Navigating Brand Visibility Trust in the AI Era

AI Insiders explores how AI is changing brand visibility, trust, differentiation, and human-centered marketing.

In this episode, host David Berkowitz speaks with Julia Kolodkina, founder of a marketing and branding company and a creative women’s entrepreneurship community builder in New York. Julia shares how her work with founders, brands, professors, and AI builders has shaped her view of marketing in an era where people increasingly use large language models to discover, evaluate, and choose products.

The conversation focuses on AI visibility, brand differentiation, trust in machines versus humans, human-in-the-loop marketing, personalization, creative storytelling, data ethics, and how brands can build consistent narratives that work for both people and AI systems.

Key moments

[00:05] Who is Julia Kolodkina and what does she do in AI, branding, and community building?

Julia Kolodkina is a marketing and branding founder who also builds a creative women’s entrepreneurship community in New York. She works with brands and founders while hosting events with companies such as Shopify and UBS, where participants discuss AI, entrepreneurship, and the future of humanity.

David Berkowitz introduces Julia as a community builder and branding expert who is thinking deeply about “what happens to humanity when everything becomes intelligent.” Julia explains that her perspective comes from working with clients, building community, speaking with professors, and spending time around founders who are actively building with AI.

Her work sits at the intersection of brand strategy, AI visibility, entrepreneurship, and human connection. The conversation uses that background to explore how marketers should adapt when both humans and machines influence discovery, trust, and purchasing decisions.

[01:56] Why do brands need AI visibility in the era of large language models?

Julia Kolodkina explains that brands need AI visibility because customers increasingly ask tools like ChatGPT, Claude, and other LLMs for product and service recommendations. If a brand is not visible or understandable to those AI systems, potential customers may never discover it.

Julia says a major cultural shift is underway: people used to trust other people, but after years of aggressive advertising and sales behavior, many now trust machines for answers. This creates a new marketing reality where brands must communicate not only to human audiences but also to AI systems that summarize, recommend, and rank options.

According to Julia, marketers now have “two different audiences”: humans and machines. Humans still respond to emotional narratives, while machines need clear, consistent, rational, and technically legible information. Her AI visibility work focuses on prompts, messaging, communication strategy, and consistent narratives that help brands become discoverable inside large language models.

[04:54] Why is brand differentiation harder in the AI era?

Julia Kolodkina says brand differentiation is harder in the AI era because many companies are using the same AI-generated language, making their messaging nearly interchangeable. She argues that brands need stronger points of view, more individuality, and more original language to stand out.

When David Berkowitz asks how to build something differentiated in a crowded AI visibility market, Julia says the current problem is a “lack of differentiation” and a “lack of point of view.” She observes that if someone reads the messaging from 10 companies and removes the logos, many of them sound the same.

Julia recommends that brands rediscover their own narrative, read more deeply, and move away from simply copying AI-generated language. She sees a growing need for thoughtful, provocative, human-centered brand language that creates emotional resonance instead of blending into the noise.

[06:35] Is AI replacing copywriters, or are human copywriters becoming important again?

Julia Kolodkina says many companies initially replaced copywriters with AI, but she believes human copywriting is becoming important again because audiences can recognize and ignore generic AI-generated campaigns. Her own team brought copywriters back to create messaging that feels human, conscious, and trustworthy.

Julia shares that when ChatGPT became publicly available, she was working as director of brand strategy at a NASDAQ-traded company with 6,000 employees. The copywriter was the first person laid off because the company believed AI could produce messaging internally.

She now sees the opposite shift. Julia says people often do not resonate with campaigns written by AI, and they can quickly spot language that feels generic or untrustworthy. For her clients, she again uses human writers because she believes people relate most deeply to messaging created by other conscious humans.

[08:57] What is AI visibility, and how does it help brands get recommended by LLMs?

Julia Kolodkina defines AI visibility as the process of making a brand’s narrative, content, keywords, and positioning clear enough for LLMs to recognize and recommend it. The goal is for AI systems to surface the brand when users ask relevant questions about a category, product, or service.

Julia says the need for AI visibility emerged because customers were using ChatGPT, Claude, and similar tools to research companies. If those tools could not find or understand a client’s product based on available messaging, keywords, content, and campaigns, the brand was effectively invisible.

Her process starts by building or clarifying the brand narrative, then creating an omnichannel communication approach so that information about the company is consistent across touchpoints. Julia says the best AI visibility strategy combines differentiation, consistency, and recognizable keywords so an AI system can place the brand among the top options in its category.

[10:39] How do critical thinking and metacognition improve brand positioning for AI search?

Julia Kolodkina says critical thinking helps founders understand their brand more clearly, while metacognition helps them question how they think about the brand. Together, these skills help uncover differentiated messaging that can be expressed consistently across channels and recognized by AI systems.

