43% of people are less likely to buy from companies that rely on AI-generated content. 51% would hesitate to recommend a brand that overuses it. 

Those numbers alone should stop any marketer in their tracks, but here's what makes them truly uncomfortable: 

AI has simultaneously made content faster, cheaper, and more abundant than ever. More output, less belief. 

Something isn't adding up.

To dig into this tension, Mavuus hosted a Coffee Chat bringing together three marketing leaders with distinct but complementary perspectives on what it actually takes to build credibility in 2026:

• Christine Royston – CMO of Wrike and former marketing leader at Salesforce, Dropbox, Udemy, and Bitly, with deep experience scaling brands through hypergrowth and global expansion.
• Tania Rai – Strategic communications specialist with 15+ years in executive messaging, crisis communications, and brand storytelling, known for helping organizations lead with clarity and credibility when it matters most.
• Liza Adams – AI Advisor and GTM Strategist who helps marketing teams build practical Human+AI workflows, drawing on 25+ years of experience at companies like Smartsheet, Juniper Networks, and Pure Storage.

Over 60 minutes, the conversation moved well beyond the AI hype cycle and into something more substantive: how modern CMOs are rebuilding trust, protecting their brand voice, and using AI as a tool, without letting it become the voice. 

Table of Contents:

1. Why Trust Is the Scarcest Asset in Marketing Right Now
2. AI as Accelerator, Not Author: How Smart Marketers Are Actually Using It
3. The Critical Thinking Trap and How to Avoid It
4. What Real Credibility Looks Like: Content, PR, and Proof
5. PR in the Age of AI: From Cost Center to Growth Engine
6. KPIs and Resources Worth Bookmarking

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1. Why Trust Is the Scarcest Asset in Marketing Right Now

There's a paradox sitting at the center of modern marketing that most leaders are reluctant to say out loud: 

We have more tools, more content, and more reach than ever before. But audiences believe us less than they ever have.

And yet, the dominant response from the marketing world has been to produce more – more content, more personalization, more automation, more scale.

The problem isn't volume. The problem is that volume, at a certain point, becomes noise. And AI-generated noise, in particular, has a recognizable texture. Audiences have developed a sensitivity to it. Journalists can spot an AI-generated pitch almost instantly. Buyers are developing the same instinct.

As Tania framed it during the session, brand reputation is everything and trust is the currency it runs on. 

That currency devalues fast when audiences start questioning whether what they're reading is real, considered, or actually meant for them. What used to be a slow erosion of credibility is now something that can happen at scale.

The uncomfortable truth is that efficiency and credibility are pulling in opposite directions right now. AI has made it dramatically easier to fill the content pipeline. But filling a pipeline and building belief are two entirely different things and conflating them is where many marketing teams are quietly losing ground.

This doesn't mean AI is the enemy. It means the brands that win in this environment will be the ones that understand the difference between using AI to move faster and using it as a substitute for thinking harder. That distinction is where credibility is either protected or slowly eroded, and it's where the most important decisions for CMOs in 2026 are actually being made.

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2. AI as Accelerator, Not Author: How Smart Marketers Are Actually Using It

If the trust crisis is the problem, a knee-jerk rejection of AI isn't the solution. The marketers navigating this moment most effectively aren't avoiding AI – they're using it differently. The distinction they keep coming back to is a simple but important one: 

AI is a tool in service of your voice, not a replacement for it.

As Liza Adams put it, the people who perform best with AI aren't the ones who hand everything over to it. They're the ones who stay in the driver's seat, using AI to move faster, structure better, and pressure-test their thinking.

What that looks like in practice

The speakers shared concrete ways they actually use AI in their workflows and none of them looked like "write this for me":

• Summarizing and structuring – using AI to organize sprawling notes or research into a coherent skeleton, then building from there with your own voice
• Challenging your own thinking – running your messaging through an AI "challenger" persona (a skeptical industry veteran, for example) to surface weak arguments and jargon before your audience does
• Training AI on what not to say – feeding it your brand's off-limits language, tone guidelines, and past missteps so it works within your constraints rather than against them
• Turning long-form content into new formats – tools like NotebookLM can transform a white paper or newsletter into a podcast-style audio summary, making content more accessible without diluting the original thinking behind it

The prompt quality problem

One thing the conversation kept circling back to: the output is only as good as what you put in.

Generic prompt → generic content. Forgettable, polished, interchangeable – exactly the kind of material that's flooding every inbox and feed right now.

But when you feed AI original context, your actual insights: your specific audience, your real point of view – the output stays distinctive. 

That's not a prompt engineering trick. That's just the reality of what AI is: a mirror that reflects the quality of thinking you bring to it.

