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I am sure you have seen this sentiment over the last few years, and I see this mistake all the time. Companies pouring millions into AI initiatives, hiring data teams, upgrading infrastructure, and running endless strategy workshops all in pursuit of\u00a0\u201cAI readiness.\u201d<\/em>\u00a0They get consultants in, build maturity models, and benchmark themselves against competitors. Yet, months, nay, sometimes years later, they have little to show for it.<\/p>\n Sound familiar?<\/p>\n No real impact. No measurable results. Just a growing sense of frustration.<\/p>\n Here\u2019s the hard truth and what I\u2019ve observed and learned over the last 25 years of my career. Two-word terms such as \u201cBusiness Readiness\u201d (yeah, remember those business readiness surveys and statements), naval gazing about how mature a company is, and endless questionnaires popping up! Here’s the hard truth:<\/p>\n \u201cAI readiness is a myth.\u201d<\/em><\/p>\n It\u2019s not something you achieve before starting, it\u2019s something you build as you go, driven by real business problems. Oh, I like that! But here\u2019s the thing. Countless organizations are stuck in this \u201creadiness\u201d loop, convinced that if they just tick the right boxes, AI will somehow transform their business, and they will all be ready!<\/p>\n It won\u2019t, and it never will, unless they shift their approach.<\/p>\n Perhaps you are already feeling the pain of this approach, even if you haven\u2019t named it yet.<\/p>\n If these sound familiar, believe me you are not alone. This is a widespread problem, and it has clear underlying causes.<\/p>\n You can blame anyone you want. But the real reason it fails isn\u2019t anyone else but you and your team. I know that\u2019s not what you want to hear because you want to put the blame at someone else\u2019s door, maybe the consultant or the contractor or the article you read last week or a motivational speaker or a book that you read.<\/p>\n No, don\u2019t go there as these are just excuses that are spectacularly flawed! We have seen this cycle repeat across industries because and through new trends, etc., because of a few common but flawed assumptions.<\/p>\n It\u2019s like trying to build a Formula 1 car without knowing what race you’re entering. You can have all the components, but if you don\u2019t know the track, the weather conditions, or even the driver, the car is completely useless.<\/p>\n I\u2019m all for asking the right questions, in fact in my early career in strategy it was all about asking the right questions. Maybe, we have lost that art, and I think the companies that succeed with AI don\u2019t ask, \u201cAre we AI-ready?\u201d Instead, they ask:<\/p>\n This shouldn\u2019t be a massive shift and one that is deeply profound as if you have just worked out the theory of black holes. It just means that AI stops being a theoretical exercise and becomes a focus and practical tool for value creation. It forces companies to move beyond endless discussions about maturity models and instead focus on the\u00a0real outcomes and results they need.<\/em><\/p>\n When we work with clients, we don\u2019t start by asking how mature their data is or whether they have the perfect AI governance framework in place. We start by identifying where AI can deliver measurable impact. Or is that just too simplistic for you? It’s not technical enough, or doesn\u2019t sound like you have to go out and buy a new platform! Nope don\u2019t do it, you don\u2019t need that extra tool. This is what you need to do:<\/p>\n This approach isn\u2019t theoretical; it\u2019s practical, and it works.<\/p>\n Take the case of a financial services firm we worked with. They had been stuck in \u201cAI readiness\u201d mode for over two years, investing in data platforms and hiring AI experts but failing to move beyond strategy discussions.<\/p>\n We flipped their approach. Instead of debating their AI maturity, we focused on a specific business problem: customer churn. It\u2019s not sexy, but, it\u2019s an area where they were having big problems.<\/p>\n We built a churn prediction model that integrated directly into their customer service workflows. It didn\u2019t just spit out insights, it gave clear, actionable recommendations to retention teams, telling them which customers to focus on and what intervention would work best.<\/p>\n The result?<\/p>\n No abstract AI strategy. No endless discussions about readiness. Just a direct impact on the business.<\/p>\n Why is this important? It helps behaviour change and people shift away from the \u201cAI readiness\u201d mindset. Readiness in my vocabulary is an ugly term that has been used for centuries to sell people nothing but rubbish that is typically consigned to the financial bin! If you do it right and get out of the readiness mindset, you can have these results that we have seen time and time again:<\/p>\n AI is not something you \u201cget ready\u201d for. It\u2019s something you deploy where it matters most in your business.<\/p>\n So, stop asking if you\u2019re AI-ready. Start asking how AI can drive real business impact. That\u2019s the only question that counts!<\/p>\n","protected":false},"excerpt":{"rendered":" The Wrong Starting Point I am sure you have seen this sentiment over the last few years, and I see this mistake all the time. Companies pouring millions into AI initiatives, hiring data teams, upgrading infrastructure, and running endless strategy workshops all in pursuit of\u00a0\u201cAI readiness.\u201d\u00a0They get consultants in, build maturity models, and benchmark themselves […]<\/p>\n","protected":false},"author":546,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[96],"tags":[],"acf":[],"yoast_head":"\nThe Symptoms That You Will Recognize<\/strong><\/h4>\n
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But Why Does This Keep Happening<\/strong><\/h4>\n
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The Shift From Readiness to Impact<\/strong><\/h4>\n
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How This Can Be Fixed<\/strong><\/h4>\n
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This Works in Practice<\/strong><\/h4>\n
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The Results of Shifting the Mindset<\/strong><\/h4>\n
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