Atlassian Marketing Leader Says Focused Expert Voices Strengthen Trust and Discoverability

Two forces are quietly reshaping marketing strategy, and both are pointing to the same solution. Audience trust has shifted away from institutions toward peers and practitioners. Simultaneously, answer engine optimization (AEO) is rewarding consistent, credible individuals whose expertise is distributed across the public internet. For brands still broadcasting authority from the top down, both forces are working against them at once.

Ashley Faus, Head of Lifecycle Marketing at Atlassian, tracks this convergence closely. The author of Human-Centered Marketing and an instructor at Stanford Continuing Studies, Faus brings experience from her career at the intersection of technology and brand strategy, with earlier roles at companies later acquired by Oracle and Cisco. She sees the instinct to spread content across many voices as a compounding mistake. "People trust people like themselves more than they trust traditional markers of authority. From a business perspective, that changes everything," she says. 

• An insider advantage: Internal influence is distinct from conventional employee advocacy, where brands ask employees to reshare content. It means cultivating people with strong personal brands, deep domain expertise, and genuine credibility with the audience the company is trying to reach. Faus points to Laura Erdem, a Sales Director at Dreamdata, who is building a following on LinkedIn by talking substantively about the problem space her customers inhabit. "People trust her because she is the ideal customer, and as a trusted source, she drives a significant amount of pipeline and inbound leads for the company," she says.

• Byline blunders: Generative AI tools reward topic density built around specific individuals, pulling signals from LinkedIn, podcasts, YouTube, owned properties, and Substack. That means a practitioner with a consistent, multi-channel presence becomes more findable and more credible at the same time. The instinct many organizations have to distribute bylines across 20 different contributors works against both goals."You're better served with two or three consistent voices writing 10 blogs each, sharing on LinkedIn, appearing on podcasts, being quoted in the press," she says.

• The loyalty trap: Keeping employee voices tightly on-brand feels like the safe move, but it can quietly undermine the very credibility a brand is trying to build. Over-association with a single company is a liability with both audiences and algorithms. The more a voice reads as a corporate mouthpiece, the less authority it carries in the broader domain. "If the only thing I ever talk about is Atlassian, I'm only associated with Atlassian, and I lose credibility with both the audience and the algorithms regarding my expertise in marketing," Faus says.

Knowing who should speak, and how often, solves only part of the problem. The other challenge is output. Building a consistent, multi-channel presence across LinkedIn, podcasts, and owned properties is a significant lift, particularly for practitioners whose core job is not content creation. That is where AI enters the equation, not as the voice, but as the engine behind the volume.

• AI, the content chef: There is a clear boundary between what AI can and cannot contribute to a human-centric content strategy. Across four pillars of content creation: credibility, profile, depth of ideas, and being prolific, AI is useful at only one of them. "Humans have to bring the credibility and lived experience. They have to build their own profile and, from a depth of ideas perspective, be the ones who think new thoughts and make discoveries," Faus says. AI helps with volume and throughput, clipping long-form video into shareable assets, generating LinkedIn posts from a single source, or synthesizing research across multiple inputs using tools like NotebookLM.

• A sparring partner: AI can pressure-test arguments, identifying the weaknesses an opponent would exploit, the hooks most likely to fall flat, and the blind spots in a creator's reasoning before anything goes public. "Sparring with the AI prompts me to ask why it flagged a certain hook as better or an argument as weak. All of that becomes fuel for more content and more ideas," Faus says.

Faus sees transparency becoming a competitive differentiator as AI-generated content scales. Audiences are becoming more attuned to the difference between content that reflects genuine expertise and content that is assembled. The response is not to hide AI use but to be explicit about it, and to invest in the experiences and outputs that carry a verified human signature. "I think we're going to see people going back to basics. I want to know the human. I want to know they created it. And I want you to be transparent about how you're using these tools."