AI Turns PR Research Into A Signal Engine For Stronger Earned Media

91% of B2B marketers increased their content volume in 2025, undoubtedly aided by AI. But when brands prioritize quantity over quality, and PR teams are using the same language models to build pitches and scale communications, they risk fading into the background. Teams are facing the pressure of building efficiencies that nurture scaling while striking the balance of maintaining their distinct voice.

Brett Pinto, Senior Manager of Communications and PR at the cloud-based marketing analytics platform AppsFlyer, is an expert at deftly navigating public relations in the AI boom. With a decade of experience ranging from the U.S. Senate to high-growth tech startups, he has built his reputation on traditional media relations. Now, he is focusing on using new tools to support originality rather than replacing it.

"If you’re just doing more volume through the same models, you’re accelerating toward sounding like everyone else. And that’s a dangerous place for comms to be," Pinto says. As more comms teams adopt the technology, content output is surging. But Pinto warns that companies leaning too heavily on generative models for external messaging risk blurring the authentic voice that gets them the earned media and eyeballs they work so hard to gain. "The more you scale up, the less the human element is touching it."

• Laundry over lyrics: To avoid lackluster output, Pinto has a clear framework for his communications team: leverage AI in the ways it can make life easier, while saving creative tasks for humans. He emphasizes that these guidelines apply strictly to his comms group, distinct from AppsFlyer's corporate AI policies. "I want to use AI to do my laundry and my household chores so I have more time to make music and make art and throw dinner parties," he says. He sees too many teams nowadays following this misguided logic, having AI help plan the dinner party while humans still do the grunt work. At AppsFlyer, he keeps strategy strictly human. His team uses automation to help prep creative via news roundups, but creating bigger-picture strategy documents and brainstorms is owned 90-plus percent of the way by comms professionals.

AI does allow the team to conduct research and a level of personalization they previously could not. By using AI tools to scan global regulatory news and identify adjacent market trends, Pinto’s group is turning what started as a U.S.-centric retail newsletter into regional editions across multiple markets. AI surfaces relevant legal and industry developments from regions he is less familiar with. Then, Pinto steps in to narrow, interpret, and write the final product. Without that oversight, he says, the result lacks the creative perspective that makes it worth reading.

• The algorithmic intern: "If I ask for five stories, two of them are actually relevant," he says. "AI is basically an intern for me sourcing stories. I'm still writing it, putting bullets on why it's important, and defining our takeaway." Using the technology like a junior researcher that does the preliminary work has its payoffs. Pinto is reducing what was previously a six-hour monthly project to about two hours. His team can then plug those AI-generated summaries into foundational tools like Cision, Muck Rack, or Meltwater while retaining full strategic authority.

• Catching the case study: Inside AppsFlyer, Pinto uses AI to help communications and customer teams spot PR angles that would otherwise stay buried in routine account conversations. His team uses internal AI databases and model context protocols to surface potential case studies and performance metrics, with strict privacy guardrails around sensitive customer information. “Internal AI databases help break down those walls with our customer teams, taking the heavy lifting out of asking a million questions,” Pinto says. “They help us identify hidden performance metrics during routine check-ins, and those are the details we can turn into stronger customer stories.”

Internal AI news trackers also keep core spokespeople current on adjacent industry verticals, supporting their narrative authority on stage and at conferences. AppsFlyer built its reputation in mobile measurement, but as the company expands into areas like CTV and digital out-of-home, the news trackers help the team stay current in less familiar territory. The tools also give mid-level employees more confidence to draft social media posts. When staff use AI as a writing companion that adapts to their own voice, Pinto sees a measurable uptick in higher-quality, employee-generated content. But he notes a potential brand risk emerges if multiple employees rely on identical prompts, which can result in near-identical posts that undermine audience trust in a brand.

• The copy-paste crutch: AI's ability to help in the writing process can sometimes slip into executive complacency. When spokespeople bypass the PR team and rely on ChatGPT for their talking points, it creates a missed opportunity for original thought leadership. To combat this, Pinto focuses on breaking down organizational silos. "As I've had conversations with comms leaders across the ecosystem, they mention that when asking spokespeople for their market observations, they're getting copy-pasted responses from ChatGPT," he says. "It's really important for comms leaders to break down the silos. With the silos broken down, you're able to actually understand, cut through the BS, and find what is actually valuable." Pinto uses internal AI intelligence-gathering to arm his team with data so they can have informed conversations with executives and surface genuine, firsthand observations.

Language models work by referencing existing patterns, which means building something truly innovative requires a human in the lead. Pinto says if teams understand that, they can leverage AI for what it's good at—research, summarizing, scanning—while leaving the strategizing and content creation to human experts. "If you want to differentiate against competitors or break into a new marketplace, you need new creative thinking, these predictive models are simply unable to do that. You need to be doing that ideation with the actual human members of your team," he says.