Julia explains that inconsistent information is one of the biggest reasons AI may fail to recommend a company. Growing companies often change products, positioning, and messaging over time, leaving disconnected signals across websites, social media, campaigns, and public content.

Her team looks strategically at whether a company’s messaging is connected, whether different people are sharing information according to the same strategy, and whether the brand’s current positioning still matches what is publicly available. This consistency matters for both human understanding and LLM-based recommendation.

[12:19] Which LLMs should brands optimize for first?

Julia Kolodkina says brands should optimize for the LLMs and AI tools their specific audience actually uses. There is no single best model for every company, because AI tool preference varies by audience behavior, just as social media channel preference does.

Julia compares LLM selection to choosing between TikTok, Facebook, Instagram, or other marketing channels. Some customers may prefer ChatGPT because they started using it early and like the interface. Others may prefer Claude because they see it as more professional or better suited to certain tasks.

Her recommendation is to research the target audience’s behavior and determine which LLMs, tools, and channels they use. Brands should then prioritize AI visibility efforts around those systems rather than assuming every audience searches in the same place.

[13:31] How should marketers combine data, interviews, and personalization in AI-era campaigns?

Julia Kolodkina says marketers should combine quantitative data with deep interviews because data shows patterns, but conversations reveal why people make decisions. She believes many marketers have access to large amounts of data but do not always interpret it deeply enough.

Julia points to data from websites, social media, performance campaigns, and platforms as useful sources for understanding customers. However, she stresses that marketers must learn how to analyze gaps, patterns, and unexpected behavior instead of simply collecting dashboards.

She also highlights the rise of situational personalization. For example, if a marketer knows someone is online at 5 a.m., that information might shape recommendations for morning routines, supplements, or courses. Julia sees personalization as a huge opportunity, but she cautions marketers not to manipulate people and urges a shift toward purpose, meaning, and responsible use of customer data.

[17:32] Should brands focus on organic reputation or paid performance campaigns?

Julia Kolodkina says brands should use both organic reputation building and paid performance campaigns, but they should not rely only on paid media. She believes long-term brand growth depends on organic resonance, reputation, point of view, and community, while paid campaigns can support specific goals.

Julia distinguishes between short-term product pushes and strategic brand building. If a company simply wants to sell something quickly, a performance campaign may work. But for companies playing a longer game, she argues that brand strategy, organic growth, and audience relationships are essential.

She says paid media can buy attention, but organic brand building creates trust and durability. Social media gives brands the ability to broadcast a narrative and build relationships quickly, but Julia believes the strongest approach combines paid campaigns with reputation, organic engagement, and consistent storytelling.

[20:09] How can brands differentiate when everyone has access to the same AI tools?

Julia Kolodkina says brands can differentiate by developing a clear, memorable, and sometimes provocative narrative that reflects the founder’s personality and the company’s point of view. Tools may be widely available, but brand individuality cannot be fully delegated to AI.

Julia argues that consumers increasingly want authenticity, process, imperfection, and a sense of belonging. People buy brands not only for utility, but also because brands help them express identity and feel connected to something.

Her team uses deep interviews with founders and teams, often lasting around five hours, to uncover the perspective behind the company. Julia says “building a brand is like having sex” because it cannot be fully delegated; the founder’s personality, individuality, and energy need to be present in the process. After that, the team can scale messaging and analyze what resonates.

[23:19] Do brands need different writers for humans and machines?

Julia Kolodkina says brands may need different writing strengths for different tasks, but the most important work is defining the brand narrative, messaging, and differentiation first. Once the story is clear, AI and technical writers can help translate that narrative into more structured formats for machines or business needs.

Julia explains that her team includes a copywriter who reads fiction and is strong at storytelling. That writer brings vocabulary, emotion, and narrative angles that Julia believes are essential for human resonance. She also works with more technical writers for tasks such as investor decks, where the language needs to be direct and less story-driven.

Her larger point is that intelligence alone is no longer a superpower because AI can help turn ideas into technical messages. The harder and more valuable work is creating a story that makes people curious, emotionally engaged, and willing to participate.

[26:20] What concerns do creative founders have about AI and information overload?

Julia Kolodkina says many creative founders and ambitious entrepreneurs are overwhelmed by too much information, too many tools, and constant overthinking. She believes marketers should respect people’s attention and only publish work that is thoughtful enough to deserve the audience’s time.

Julia describes working with founders who are building every day and facing continuous pressure from noise, content, and AI-generated information. In response, she tells her team that if they would not personally invest serious money behind a message or post, they should not send it to a client.

For Julia, the antidote to AI-driven noise is conscious, intentional communication. She believes people can feel when something is thoughtfully created and that this human feeling still differentiates human-made work from automated content.

[29:26] How should brands handle customers who trust AI and customers who strongly distrust AI?

Julia Kolodkina says brands need balance: they can use AI for information, automation, and visibility, but they should keep humans in the loop and question AI-generated answers, data, and sources. This matters because some customers trust AI recommendations while others strongly distrust or even resent AI.

