If you run a modern DTC brand, you already know AI is no longer a nice-to-have. It is the new electricity, the secret sauce, the caffeine shot that keeps your growth curve awake. The question is not whether to embrace AI, but who should actually be steering this rocket ship. The contenders: Head of Data Science, Chief Digital Officer, or the Product roadmap wrangler who knows how to juggle business goals and data without breaking a sweat. Let’s examine the candidates.
Option One: The Head of Data Science
These folks are brilliant, no question. They can talk your ear off about model accuracy, clustering algorithms, and the merits of supervised learning. The problem? They often live in a world where business goals are optional background noise. Sure, your Head of Data Science can optimize a recommendation engine, but ask them to explain how that aligns with next quarter’s revenue targets or customer lifetime value, and you may get a shrug. It is not that they lack smarts. It is that they are wired for the technical puzzle, not the commercial scoreboard.
Option Two: The Chief Digital Officer
On paper, this feels right. The CDO sits at the crossroads of e-commerce, marketing tech, and store innovation. They already manage digital channels and have budgets that dwarf entire startups. But here’s the catch: they are generalists. Their world is full of vendor RFPs, platform migrations, and making sure the CMS does not explode on Black Friday. AI for them often means evaluating which SaaS tool to plug in rather than shaping an internal roadmap that weaves AI into the DNA of the company. Useful, yes. Owner of AI vision, not quite.
Option Three: The Product and Roadmap Owner
This is where it gets interesting. Someone who has lived inside e-commerce, speaks fluent data, and knows that “roadmap prioritization” is not just a buzzword but a survival skill. This person can translate boardroom goals into technical requirements that engineering teams can actually build. They understand the friction points in the customer journey and how AI can solve them. They can map personalization engines to retention strategies and forecast models to supply chain pain points. In other words, they are bilingual: fluent in both business and tech. That is a rare and dangerous superpower.
The Verdict
The Head of Data Science is too deep in the code. The Chief Digital Officer is too wide in scope. The Product-driven leader with data fluency hits the sweet spot. They can prioritize which AI initiatives actually move the needle, communicate clearly with engineers, and keep executives happy with measurable results. In DTC, where margins are thin and every customer interaction is a potential love story or breakup, you cannot afford to put AI in the wrong hands.
So, who owns AI? Not the data nerd. Not the digital overlord. The winner is the translator, the bridge-builder, the roadmap obsessive who knows both how to measure KPIs and how to make them happen. In short: Product owns AI. Everyone else can send their complaints to customer service.
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