It used to stump me, but I’ve realised the answer is simple: I can show you people who’ve been innovative with AI before. It’s highly unlikely that they do exactly what you do in exactly your context. Your job is to interpret that inspiration and make it work for you.<\/p>\n
Enter The AI Play Matrix.<\/strong><\/p>\n We need to consider AI in the context of business problems and the solutions it provides. Some business problems are well understood, while many are emerging or unclear. Some AI capabilities are proven and understood, while many are experimental or in the process of evolution.<\/p>\n The bottom half is where actual AI innovation happens. But it’s also where most businesses struggle because that’s not how they’re designed to operate.<\/p>\n <\/p>\n There is a logical progression: ideas from AI Tinkering feed into AI Adaptive processes, which rapidly test concepts through prototyping until they’re ready to scale through planned delivery approaches.<\/p>\n The problem? Most organisations:<\/p>\n <\/p>\n Anything in the bottom half of the matrix can be genuinely difficult for large organisations. The procurement processes, governance models, investment processes, and risk frameworks are all designed under the assumption of certainty about the solution.<\/p>\n But if you want to do something genuinely innovative with AI rather than just following what everyone else is doing, you need to get comfortable operating in the bottom half.<\/p>\n So, what skills do you need for AI exploration instead of AI engineering? Let’s find out…<\/p>\n Now we’ve established that different AI approaches require different mindsets and methods, let’s unpack what that means in practice. Let’s examine the skills required for effective AI innovation.<\/p>\n <\/p>\n First, there’s a collective mindset that wants to connect.<\/strong><\/p>\n <\/p>\n Second, there’s an individual mindset that’s willing to experiment.<\/strong><\/p>\n <\/p>\n Finally, there are practical approaches that help you build.<\/strong><\/p>\n Is this a foolproof process for AI innovation success? No.<\/p>\n No such thing exists for AI (despite what the consultants tell you), so don’t fall for it.<\/p>\n But if you want to do something genuinely useful with AI rather than just following what everyone else is doing, these skills will help you operate effectively across all the different approaches you’ll need.<\/p>\n The alternative is staying stuck in the Plan quadrant forever, implementing slightly better versions of what your competitors already have.<\/p>\n Your choice.<\/p>\n","protected":false},"excerpt":{"rendered":" GenAI has captured organisational imagination like nothing I’ve seen since the early days of the web. The launch of ChatGPT in late 2022 marked a watershed moment, making AI suddenly feel tangible and accessible to everyone, not just data science teams. Every organisation I work with now has some kind of AI initiative. Board presentations […]<\/p>\n","protected":false},"author":231,"featured_media":21735,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"categories":[806],"tags":[],"location":[],"class_list":["post-21727","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-ai"],"acf":[],"yoast_head":"\nThe Matrix<\/b><\/h2>\n
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The flow<\/b><\/h3>\n
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The reality<\/b><\/h3>\n
The skills of AI exploration<\/strong><\/h2>\n
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\nThe three mindsets<\/h2>\n
1. Connect<\/b><\/h3>\n
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2. Experiment<\/h3>\n
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3. Build<\/h3>\n
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The reality check<\/strong><\/h2>\n