The "same tools" problem

Here's the challenge that no amount of better prompting fully solves: if every marketing team has access to the same AI tools, trained on the same data, optimized for the same outputs – where does differentiation actually come from?

It comes from what AI can't replicate:

• Your proprietary customer insights
• Your executives' genuine points of view
• Your brand's earned credibility and relationships
• The human judgment that decides what to say, when, and why

AI can help you say it faster and more clearly. But the thing worth saying still has to come from somewhere real. That's the part no tool can automate, and in 2026, it's also the part audiences are paying the most attention to.

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3. The Critical Thinking Trap and How to Avoid It

Here's the paradox Liza Adams put on the table that stopped the room: 

We say we don't want AI to replace human thinking. But our behavior increasingly suggests otherwise. 

When teams use AI to generate the answer rather than interrogate it, when they ship the first output without pressure-testing it, when the pipeline moves so fast there's no time to ask "wait, is this actually right?" – that's AI quietly replacing the judgment it was supposed to support.

And the consequence isn't just mediocre content. It's credibility leaking out of your brand slowly, steadily, in ways that are hard to trace until the damage is done.

The antidote is using it more deliberately and that starts with how you think about the role AI plays in your process.

Liza's three-level critical thinking framework

Liza shared a practical framework she uses to keep human judgment at the center of her AI workflow. It operates at three levels:

Level 1: Use AI to evaluate your thinking

Don't ask AI for the answer. Ask it for options, trade-offs, and confidence levels. If you're choosing a blog topic, don't prompt "give me the best topic." Prompt "give me three options, with pros and cons for each, and how well each aligns with our persona and objectives." Then you make the call. AI does the analysis; the human does the judgment.

Level 2: Use AI to pressure-test with different perspectives

Take something you've created and run it through the lens of everyone in the buying committee – the influencer, the decision maker, the champion, the end user, the ratifier. Ask AI how each of them might read your content, what might land, what might fall flat, what might raise a red flag. The result isn't AI telling you what's good. It's AI handing you a set of perspectives you might not have considered on your own.

Level 3: Use AI to challenge your assumptions

This is the level most people skip and the most valuable one. Feed AI your assumptions and ask it to argue against them. What if you're wrong? What are the counterarguments? What might you be missing? Because here's the thing: AI doesn't judge you. There's no ego on the line, no fear of looking foolish in a room full of peers. It's a genuinely safe space to stress-test your thinking before you take it to market.

As Liza put it: by the time you walk into a room, or publish a piece of content, you've already heard the counterarguments. You're prepared. In that way, AI doesn't make you less human. It actually makes you more confident, more considered, and more effective as a thinker.

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4. What Real Credibility Looks Like: Content, PR, and Proof

Strategy and frameworks matter. But at some point, credibility has to show up somewhere tangible – in the content you publish, the stories you pitch, the proof points you put in front of your audience. 

Content: clarity beats polish

Christine Royston was direct about what actually earns her attention as a consumer of content: it has to be personable, easily digestible, and clear about what she'll get from it. 

Not impressive. Not optimized. Clear and human.

That instinct points to something broader. In a world where AI can produce polished content at industrial scale, polish is no longer a signal of quality. It's table stakes and sometimes even a red flag. 

What stands out now is:

• A genuine point of view, not a synthesized consensus
• Content that reflects real experience, not research aggregation
• A recognizable human voice behind the words — someone with actual authority on the subject
• Format that serves the reader: short-form and long-form both have their place, but only when the choice is intentional

Short-form and long-form: different jobs, equal importance

Tania Rai was clear that the short vs. long debate is a false choice: both formats are still relevant, but they serve fundamentally different purposes and shouldn't be treated as interchangeable.

Short-form content – a sharp LinkedIn post, a punchy video clip, delivers immediacy. It feels human, it travels fast, and it builds familiarity over time. 

Long-form content, on the other hand, is where authority is built and sustained. A well-placed CEO byline, a research-backed thought leadership piece, an in-depth industry perspective – these are the assets that establish your brand as a credible voice in your category.

And there's a practical dimension to this that's becoming increasingly important: long-form content with original data and third-party references is also what feeds AI-powered search. 

As audiences rely more on LLMs to surface information, the brands with substantive, authoritative long-form content are the ones getting picked up and cited. It reinforces credibility in the traditional sense and increasingly in the algorithmic sense too.

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5. PR in the Age of AI: From Cost Center to Growth Engine

For years, PR has fought an uphill battle for its seat at the executive table. It was seen as a support function: reactive by nature, hard to measure, and perpetually justifying its existence against more attributable marketing channels. 

That's changing. And AI is a big part of why.

