AI
AI cannot fix bad strategy
AI can optimise, generate, and accelerate, but it cannot correct a product direction that was flawed from the start. It amplifies the strategy it is given.
Why AI only creates value when it is anchored to a clear direction, and why using it on top of weak strategy often makes the underlying problem harder to see.
In short
Why AI only creates value when it is anchored to a clear direction, and why using it on top of weak strategy often makes the underlying problem harder to see.
Why AI feels like progress even when direction is unclear
Most of the problems that show up in digital products aren't caused by poor execution. They sit much earlier: the wrong problem has been prioritised, the journey doesn't reflect how users actually behave, the structure doesn't support the task it's meant to enable. When that happens, no amount of glossaryOptimisationOptimisation is the process of improving a product or journey to increase performance, usability, or conversion.Open glossary term will fix it. AI just makes it happen faster.
AI does not rescue unclear thinking. It simply scales whatever direction the product is already moving in.
Why optimisation is not the same as effectiveness
Content can be improved, but if it's answering the wrong questions, it will still miss the mark. Journeys can be streamlined, but if they're built on incorrect assumptions, they will still create glossaryFrictionFriction refers to anything that slows users down or makes it harder for them to complete a task. It can be caused by poor design, unnecessary steps, unclear messaging, or technical issues.Open glossary term. glossaryInterfaceAn interface is the point of interaction between a user and a system, where inputs are made and outputs are received. It can be visual, physical, or conversational.Open glossary term can be refined, but if the underlying flow is flawed, the experience will still break down. Everything becomes more efficient. But not more effective.
Key takeaway
If the problem has been framed badly, AI can improve the execution while leaving the real issue completely untouched.
Why AI can create a false sense of progress
AI is very good at making things look better. It can produce cleaner copy, more consistent structures, and more polished outputs. From the outside, it can look like the product has improved significantly. But underneath that, the same issues often remain. The glossaryStrategyStrategy is a high-level plan that defines long-term goals and the approach to achieving them.Open glossary term hasn't changed. Metrics may shift slightly, glossaryEngagementEngagement refers to how users interact with a product, content, or experience, including actions like clicks, time spent, and interactions.Open glossary term may improve in places, and there's a sense that things are moving in the right direction. But the core problem is still there, just hidden behind better execution. That only holds for so long, because users don't respond to polish. They respond to relevance.
Why strategy has to come before AI
Before AI is introduced, before glossaryOptimisationOptimisation is the process of improving a product or journey to increase performance, usability, or conversion.Open glossary term begins, before anything is generated, the direction needs to be clear. What problem is being solved? Why does it matter? How does the product support that in a way that makes sense for the user and the business? Without that glossaryClarityClarity is how easily users can understand what is happening and what they need to do.Open glossary term, AI has nothing solid to work with.
Used properly, once the glossaryStrategyStrategy is a high-level plan that defines long-term goals and the approach to achieving them.Open glossary term is right, AI can be incredibly effective. It can scale content, accelerate glossaryIterationIteration is the process of repeatedly improving a product through cycles of testing, feedback, and refinement.Open glossary term, and support glossaryRefinementRefinement is the process of preparing and clarifying backlog items before development.Open glossary term in a way that would otherwise take significantly more time. When the direction is clear, AI becomes a multiplier. When the direction is wrong, it simply reinforces the problem, making it harder to recognise and more expensive to fix later. AI is not a safety net. It will not step in and identify that the wrong problem is being solved. That still requires human judgement. The temptation is to use AI to improve what exists. The reality is that sometimes what exists needs to be challenged first.