In boardrooms and marketing departments across the e-commerce world, one question looms large: Will generative AI replace our carefully crafted brand messaging? It’s a bold new era – AI language models are everywhere, answering customer queries with fluent ease. Yet as tantalizing as it sounds, handing over your brand voice to a probabilistic algorithm is a perilous gamble. This op-ed argues that no matter how advanced AI becomes, businesses must retain deterministic control over their customer messaging. In e-commerce especially, where brand identity, positioning, and feature emphasis drive competitive advantage, losing that control could mean losing everything that differentiates you in the market.
Generative AI can be a powerful tool, but it is not your Chief Marketing Officer. In fact, AI is fast becoming a gatekeeper between brands and consumers – curating information and shaping perceptions in ways companies never directly sanctioned. This shift demands scrutiny. When an AI-driven engine answers a shopper’s question about your product, who decides what gets said? Without a firm hand on the wheel, you risk your brand’s voice being distorted, diluted, or drowned out entirely. The bottom line: AI cannot and will not replace the critical role of deterministic (i.e. controlled and intentional) messaging in business communication. Here’s why e-commerce executives and marketing leaders must take action now.
Every successful brand has a carefully honed message – a tone, a story, a promise – delivered consistently across channels. In traditional marketing, nothing about that is left to chance. This deterministic messaging is non-negotiable for businesses precisely because it guarantees that customers hear exactly what the brand intends them to hear. Nowhere is this more crucial than in e-commerce, where brand, positioning, and feature emphasis directly impact buying decisions.
Consider a scenario: A customer asks an AI assistant, “What makes YourBrand running shoes special?” If your marketing team has its way, the answer will hit all the key points – your patented cushioning technology, sustainability initiatives, community raves – in a tone that fits your brand personality. But if a generative AI decides the answer, you might get a generic one-liner about “comfortable shoes” or, worse, an omission of your biggest selling point. Businesses fundamentally require control over how their messaging is delivered to customers because no AI will care about your brand’s nuances as much as you do. As one marketing expert notes, marketers now realize LLM-based search models are “becoming the gatekeeper” to consumers, so ensuring an AI-generated summary of a brand aligns with its intended messaging is crucial. In other words, if you’re not dictating your brand’s story, the algorithm will – and it likely won’t get it right.
E-commerce leaders know that a mis-delivered message can be deadly. The wrong tone or omitted value proposition can confuse shoppers and erode trust. AI outputs that don’t match the brand voice can be jarring. Imagine a luxury fashion label described in frigid, technical terms, or a family-friendly brand summarized with edgy slang. These aren’t hypotheticals – early evidence shows AI systems, even when trained on a company’s own content, can produce inconsistent tone and off-brand style that “confuse customers and dilute the brand’s identity”. Unlike a human copywriter following guidelines, a probabilistic model has no inherent sense of your brand’s soul. That’s why deterministic control over messaging – having final say over wording, tone, and emphasis – remains absolutely essential. It’s the difference between brand stewardship and leaving your reputation to chance.
At the heart of the issue is a stark contrast in how messages are generated. Brand messaging is deliberate and authoritative; AI outputs are probabilistic and fluid. Large Language Models (LLMs) like ChatGPT generate text based on statistical patterns, not on strategic intent. They predict likely words and phrases to answer a query, which means the phrasing and focus can vary each time – a feature for creative tasks, perhaps, but a serious bug when you need consistency and authority.
To put it bluntly, probabilistic AI outputs are inherently unsuitable for authoritative brand communications. Why? Because by design, they are non-deterministic – their responses can differ from user to user, even given the same question. What one customer hears about your product in an AI-generated answer might be completely different from what another hears. No premier brand wants to play telephone with its value proposition. Consistency is the bedrock of brand trust, and these models simply don’t guarantee it.
There’s also the issue of accuracy and emphasis. A generative AI might summarize your product in a way that’s factually correct yet de-emphasizes the very feature you’re most proud of – or worse, it might introduce errors (so-called “hallucinations”) that mislead customers. In customer-facing contexts, this is a nightmare. Amazon’s own researchers recently flagged that LLMs “are prone to hallucinations… unfaithful to the source input,” posing significant risks in e-commerce applications. An AI might confidently assert a product has a feature it doesn’t, or omit a critical safety disclaimer. Authoritative brand messaging cannot tolerate such unpredictability. When your company speaks to a customer – whether in an ad, a product description, or a support chat – the words must be right every single time. Probabilistic outputs simply don’t offer that reliability.
Even setting aside outright inaccuracies, the subtler issue is tone and brand voice. Marketers spend years refining a brand’s voice to resonate with target audiences. LLMs have no innate loyalty to that voice. They can attempt to mimic it, but as many content teams have learned, AI-generated content often comes out “generic, inconsistent, and off-brand” without heavy guidance. It might take on a formal tone when your brand is casual and witty, or vice versa. It might use phrasing that doesn’t align with your values. These are not minor quibbles – for many businesses, tone and word choice are part of the product experience. Imagine Disney’s brand voice sounding clinical, or Apple’s copy losing its sleek confidence. Every deviation chips away at brand equity. This is why savvy companies are cautious about letting generative AI talk as the brand without strict controls. The authoritative voice of your brand must remain deterministic – crafted and approved by humans who understand the strategic intent – if you want it to remain authentic and effective.
