This article was based on the interview with Eugene Amigud, Chief Innovation Officer at Infios by Greg Kihlström, AI and MarTech keynote speaker for The Agile Brand with Greg Kihlström podcast. Listen to the original episode here:
It’s becoming difficult to attend a marketing conference or scroll through a professional feed without being inundated with declarations about how artificial intelligence (AI) is set to revolutionize, well, everything. While some of the fervor borders on the hyperbolic, the underlying shift is undeniable. For enterprise marketing leaders, the challenge isn’t in acknowledging that AI is important, but in cutting through the noise to understand where the real, tangible impact lies. It’s less about launching a novel generative AI campaign and more about re-architecting the fundamental ways we connect with and deliver value to customers. The conversation is moving from the front-end—the slick website interface or the clever chatbot—to the complex, often-unseen machinery of the business that actually makes and keeps the promises marketing puts into the world.
This is where the future of customer experience is being forged. We are entering an era where the brand is less defined by its advertising and more by its operational excellence. The consumer, now accustomed to near-instant gratification, has little patience for supply chain disruptions, delayed orders, or poor communication. The paradox we face is that as AI potentially atomizes the customer journey across infinite touchpoints, it also provides the tools for unprecedented levels of personalization and proactive service. The key, as we’ll explore, is understanding that the slickest marketing in the world is instantly undermined by a failed delivery. The supply chain is no longer a back-office cost center; it is a critical, customer-facing component of the brand itself.
The Explosion of Infinite Channels
For decades, marketers have obsessed over a relatively contained set of channels. We built our beautiful, branded websites, optimized our search rankings, and curated our social media presences. The goal was to draw the customer into our owned digital properties. According to Eugene Amigud, Chief Innovation Officer at Infios, that paradigm is rapidly becoming obsolete. The rise of conversational AI and integrated digital assistants means the point of purchase is detaching from the brand’s website and scattering across a limitless digital landscape.
“This AI will introduce almost an infinite number of channels because really I don’t need to go to the website to buy it anymore… I’ll just ask saying, ‘hey, what’s the…best recommended shirt out there?’ … And then I can say… ‘well, I’ll just buy it.’ And guess what? They already know my address. They have all the information… So again, going from… one channel to this infinite number of channels becomes pretty massive… if they’re not architected, if they’re not built correctly, that will become overwhelming really fast.”
This shift presents a profound strategic challenge. If customers are no longer visiting your “digital flagship,” how do you communicate brand value, differentiate your products, and build a relationship? The focus must pivot from attracting customers to a destination to distributing rich, accurate, and compelling product and brand information everywhere. This means ensuring that whatever AI agent a consumer is interacting with has access to the best possible data about your offerings. It becomes less about web design and more about structured data, content syndication, and API strategy. For leaders, the question changes from “How do we drive traffic?” to “How do we ensure our brand is represented accurately and persuasively at any potential point of transaction, wherever that may be?”
From Depersonalization to Proactive Personalization
The immediate fear that arises from this “infinite channel” world is one of depersonalization. If a customer is buying through a generic AI assistant, the connection to the brand feels tenuous at best. However, Amigud argues that this is a limited view. While the initial transaction may feel more abstract, the data and intelligence AI unlocks can create moments of service and connection that are far more powerful and personal than a generic marketing email. The opportunity lies in using data not just to sell, but to serve.
“In this… less personalized world, if you will, what you’re asking for, there’s actually an opportunity to get closer to the customer. If I know… that in this region, bad weather is coming and I know your address… I can be very kind of saying, because I know where you’re getting it and I know you’re getting it for your birthday, you should probably order in a different way because you will not get it on time. Because now through AI gives me access to all this information. So it actually can be very powerful.”
This is where the marketing and supply chain functions must become inextricably linked. A marketer’s promise of a delivery date is just words until operations makes it a reality. By using AI to fuse data streams—customer order history, real-time logistics information, weather patterns, local events—brands can move from a reactive to a proactive service model. Imagine a customer receiving a message that says, “We noticed a storm is forecast for your area and your package might be delayed by 8 hours. We see it’s a birthday gift, so we’ve proactively upgraded your shipping at no cost to ensure it arrives on time.” That single interaction does more to build brand loyalty and trust than a multi-million dollar ad campaign. It demonstrates that the brand understands the customer’s context and is actively working to ensure a successful outcome. This is the new frontier of personalization: operational empathy at scale.
The Shift to Use-Case Driven, Modular Innovation
For many enterprise leaders, the prospect of re-architecting systems to enable this kind of intelligence is daunting. It conjures images of massive, multi-year transformation projects that are expensive, disruptive, and often fail to deliver on their initial promise. The traditional approach of buying a monolithic piece of software to solve a broad problem is ill-suited for the pace of change we face today. Amigud advocates for a more agile, targeted approach rooted in specific business outcomes rather than technology for technology’s sake.
“I was talking to one customer and they said, ‘you know what, my revenue is coming 80-20. So 80% is from brick and mortar and 20% from digital. And my board told me that in three years, it has to be 50-50.’ … to me, that was kind of my… light went on. like, that’s exactly… how you should be thinking about it, right? It’s not about opening a warehouse or buying another 20% inventory, but it’s really kind of, okay, what’s your business need? And then you break this business need to individual functions.”
This function-driven methodology is a powerful antidote to digital transformation fatigue. Instead of a vague goal like “modernize our supply chain,” the objective becomes “increase our digital revenue share from 20% to 50%.” That clear business goal can then be broken down into smaller, manageable use cases: How do we improve online inventory visibility? How can we offer more accurate delivery promises on the product detail page? How can we optimize fulfillment from stores? Each of these problems can be addressed with a specific, often modular, technology solution that delivers value in months, not years. This approach empowers individual business functions and allows the organization to build momentum through a series of focused wins, rather than betting everything on a single, high-risk project. It also requires matching the right tool to the job—knowing when a sophisticated optimizer is needed versus a generative AI agent versus a machine learning forecast.
Summary
The integration of AI into the shopping experience is forcing a necessary and overdue convergence of marketing, commerce, and supply chain operations. The old silos, where marketing made promises and operations tried its best to keep them, are no longer viable. In a world of infinite channels and rising customer expectations, the reliability, speed, and transparency of your supply chain have become potent marketing tools. The ability to accurately promise a delivery date, proactively communicate a delay, and intelligently solve a customer’s problem before they are even aware of it is the new currency of brand loyalty.
For marketing leaders, this requires an expansion of our domain. We must become conversant in the language of logistics, inventory management, and fulfillment optimization. Our success is no longer measured solely by brand lift or conversion rates, but by the organization’s ability to deliver a seamless and trustworthy end-to-end experience. The path forward isn’t about chasing every new AI trend, but about adopting a purposeful, use-case-driven approach to innovation. By focusing on solving specific business and customer problems, we can leverage technology to build not just smarter systems, but a more resilient, responsive, and ultimately more human connection with our customers. In the end, the most powerful AI application is the one that allows you to simply and reliably keep your promise.