Tania Rai distilled the shift into three distinct areas where AI is fundamentally reshaping what PR and communications teams can deliver:

1. Eliminating the grunt work tax

Historically, a significant chunk of PR bandwidth has been consumed by manual media tracking – monitoring coverage, logging hits, compiling reports. Valuable in theory, tedious in practice, and not where the best communications minds should be spending their time.

AI gives that time back. Monitoring, pattern recognition, and coverage tracking can now be handled at a fraction of the cost in human hours, which frees PR teams to do what actually moves the needle.

2. From reactive to proactive

The traditional PR posture has been reactive – respond to what's happening, manage what's already in the news cycle, scramble when a crisis hits. AI enables a fundamentally different mode of operating.

Tools like Meltwater can now surface macro trends before they hit mainstream news, giving communications teams the intelligence to get ahead of narratives rather than chase them. 

That shift repositions PR from a function that responds to the news to one that helps shape it.

3. Closing the executive measurement gap

This is perhaps the most significant shift of all. Tying PR to business value has historically been difficult and that difficulty has cost communications teams credibility at the executive level for decades.

AI is changing that. It's now possible to track message pull-through, connect share of voice to brand reputation movement, and draw a clearer line between PR activity and the metrics that executive teams actually care about. 

That's not just a reporting improvement. It's a fundamental repositioning of what PR is worth and how it gets valued inside the organization.

What this means for agencies and writers

The bar for external communications partners is rising alongside all of this. Journalists can spot an AI-generated pitch almost instantly and so can savvy clients. The agencies and writers that will thrive in this environment aren't the ones that use AI to produce more output faster. They're the ones that use it to show up better prepared, more informed, and further ahead of the client's needs than was previously possible.

That means deeper industry expertise, not shallower. More genuine media relationships, not more automated outreach. And a willingness to walk in the client's shoes – to understand the business well enough to counsel it, not just service it.

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6. KPIs and Resources Worth Bookmarking

At some point, every marketing leader has to answer the same question from the board: how do we know it's working? When the goal is something as intangible as trust and credibility, that question gets harder, but it doesn't get less important.

KPIs for credibility

Christine Royston framed it well: traditional performance metrics still matter. ROI, pipeline contribution, hitting and exceeding targets – none of that goes away. But measuring credibility requires a broader lens on top of that foundation.

The two layers work together, not in opposition:

Performance metrics — the numbers that prove marketing is contributing to the business:

• Revenue influence and pipeline contribution
• Conversion rates across the funnel
• Campaign ROI and efficiency gains

Trust and credibility metrics — the indicators that tell you whether belief is actually building:

• Brand perception — are audiences seeing you the way you intend?
• Customer engagement quality — not just clicks, but depth of interaction, return visits, time spent
• Thought leadership impact — are your ideas being cited, shared, and built upon by others?
• Share of voice — how much of the relevant conversation are you driving, and with what authority?
• Inbound executive requests — are journalists, analysts, and event organizers coming to you?
• Third-party references — independent validation from analysts, press, and peers

As Christine put it, the breadth of how you measure trust matters, but ultimately, it all needs to be reflected back in the performance metrics. Credibility that doesn't eventually show up in the business numbers is hard to defend. The goal is to connect the two: show how brand trust translates to pipeline, retention, and revenue over time.

Resources worth bookmarking

The session surfaced a handful of resources that the speakers and attendees found genuinely useful — not a reading list for its own sake, but tools and references that directly support the themes covered in this conversation.

On trust and AI:

• Is AI Smarter Than Humans? — the Wall Street Journal piece Liza referenced, exploring where Human+AI performance actually outpaces both humans and AI working alone.
• AI Has Made Me More Human — Liza Adams' own piece on how AI, used well, can deepen rather than diminish human thinking and creativity.

On practical AI use:

• NotebookLM — Google's tool for turning long documents into podcast-style audio summaries, debates, and discussions. Liza's team uses it regularly for content repurposing and synthesis.
• AI Content Pressure-Test Tool — a practical tool shared in the session for stress-testing AI-generated content before it goes out.
• Google AI Fundamentals Certification — a solid starting point for teams looking to build foundational AI literacy across marketing functions.

For staying current:

• MAICON AI Conference + CMO Summit — October 13–15 in Cleveland. Recommended by Liza Adams as a strong gathering for marketing leaders navigating the AI transition.

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Join the Mavuus Community 

The future of marketing leadership is constantly changing, driven by new economic pressures, AI capabilities, and C-suite expectations. Staying ahead requires a commitment to continuous learning and peer support. 

Mavuus is a confidential community built for senior marketing leaders (CMOs, Heads of Marketing, VPs) to share insights, solve complex problems, and engage with top experts. Our mission is to empower leaders through shared intelligence. 

If you are a senior marketing leader looking to future-proof your career and connect with the best in the industry, we invite you to explore the Mavuus community today.