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Comms Teams Build For Algorithms First, Then Win On Human Trust and Relevance
Oleksandra Lytvynenko, Senior Public Relations Specialist at MacPaw, says that effective communications rely on aligning algorithmic interpretation with audience perception, carefully evaluating collaborators, and tracking outcomes to ensure messages land as intended.
Key Points
As AI shapes how brand content is surfaced and summarized, communicators risk reaching audiences without earning their trust. Visibility alone no longer guarantees credibility or influence.
Oleksandra Lytvynenko, Senior Public Relations Specialist at MacPaw, says that success depends on a dual-layer approach, balancing machine-readable narratives with human-centered engagement.
Implementing this strategy requires structured storytelling for AI interpretation, careful vetting of collaborators, and continuous evaluation of communication resonance and algorithmic performance.
AI can surface, summarize, and recommend, but it cannot replace credibility, context, or human judgment.
Oleksandra Lytvynenko
Communications is now a dual-layer discipline: one layer shapes how AI surfaces brand narratives, the other ensures audiences perceive them as credible. Today, audiences encounter synthesized responses that decide which brands appear, how they’re framed, and whether they’re recommended. AI drives visibility, but algorithmic discovery does not guarantee trust. PR’s core role remains rooted in integrity, context, and human-centered assessment.
Oleksandra Lytvynenko is a Senior Public Relations Specialist at MacPaw, a Mac app development company. Her award-winning campaigns have been recognized by AMEC, the UN Global Compact, and Reuters. She helps organizations and projects achieve tangible results through brand communications, navigating the intersection of reliability and AI-curated visibility.
"AI is fundamentally changing how people find information, moving from search to answer-driven discovery, but discovery is not the same as trust. AI can surface, summarize, and recommend, but it cannot replace credibility, context, or human judgment," Lytvynenko says. The distinction between what AI reveals and how people perceive it is at the heart of her “two-layer” approach, where success depends on making narratives both machine-readable and resonate with audiences.
Two-track mind: "Build narratives that are readable for LLMs. From my professional perspective, I have to operate on two layers. One is the machine-readable layer, so AI can understand and surface brand information. The other is the human trust layer, where people evaluate and believe you. Both are essential; it’s the duality of my work," Lytvynenko emphasizes. This framework guides every campaign, partnering with creators whose influence drives meaningful audience engagement.
Buzz whisperers: "We have to build relations with creators who have an audience that trusts their perceptions. Previously, we collaborated with creators on campaigns. Now we build relationships so they don’t just distribute content; they shape perception, credibility, and cultural relevance," she says. While these connections influence how messages are received, expert evaluation remains the decisive factor in high-stakes communications.
"We live in the AI era, but we are still humans and AI won’t substitute us. Especially in crisis communications or complex cases, AI wouldn’t solve it as quickly as a person. We still need the people-to-people perspective and must focus on how our communication resonates with people," Lytvynenko explains. Even as AI shapes the reach and framing of content, real-world insight remains the lens through which impact and credibility are judged, ensuring that every partnership reflects the brand's principles.
Reputation roulette: "Before we start collaborations with any creator, we do our own research. We check everything about the person. We need to do reputational checks with every creator, with every brand we work with. We don’t collaborate with someone whose position or personal opinion differs from what we are building here," she adds. Once trust is established and partnerships meet standards, the team evaluates results, combining traditional metrics with new AI-driven insights.
Data mojo: Communicators must actively monitor how AI presents their brand, interpreting outputs while maintaining people-centered reasoning. "We see a creator as a partner, and that’s how we measure, track, and improve it: by numbers and by narratives themselves itself, such as brand mentions, key messages, message penetration. There’s also an emerging sphere of AI measurements in how LLM models give information about your brand. This requires understanding the algorithm and using new tools like AI for PR courses or becoming a prompt engineer," says Lytvynenko. Bringing together data, AI insights, and professional acumen allows organizations to tell stories that resonate with viewers and algorithms.
Companies that skillfully balance AI-readability with human assurance, ensuring information is both discoverable and credible, are poised to lead the next era of communications. "Think about how AI systems read and present the brand, while making sure communication resonates with people. If one side fails, the whole system breaks. Visibility without trust is meaningless, and trust without visibility is invisible," Lytvynenko concludes.