So what happens if we don’t solve this, if businesses simply cede their messaging to AI systems without any structural way to influence the outcome? In a word: commoditization. Picture a future where every AI assistant gives roughly the same generic product answers, pulling from the same amalgam of internet data. In that world, brands blur together in the consumer’s mind. Without distinctive messaging shining through, all that’s left to differentiate products are bare facts like specs – and especially price. It becomes a race to the bottom, a hyper-commodified market where the lowest price wins because, from the customer’s viewpoint, everything else looks the same.
This isn’t hyperbole; it’s a real risk we’re already seeing. When AI search tools consolidate information from multiple sources, brand differentiation suffers and messaging gets blended into a commoditized category view. One recent analysis of AI-generated comparisons in B2B found that unique positioning statements were preserved in only ~12% of AI answers – the vast majority of brands were described in standardized, look-alike language. All those finely tuned differentiators and value-adds that companies invest in simply vanished from the conversation. The predictable result? Buyers start saying, “These options all sound the same. Who’s cheapest?” Indeed, sales teams reported hearing “you’re basically the same as Competitor X, right?” from prospects, and noticed conversations shifting to price over value. That is the commoditization nightmare in a nutshell.
Without a new structural architecture to regain control – think of something like an open web answer-and-question framework (OWAQA) designed for the AI era – this trend will only intensify. If marketing teams have no direct avenue to inject their optimized content into AI-driven answers, then by default the AI will reduce products to their lowest common denominators. Features that don’t get mentioned might as well not exist. Brand storytelling and emotional appeal won’t survive an algorithmic summary that’s blind to nuance. In such an environment, competing on price and basic specs is the only game left in town. For most businesses, that’s a losing game long-term. It squeezes margins, erodes brand loyalty, and favors giants who can win price wars (or no-name knockoffs who don’t care about brand at all). E-commerce would devolve into a hyper-commodified bazaar, where brand value dies in the AI’s bland, one-size-fits-all answer. This is the dystopia we must avoid.
How do we avoid that dystopia? By building a competitive arena within AI-driven platforms where marketing professionals can fight for their brand messaging – an “AI-era coliseum,” if you will. In the golden age of search engines, we had such arenas: SEO and SEM (search engine marketing) were battlegrounds where companies vied for visibility, testing and refining content to capture customer clicks. Marketers could optimize pages, bid on keywords, A/B test headlines – they had levers to pull. Crucially, they had data feedback (impressions, clicks, conversions) to know what messaging worked and iterate on it. This constant refining is how we match products with customer needs and narratives with receptive audiences. It’s how product-market fit is both found and communicated.
The AI-driven future needs an equivalent. Marketing teams need a structured way to actively participate in shaping AI answers, to create, test, and refine messaging that aligns with real user intent in real time. Think of it as the next generation of content optimization – call it Generative Answer Optimization, if you like. Without it, marketers are fighting blind against an opaque algorithmic tide. With it, however, we open up a new frontier of competition – one that can actually elevate customer experience by delivering better answers and preserve healthy competition among brands beyond just price.
What might this AI-era coliseum look like in practice? It could take many forms, but likely involves a combination of open standards, interfaces, and tools that let companies feed their best content into AI systems under defined rules. For instance, marketers might maintain structured answer files or verified data feeds that AI assistants consult when answering relevant questions (much like providing data for search snippets, but more dynamic). Early signs of this are emerging – consider the push for protocols like “LLMs.txt,” introduced in 2024 as a sort of robots.txt for AI to tell models which content to use and how. Forward-thinking brands and even government data portals have started publishing these AI-focused content roadmaps. The principle is to surface authoritative, marketer-curated information where generative AI looks first, rather than leaving it to scrape randomness from the web.
Additionally, an AI-era marketing arena would involve analytics on AI interactions. Marketers should be able to see, at least in aggregate, how often their content is being served up by AI assistants, what follow-up questions customers ask, and where the AI’s answers are satisfying or falling short. Some pioneers are already treating AI responses like a new SEO, tracking citations and tweaking content accordingly (for example, by ensuring their brand is mentioned on key platforms AIs draw from, or publishing unique research that AIs will cite). This kind of telemetry needs to become standard. With it, marketing teams can iterate – if Message A isn’t resonating in the AI, try Message B, measure the difference. If a competitor’s info keeps overshadowing yours in answers, adjust your content strategy to reclaim that ground. In essence, we need the ability to compete for the AI’s “attention” much like we competed for search rankings or ad impressions. That competition drives innovation in messaging and, ultimately, better informs consumers.
A true “AI coliseum” for marketers ensures that AI-driven customer engagement isn’t a spectator sport for brands. It brings them down to the arena floor to contend for hearts and minds, using words and ideas as their weapons. This isn’t just good for businesses – it keeps the marketplace of information vibrant. Consumers benefit from hearing diverse, well-crafted perspectives rather than a monotone synthesis. It maintains a healthy tension where companies strive to communicate superior value, not just drop prices.
