Strategic thinking about AI adoption and implementation
Name your top five marketing tools. Now name the metric each one feeds. If most of those metrics live inside a single function — paid, content, email — your AI is succeeding at the wrong job. The question isn't
AI accelerates whatever it's handed. A fragmented stack doesn't become unified by running faster — it becomes a faster-moving version of the same problem.
We just built the fix for a contract furniture manufacturer running three brands. 610 products. 4,342 digital assets. Spec sheets, price sheets, and proposals that generate themselves from the record instead of being maintained by hand. Role-gated pricing. Automated publishing to the storefront. Live in production, not a pilot. AI did a lot of that work, and I want to be precise about which part, because the hype in this space is out of control. AI did the extraction, the normalization, the reconciliation, the code. It did not decide what a product family means for that business, or who's allowed to see cost, or how discounts work in a channel with reps, dealers, and specifiers. AI compressed the labor. It did not make the decisions. I wrote up the whole build — seven steps, in order, with the reasoning attached. It's not a pitch. It's what we actually did.
AI gave volume tools a faster engine. What they built was more sameness. Here's why presence and position are different purchases — and why the unit matters.
