and Hope made clear that both camps shared the same anxiety. In short, AI can produce more of everything, faster than ever — but more isn’t the goal. The pressure is to prove that content moves the business, rather than just the publishing calendar.
Hope framed the stakes plainly. Marketers feel the squeeze from two directions: While leadership demands that marketing teams adopt AI to do more, those same teams harbor a quiet fear that the technology is coming for their jobs. The session’s purpose was to hand that confidence back to marketers, repositioning them as the orchestrators of the tech rather than its casualties.
“We all saw the news on how Block eliminated nearly half of their workers. And as a reminder, that’s 4,000 people. That’s because the CEO Jack Dorsey said that AI can do it more and do it better,” said Hope. “Yet here we are, under pressure to use AI for all that it’s worth. At the same time, [we’re] looking over our shoulders, maybe worried that AI is coming for our jobs. Or [maybe] that’s just me. Hopefully, this session will give us the confidence back on the value that we bring as the orchestrators of the tech.”
The answer isn’t to retreat from AI or surrender to it — instead, now is the time to take the wheel.
Julian Hinkle’s Background and AI Integration
Hinkle’s relationship with AI is, in her words, both wonderful and tricky. Her original degree is in music, and her life has straddled two worlds: a highly technical family of engineers on one side and a deeply creative lineage on the other. That tension shaped how she approaches the technology today.
Rather than treating AI as a threat to creativity, Hinkle chose to get involved. She wanted to understand the tools, to work alongside the engineers and product teams she sits with at Salesforce, and to help shape the conversation instead of watching from the sidelines. Her marketing roots run deep, going back to writing her first website in Notepad and publishing it on WordPress.com.
“When we think about AI, I can’t really acknowledge there’s this sense that, what about our creativity, is it being stolen from us? And my thought is, rather than just throw my hands up and walk away, I want to be very involved with the technology,” Hinkle explained. “I want to understand the other leaders, and I want to be able to help shape the conversation. But ultimately, in marketing, we don’t get to do more of what we’re doing if we can’t prove pipe. As a person that’s been in that demand gen and the content side, if the content is not there, you’re not going to get pipe.”
That conviction — that content and pipeline are inseparable — became the spine of the entire session.
Improving Content Quality with AI
Hope opened this stretch with a complaint that every marketer recognizes. Swap the logo on most AI-generated pages and nobody would blink. That’s not content strategy; that’s a content assembly line. The challenge she put to Hinkle was how to use AI to raise the bar on story, clarity, and brand differentiation, rather than just cranking up the volume.
Hinkle’s answer? Advisory agents. When a product manager handed her a finished HTML blog post that ignored every workflow, every brand guideline, and every tonal rule, she didn’t fight the AI adoption. She built around it. She developed advisory agents loaded with Salesforce’s tone, voice, format rules, and even technical restrictions on specific characters that wouldn’t render or that needed special code treatment.
“We wanted a grading system that would let them know where to develop the extra style, but then also told them things like, hey, clarity is good, your accuracy is good…all of those things. We put it all into this agent that they can then use directly,” Hinkle stated. “They attach that Google Doc, send it back and forth, work it themselves, and it gives them suggestions but reminds them to do stuff before they hit their workflow.”
“So, when I get to have that conversation with them, I’m still having a conversation about, ‘Oh, this is an interesting release. Did you catch all these things?’ Instead of going back and forth because they handed me something that was AI slop.”
The payoff was speed without sacrifice. The AI agents became shareable, approved frameworks the whole team could build on, a direct counter to the disruptive sprawl of shadow AI.
Optimizing SEO Strategy with AI
Search felt wildly disruptive this year, and Hinkle didn’t pretend otherwise. She’d watched people chase hacks straight out of 1999, including one agency claim that keyword-stuffed shadow pages could win the top spot for a brand-new product. Her verdict was blunt: It won’t work long term. The fundamentals always come back.
She pointed to Google’s John Mueller, who stated flatly that you can’t have generative engine optimization without SEO. So, Salesforce doubled down on structure. Title tags on product pages, full-page semantic clarity that doubled as an accessibility win, and a disciplined approach to FAQs, placing them on specific product pages rather than dumping them into a single orphaned page.
“Internally, people were getting wrapped around the axle [of] ‘Is it GEO, is it AEO, is it AIO?’” Hinkle said. “I stopped talking any of those words. And instead, when we would say, ‘Debbie wrote something. I would really like a lot of people to read it.’ And that would be the conversation. We’re finding too you have to answer, individually, the what, the how [and] the why in your content and keep those separated, for both humans and machines, really specifically.”
Then came the deeper shift: from keywords to cohorts. Instead of chasing terms, Hinkle’s team mapped the actual decisions buyers face, fully managed versus self-hosted, and grouped queries around those choices. Smart cohorting, drawn from tools like Semrush, Google Analytics, and Parse.ly, surfaced the trends worth acting on.
Connecting Content to Pipeline Revenue
The hardest internal sell, Hope admitted, is drawing a line from a thought-leadership post to downstream impact. So, both leaders pushed past traffic and toward revenue. Hinkle separated educational cohorts, valuable for nurturing customers on starter products, from bottom-of-funnel cohorts where buyers have a problem to solve and a solution to build.
That distinction reshaped spend. Educational content still mattered, but the team prioritized keywords tied to buyers who could take an idea, build it, and see value quickly. Hope described the WordPress VIP equivalent: mapping every touchpoint from first landing page to MQL to opportunity, then optimizing for the cohorts and topics genuinely centering pipeline.
“Everyone was freaking out. We saw some organic traffic dip as AI Overviews took over,” explained Hope. “But the C-suite is not going to bat an eyelash if our revenue numbers are healthy or are rolling up because we’re seeing higher-intent traffic coming from ChatGPT.”
“We have to retrain our leadership, so don’t just go for traffic. My report literally is landing pages by influenced revenue, and then I look at the number of opportunities we’ve driven by industry. So, we have a clear picture of which landing pages are driving the most impact, or which parts of our customers.”
Balancing Content Creation and Stakeholder Expectations
The final tension is the one nobody escapes. AI makes content cheap to produce, so the backlog only grows. An audience member asked how to decide what not to create, and how to manage stakeholders who keep pumping out posts.
Hinkle uses three filters, borrowing a concept from her engineering counterparts to make the maintenance cost vivid:
- Is it appropriate to the buying cohort and the users who’ll use it?
- Does it actually contribute to conversion?
- And only then, does it serve AEO and GEO goals?
“I think you really need to step into something that ops and engineers talk about, which is day two. Websites sprawl quickly and become wildly infected,” said Hinkle. “In engineering, day zero is creating the thing; day one is launching it; and day two you now have to maintain it.”
“If you’re constantly adding new information — you know, ‘I saw that thing on TV, so now I need to do a blog post about it’ — your internal linking has lost revenue. You have to express that back to your leadership team and say, ‘Instead of just doing more, we need to optimize what we have and get better.’”
The lesson for marketers under pressure was clear: AI hands you near-infinite capacity, but capacity isn’t strategy. Build the guardrails, measure what converts, and have the courage to optimize rather than multiply. That’s how you turn content into pipeline, and that’s how marketers will keep their seat at the table.