The flip side of this vision – exclusion – should worry every business leader. If marketing teams are kept out of the AI loop, businesses are effectively gagging their own best storytellers. The people who know the product, the customers, and the brand DNA intimately would have no direct way to apply that expertise at the cutting edge of customer interaction. That’s a recipe for strategic oblivion.
First, consider differentiation and brand identity. As we’ve discussed, if you’re not actively ensuring your key differentiators are part of AI-driven conversations, they will fade away. An AI isn’t going to intuitively know that your phone’s camera quality is the result of years of R&D and is worth a premium – not unless you find a way to bake that into the info it has. Excluding marketers means excluding the very narratives and value propositions that set your product apart. The result is every offering looks alike. Businesses spend millions on branding and positioning; letting a black-box AI flatten those into oblivion is strategic malpractice.
Second, think about the feedback loop for product-market fit and messaging fit. Marketing is not just about broadcasting a message, it’s about listening and refining. Traditionally, marketers adjust their campaigns and even feedback insights to product teams based on customer reactions – what gets clicks, what features spark interest, what language converts. This iterative loop is crucial to finding and maintaining product-market fit. If AI intermediaries are answering most top-of-funnel inquiries and you have zero insight into those interactions, you’ve effectively lost a primary source of market feedback. It’s like flying blind. Perhaps customers keep asking an AI about a feature your product lacks – a savvy marketer who hears that could flag a new opportunity to the product team. But if you’re out of the loop, you miss it. Or conversely, maybe the AI consistently misinterprets your value prop and customers drop off; if you’re unaware, you can’t course-correct your messaging or educate the AI. Removing marketing from the equation kills the signal loop that organizations rely on to adapt offerings and messages to what the market actually wants. It’s no surprise that industry observers warn of “digital sameness” and customer fatigue if every AI interaction feels identical and no brand can inject creativity or unique flair. Without intervention, that’s where we’re headed.
Finally, disempowering marketing teams is demoralizing and shortsighted for the business itself. These are the people charged with crafting your brand’s future. Telling them their skills are now irrelevant because “the AI will handle it” not only stifles innovation, it also bets your entire brand on an outsider’s opaque system. Make no mistake, Big Tech would be perfectly happy to intermediate every customer relationship – and charge a toll for it, perhaps. If brands go along quietly, they’ll wake up to find they don’t own their audience anymore; the AI platforms do. That’s a strategic catastrophe. Businesses need their marketing and customer experience teams fully empowered to engage, experiment, and connect. It’s part of owning your destiny in the market. Exclude them from the AI interaction layer, and you’re essentially outsourcing your brand’s voice to a third party with its own agenda. No responsible leader should accept that.
The path forward is clear: Business and marketing leaders must demand a seat at the AI table. The rise of generative AI in customer interactions is not something to simply observe and accept; it’s something to shape proactively. That means demanding access – access to the mechanisms that decide what content is shown to customers, access to the data on how our content is used, and access to channels for inputting our own messaging. It means supporting open standards and architectures that make AI a participatory ecosystem rather than a walled garden. When an open alternative or protocol arises that gives you more control, back it – much like the early adopters of LLMs.txt who saw an opportunity to explicitly guide AI with curated content. These efforts only succeed if the industry rallies behind them.
Conversely, we must push back on black-box AI integrations that block participation. If a platform’s AI assistant won’t reveal how it sources answers or offer any way for businesses to contribute or correct information, that integration should be viewed with extreme caution. It might be convenient for users in the short run, but if it marginalizes brand input entirely, it’s eroding the long-term health of the marketplace. Remember, an AI that sidelines all branding essentially turns every product into a commodity in its eyes. As leaders, we should collectively question and challenge such models. Regulators and industry groups may also play a role – advocating for transparency, standards, and fair access in AI-driven markets (just as we’ve had to do with search engine practices over the years).
In the end, the future of e-commerce belongs to those who refuse to be silent. AI may change the channels and format of customer engagement, but it doesn’t change the fundamental truth that companies need to communicate their value persuasively and authentically. That won’t happen by accident. It will happen because we insist on it. So arm your marketing teams with the mandate to experiment with AI-era tools. Embrace emerging frameworks that let you inject your voice into AI answers. Educate your stakeholders that this is not a tech issue alone, but a strategic and economic imperative.
Generative AI is a marvel, but it is not a brand strategist – you are. It’s time to step into the arena and ensure that, even as algorithms evolve, the art of deliberate, differentiated messaging survives and thrives. For those bold enough to demand control and foster open collaboration with AI, the reward will be relevance and resilience in the next era of commerce. For those who sit back and let the black box dictate their story – well, they may find they no longer have a story anyone can distinguish from the rest. The call to action is clear: Fight for your voice, build the standards, and don’t let your brand become collateral damage in the age of AI. The coliseum is open; let the games begin, and may the best brand win.