Chris raises the concern that while some people increasingly trust AI for answers, many others do not trust AI at all. He notes that in markets such as San Francisco, some people visibly reject AI technologies such as Waymo, and that brands using AI may face backlash from anti-AI customers.

Julia responds that context matters. People may accept AI for low-stakes recommendations, such as choosing a lipstick, because they want a quick answer and do not want to overthink. But for more personal or sensitive decisions, brands need to be more careful. She recommends questioning AI outputs, checking sources, involving humans, and recognizing that human culture, feeling, and physical experience remain central to brand trust.

[35:01] How can AI memory and personalization become risky for marketing and creativity?

Julia Kolodkina says AI memory and personalization become risky when brands use personal patterns to manipulate people’s fears, habits, or vulnerabilities. AI can help with self-reflection, but the same data can also be used to predict behavior and pressure people into buying.

Chris raises a concern that AI systems with memory may overuse past preferences when generating future creative work. He argues that creative expression does not always need to be constrained by previous behavior, and that users must understand how AI memory shapes outputs.

Julia agrees and expands the concern to marketing ethics. She says AI may know personal details, patterns, and insecurities, such as concerns about hair loss, and marketers could use that knowledge to design highly persuasive campaigns. She sees data safety, personal information, and responsible personalization as major questions for the next several years.

[41:09] How does Julia Kolodkina design brand context for campaigns and AI agents?

Julia Kolodkina designs brand context by starting with the individuality behind the company, then combining founder interviews, industry research, cultural analysis, and testing with real people. Her goal is to create a context and narrative that can guide campaigns, messaging, and brand decisions.

Julia says her team begins with long in-person interviews to understand how the founder thinks, why the product exists, and what energy or state of mind sits behind the brand. They then study what is happening in the same field across markets such as China and Germany, as well as comparable industries that may offer useful ideas.

She describes borrowing ideas “like an artist” from different industries and integrating them into the client’s main narrative. Her team then tests the context through performance campaigns, interviews, events, or other feedback loops to see whether real people respond to the brand direction.

[43:31] How should teams organize brand context and maintain consistency when using AI tools?

Julia Kolodkina says teams should keep brand strategy, messaging, and context in shared systems so everyone can access the same source of truth. Her team uses practical tools such as Google Drive, Slack, Figma, client folders, cloud access, and Claude to maintain consistency.

Julia does not believe brand strategy needs to be a 100-page document. She says strategy should be simple enough to guide decisions clearly, sometimes even reducible to one strong sentence.

For ongoing work, her team keeps shared files and uses Claude so team members and clients can ask questions, add information, and check whether new content still connects to the original strategy. This helps prevent the common problem of drifting away from the agreed narrative as campaigns and tactics evolve.

[46:00] Should brands allow AI agents to publish marketing content autonomously?

Julia Kolodkina says brands can automate many marketing tasks, but she still recommends keeping a human in the loop. Her team uses AI and automation for clients, including performance campaigns, but humans define the narrative, review the output, and ensure the work remains aligned with the brand.

Chris asks whether Julia would ever let a brand or marketing agent publish autonomously on behalf of a company. Julia responds that while automation is useful, brand messaging still needs human oversight.

Her position is not anti-AI. She supports using AI’s benefits for efficiency and execution, but she believes humans should create and guard the strategy, narrative, and final quality of the brand’s public communication.

[46:44] How can AI-generated creative and UGC creators work together in campaigns?

Julia Kolodkina says AI-generated creative and UGC creators can work well together when brands use both as part of one campaign. AI can create visuals and content variations, while real human creators add authenticity and human trust.

Julia explains that for technology companies without physical products, AI can help create campaign content that would otherwise be difficult to visualize. For e-commerce brands with physical products, AI can place products into different situations and test how those creative concepts perform.

She says some AI-generated campaigns perform well, but her team often combines them with UGC creators. In her experience, the mix of real human content and polished AI-generated creative can produce strong campaign results.

[47:49] Which marketing channels should brands use for e-commerce, reputation, and authority?

Julia Kolodkina says channel selection depends on the client’s goal, audience, and product. E-commerce brands may use Meta, Instagram, or TikTok for sales, while reputation-focused or B2B luxury brands may need authority-building assets such as Wikipedia.

When asked which channels her team buys, Julia says they buy whatever makes sense for the client. If a brand is selling a consumer product to a younger audience, TikTok may be appropriate. If the goal is e-commerce sales, Instagram and Meta may be useful.

For other clients, immediate sales are not the only goal. Julia gives the example of recommending Wikipedia for a client not because it would drive sales that day, but because it could support authority and reputation. Her broader approach is holistic: combine paid advertising, organic community placement, UGC, audience insights, and brand-building so the company is not dependent only on performance media.