Data Fluency is the New Credibility Standard as Audiences Learn to Question AI Content

Communications has long operated as a qualitative discipline, where proving ROI means gesturing at sentiment trends rather than pointing to hard numbers. That gap is narrowing. As AI-generated content floods newsfeeds and audiences grow skeptical, data is emerging as the most direct way for comms professionals to prove their work changes outcomes.

We spoke with Talan Tyminski, Senior Vice President at the award-winning PR firm The MACH 1 Group, who navigates this new reality in her work. She also serves on the City of Austin’s small business procurement committee, grounding her work in public accountability and results. For Tyminski, the playbook for navigating this new terrain hinges on a paradox: to survive the rise of machines, we need to become more human, not less.

"There's such a place for data being both quantitative and qualitative and having to work together, because those are how we can see the full picture of a story." With AI-driven misinformation and deepfake threats reshaping corporate risk, Tyminski argues that data is the essential proof layer separating credible communications from noise.

• Data counters AI slop: "When you're competing against AI slop, data is a way for you to back up what you're doing and really showcase the proof that things are changing or that what you're arguing is true," Tyminski says. She points to a project where her team mapped every Texas elected official's social media follows to identify the most influential reporters, turning that analysis into an effective targeting strategy.

• Human stories need data: "In a world where AI can create stories, we are going to trust the individual story less because we don't know what's true or what's not," she says. "Data is a way to back that up." For communications teams adapting to AI, a compelling anecdote is no longer enough on its own.

• Calling out robotic messaging: Tyminski sees growing backlash against content that sounds too polished, even when it comes from humans. As platforms increasingly reward authentic expression over AI-generated work, the stakes keep rising. "People are questioning that more, and comms has to adapt and become more human," she says. "We've built a whole industry around media training and exactly what you need to say, and now we need to allow for some of that vulnerability."

• Audit every tool: Tyminski, who has written about how communicators should approach AI, encourages her team to use it for organizing content and building outlines but draws a firm line at final output. "Allow AI to do some of the prep work, but then add the human on top of it," she says. Leadership clarity around AI guardrails is central to how her team operates. The Mach 1 Group evaluates every AI feature in its software, checking whether it contacts third parties or trains on client content. "Any AI that one of our tools starts using, we take the time to really investigate what that is doing," Tyminski says.

She points to the firm's work with Make Our Schools Safe, a nonprofit founded by the mother of a Parkland victim, as proof. "It is such a human-centric story about her daughter, about what happens in those moments when you are in a crisis, that the human touch tells that story so much better than AI ever could," Tyminski says. It is the kind of work where investing in human experiences pays off in ways that scale cannot. "What is the expertise that a comms firm brings? I think that is the specificity."

• Source credibility is under pressure from every direction: Looking ahead, Tyminski sees forces converging that will push data and verification further into the center of communications work. The rise of influencer journalists, AI-generated deepfakes, and fake news sites running reproduced content are accelerating demand for proof. "People are starting to dig in more to what is actually a good news source," she says. "They're giving those sources a little bit more credit."

• Identity protection is an unresolved ethical question: Tyminski, who has explored the nuances of on-the-record participation, raises a concern the industry has barely addressed: how to protect people who share vulnerable stories in media. "How do we ask people to do media interviews and put themselves out there, but also make sure they have some protection?" she says. "I don't have an answer to that, but it's something I'm thinking about every time I'm asking someone to do an interview."

For communications teams working to earn trust in a content environment where authenticity is increasingly suspect, Tyminski's position is plain: start with the numbers, build the human story around them, and never let a machine write the ending.