This article was based on the interview with Linnworks CMO Hilary Smith on the manual work hiding inside “automated” operations by Greg Kihlström, AI and MarTech keynote speaker for The Agile Brand with Greg Kihlström podcast. Listen to the original episode here:
Most of us in marketing leadership have spent the better part of two years discussing, debating, and deploying AI in its most visible forms. We’re using it to draft copy, segment audiences, personalize campaigns, and power the ever-present chatbot in the corner of the screen. We believe we’re at the cutting edge. Yet, while we’ve been polishing the customer-facing chrome, a subtle, more consequential shift has been happening in the engine room of commerce. For all the talk of our “automated” marketing stacks and sales funnels, a surprising amount of manual work continues to pile up in the background, particularly in the unglamorous but essential domains of inventory, order management, and fulfillment.
This hidden labor is more than an operational inefficiency; it’s a silent brand killer. Every time a marketing campaign succeeds a little too well, it stress-tests an operational model that is often far more manual than we care to admit. The resulting stock-outs, shipping errors, and fulfillment delays directly undermine the brand promise we spend millions to build. I recently sat down with Hilary Smith, the CMO of Linnworks, whose career at the intersection of e-commerce, data, and automation provides a uniquely clear-eyed view of this challenge. Her perspective is a necessary one for any marketing leader who wants to ensure the promises they make in their campaigns can actually be kept when a customer clicks “buy.”
The Real Cost Center: Where Brand Promises Go to Die
As marketers, we are conditioned to focus on the top of the funnel—acquisition, conversion, and the creative that drives them. We build intricate customer journeys and obsess over brand sentiment. But the most memorable part of any journey is often the destination. When it comes to e-commerce, that destination is a package arriving on time, with the correct items inside. According to Smith, this final, critical stage is where even the most sophisticated brands are stumbling, and it’s the place where profitability and loyalty are most at risk.
“The really hard stuff and the stuff that keeps people up at night over their profit margins or over bad customer experiences is unfortunately when inventory is misaligned, you are stocking out where you shouldn’t, things get shipped to the wrong place, you mis-ship the wrong product to the… wrong customer. And you start to look at all of your operations and think that the only way to solve it is to hire more people. And that is a huge margin squeeze.”
This is a point that should resonate with every CMO. We can calculate the ROI of a campaign down to the penny, but that calculation becomes meaningless if an operational failure negates the lifetime value of a newly acquired customer. A stock-out on a heavily promoted product doesn’t just represent a lost sale; as Smith notes, it can permanently sever the relationship with a first-time buyer. The knee-jerk reaction for many organizations is to throw bodies at the problem, adding headcount to the warehouse to manage the increased volume. But this is a fundamentally unscalable model. It treats the symptom—an influx of orders—rather than the disease: a system that isn’t truly automated and can’t handle success. The real opportunity for AI, then, isn’t just in making our marketing slicker, but in making our operations smarter and more resilient.
Beyond Automation: Building Systems That See the Problem First
The term “automation” has become so broad as to be almost useless. We say a workflow is automated, but often that just means a series of scripts are running, requiring human oversight and frequent manual intervention when exceptions arise. Smith draws a sharp distinction between this kind of brittle, rules-based automation and a more intelligent, autonomous system. The goal isn’t just to automate tasks, but to build a system that can identify its own inefficiencies.
“We have a tool that launched earlier this year called Spotlight AI that actually highlights the things that you haven’t automated yet. So it will… scan for those all of the time and then say, ‘Hey… you keep doing the same thing manually over and over again. How about you stop doing that?’ And then give you the rule that you can build and implement yourself. So that it’s doing the work for you… It’s flagging where you’re not being productive, but it’s not taking the control away from you.”
This is a far more sophisticated application of AI than simply feeding prompts into a language model. It’s using AI as a diagnostic tool for the business itself. The system observes the patterns of human behavior—the constant manual adjustments, the repetitive exceptions handling—and surfaces them as opportunities for improvement. For marketing leaders, this is the operational equivalent of a session replay tool showing you where customers are getting stuck on your website. It provides actionable intelligence, allowing teams to build more robust and truly automated workflows without ceding the control necessary when dealing with physical inventory and logistics. It’s a shift from “if this, then that” to a system that asks, “Why does this keep happening, and how can we build a rule so it never happens again?”
The Foundation of Trust is Operational Consistency
In a world of multi-channel commerce, a brand is no longer defined by its website or its flagship store. It is the sum total of every interaction a customer has, whether they discover a product on TikTok, read reviews on a marketplace, or make a purchase on a DTC site. When the experience is inconsistent—when shipping is faster from one channel than another, or an item is in stock on the site but not the app—it creates a sense of fragmentation that erodes trust. Smith argues that the only way to present a unified brand front is to have a unified operational back-end.
“If you’re able to make that consistent across all of your channels and you’re able to make sure that, hey, if I’m selling through this channel, it’s gonna have a very similar delivery time and delivery experience, and have that consistency, that is… key for shoppers because it… helps increase that trust.”
This is where the CMO’s vision must connect directly with the COO’s reality. The brand promise of convenience and reliability is either upheld or broken by the systems managing inventory and fulfillment across every touchpoint. Customers don’t know or care that your marketplace operations are siloed from your direct-to-consumer warehouse; they only perceive the inconsistency. True omnichannel excellence isn’t just about marketing presence; it’s about operational integrity. Smith’s point is that technology should serve to unify these disparate channels, ensuring that inventory levels are accurate everywhere and that fulfillment logic can route an order from the most efficient location, regardless of where the customer placed it. This operational consistency is no longer a competitive advantage; it is the table stakes for building a modern, trusted brand.
Keeping the Human in the Loop, and at the Helm
With all this talk of automation and AI, it’s easy to assume the goal is to remove humans from the equation entirely. But Smith’s perspective, born from years of working with business owners, is more nuanced. The objective isn’t to replace human oversight but to elevate it. She points to the danger of relying on AI for tasks that require genuine human spirit and strategic insight, from brand voice to product strategy.
“And the more we tried to scale more of it with AI, the further it got from, like, the real human story. And so we ended up having to do it the old-fashioned way and saying, ‘We’re gonna sit down and we’re gonna listen to customer calls, and we are gonna interview every seller on our team and find out really what customers are facing every day, so that… we are getting the real lived human experience, not just the AI layer that’s been applied over that real human experience.’”
This is a crucial lesson. AI can replicate patterns, but it cannot replicate empathy or lived experience. The most valuable role for people in an increasingly automated world is not to perform the repetitive tasks of a machine, but to do the work a machine cannot: define the strategy, listen to the customer, understand the market, and imbue the brand with a soul. In operations, this means humans should be setting the rules, not manually processing every exception. The technology should handle the toil, freeing up teams to focus on building a more resilient, intelligent, and customer-centric system.
Ultimately, the conversation around operational AI is not a distraction from the customer experience; it is the very foundation of it. As Smith’s insights reveal, the path to scalable, profitable growth isn’t paved by hiring more people to pack boxes. It is paved with smarter systems that surface hidden manual work and turn operational data into a strategic asset. It’s about creating a business where success doesn’t break the system, but instead makes it stronger.
The future of marketing and technology is not about a battle between humans and machines. It’s about forging a partnership where technology absorbs the complexity and repetition, allowing us, the leaders, to focus on the deeply human work of strategy, creativity, and connection. The goal is to build systems that don’t force our teams or our customers to deal with frustrating, inhuman breakdowns. By turning our attention to the operational engine, we can finally ensure that the brand promise we so carefully craft in our marketing is the one we actually deliver.