Everyone’s an AI company now – Here’s the checklist before you join them
All of a sudden, every company is an AI company! People who, a year ago, would have mistaken the acronym ‘LLM’ to be another flavor of ice-cream claim to be developing foundation models. When you start scratching the surface, their responses would put ChatGPT’s hallucinations to shame.
I don’t entirely blame them. I saw the same behavior in the late 1990s, when every company claimed to be an Internet company by launching a static site with an office photo and an ‘About Us’ page. Thirty years later, plenty of those same companies are still finishing their digital transformation, which is the quiet warning in this story. The label changes faster than the substance does.
Here’s the CxO’s real dilemma, though, AI is at least 10x more transformational than the Internet was, and unlike the browser era, there’s no five-year runway to figure it out before competitors pull ahead. What are your use cases? What’s the ROI? Build in-house, buy, or augment? Which vendor, which tech stack, what happens to your data, what’s the legal exposure? That’s enough open questions to produce analysis-paralysis on its own.
My recommended starting checklist, distilled from what I’ve seen work is to start experimenting now, even with a small team. If you have no in-house use cases identified, bring in a mid-sized specialist firm rather than a big-name consultancy claiming thousands of ‘AI experts’ on staff, since scale rarely correlates with judgment and competence here. Keep your data and your models close. Fine-tune open-source models in your own environment before you hand confidential data to a black box you don’t control. Think model ensembles (e.g., MoE – Model of Experts), not one giant model doing everything, so you can swap components as better ones emerge. And put governance in place on day one, not as an afterthought once something goes wrong.
Call it the Four-Point AI Readiness Check – Use cases, data ownership, model architecture, governance. Skip any one of the four and you’re not behind on AI; you’re behind on the fundamentals that make AI safe to scale.
This article leaned toward GenAI vendor selection specifically, but the checklist holds regardless of where you are on the journey. If you’re staring at all four boxes and only one is checked, that’s worth a conversation before the budget gets spent twice.