> ## Content Index > Fetch the complete content index at: https://jonathancanales.com/llms.txt > Use this file to discover other available public pages before exploring further. # There's no such thing as an AI-ready culture: what exists instead (and is better) - URL: https://jonathancanales.com/en/ai-ready-culture/ - Published: 2026-10-12T14:00:34.000Z - Updated: 2026-10-22T16:18:45.000Z - Description: Picture it: licenses purchased, course completed, policy signed. "We're ready for AI now," you say. And the next week a new model comes out that makes half of what you prepared obsolete. - Author: Jonathan Canales - Tags: Strategy and decisions, #en There's no such thing as an AI-ready culture: what exists instead (and is better) 0:00 /444 1× [![Listen on Spotify](https://jonathancanales.com/content/images/2026/10/image-ebade917.jpg)](https://open.spotify.com/show/1RbZ5C2DI8VFR4RA6paicv?ref=jonathancanales.com) [Read in Spanish →](https://jonathancanales.com/cultura-lista-para-ia/) Picture it: licenses purchased, course completed, policy signed. "We're ready for AI now," you say. And the next week a new model comes out that makes half of what you prepared obsolete. If that sounds familiar, you're not alone: it's the trap of treating AI like an exam you pass once, when it behaves more like weather that keeps changing. A recent Harvard Business Review article, written by three Korn Ferry consultants, names this with an uncomfortable phrase: there's no such thing as an AI-ready culture. Their argument is simple. "Ready" implies a fixed destination, a point where you're done. And AI keeps moving the destination. ## The moving target The authors explain that they set out to define the profile of the "AI-ready culture": they reviewed organizational culture data, interviewed CHROs, and compared research on successful AI deployments. Their conclusion was the opposite of what they were looking for. What sets apart organizations that get real value from AI isn't being ready, it's being adaptable: the capacity to flex when strategy, technology, or work changes. ![Moving target with an arrow chasing it](https://jonathancanales.com/content/images/2026/10/hbr-d1-g.png) Careful: adaptable doesn't mean changing everything all the time. The authors warn about both edges: too much change produces cultural whiplash (people stop knowing what actually matters), and too little leaves the company unable to respond. The real skill is running today's business well while building tomorrow's, with the judgment to know which mode each moment calls for. Here's the data point that should keep you up at night: according to the Korn Ferry research they cite, the traits needed for transformation (speed, agility, action orientation) are among the least common in organizations today. We're wired to perform, not to transform. ## What this means for a business like yours If you run a small or mid-sized business, you might think this is a problem for corporations with thousands of employees. I read it the other way: it's your advantage. A big company takes months to change a norm; you can change it in one meeting. The bad news is the temptation is the same at small scale: buy the tool, run the course, declare "we're using AI now," and feel like the job is done. The article proposes five habits that do show up in organizations that adapt. Here's the summary, and each one gets its own post on this blog: - **Impact over activity.** Measure results, not gestures: not how many courses got finished, but what changed in the work. - **Experimentation over certainty.** Test small, learn fast, and use evidence to decide what grows, what changes, and what dies. - **Decision systems over decision heroes.** Get information to whoever is closest to the problem, with clear authority and accountability. - **Enterprise thinking over local optimization.** Let AI connect knowledge across areas instead of building new fiefdoms. - **Learning velocity over accumulated expertise.** When expertise expires faster, the winner is whoever learns fastest, not whoever knows the most. ## The hard part: performing and transforming at once The hardest part of this idea isn't understanding it, it's living it. Performing asks for stability: repeatable processes, few surprises, everything under control. Transforming asks for the opposite: test, break, adjust. A perform-only company squeezes the present until the present runs out; a transform-only company lives in permanent construction and never collects. The authors argue that adaptable organizations do both at the same time and, rarest of all, develop the judgment to know which mode each moment needs: there are seasons for tightening bolts and seasons for moving walls. In a small business that translates into something very concrete: AI can't live in a drawer labeled "projects" or in the hands of one enthusiastic person. If the tool depends on you remembering it exists, it's not a capability, it's a hobby. ## What this approach does NOT ask of you It doesn't ask for a master digital-transformation plan with a Gantt chart and a slide deck. It doesn't ask you to adopt every tool that launches. And it definitely doesn't ask you to declare victory. In fact, the suspicion runs the other way: the article closes by saying the advantage won't belong to organizations that declare themselves ready, but to those that build the muscle to keep getting ready. ## A distinction that organizes everything Before going further it helps to separate two words we usually mash together: digitizing and adapting. Digitizing is putting new tools on top of the same old processes; adapting is changing the processes when new tools make them obsolete. Most companies are doing the first and calling it the second. It's not bad faith: digitizing can be delegated to a vendor and adapting can't. Adapting requires leadership to decide what stops being done, and no software seller signs that off for you. ![Balance scale in equilibrium](https://jonathancanales.com/content/images/2026/10/hbr-d5-g.png) ## Where to start this week No consultants, no formal project. Three things: - Change the question. Where you today ask "is everyone using AI?", ask "what is AI doing for the work?". The first gets answered with screenshots; the second with results. - Pick ONE process and ask whoever runs it what they would try if there were no consequences for failing. The answer tells you two things: where there's an idea and how much psychological safety actually exists. - Check what you celebrate. If recognition goes to whoever follows the process, your culture already voted: it prefers activity. If it goes to whoever finds a better way, it voted for impact. ## Questions to ask yourself When was the last time my business changed a way of working because something better showed up, not because something broke? What weighs more on my team: doing today's work well or preparing tomorrow's? Is that the balance I want? If AI stops being news and becomes the floor everyone stands on, does my advantage still hold? ## The takeaway You're never going to arrive at "ready for AI," and that's fine: nobody is, because the target keeps moving. What you can build is a business that adjusts without breaking every time the target moves. That doesn't come with a license; it's trained like a habit. ![Takeout box](https://jonathancanales.com/content/images/2026/10/hbr-d8-g.png) Source: "There's No Such Thing as an AI-Ready Culture", Sarah Jensen Clayton, Michael Welch and Khoi Tu (Korn Ferry), Harvard Business Review, October 5, 2026\. [https://hbr.org/2026/10/theres-no-such-thing-as-an-ai-ready-culture](https://hbr.org/2026/10/theres-no-such-thing-as-an-ai-ready-culture?ref=jonathancanales.com)