AI has made strategy, goals, and prioritisation more important than ever
One thing I keep noticing with teams is how easily work can become requirement-driven.
We all know the story — a request comes in, people want to get moving, a stakeholder asks for something, a feature gets suggested at the right level of hierarchy. Someone writes it down as a requirement and from that point on, all energy goes into delivery.
In a way, it does make sense — requirements feel concrete, they give people something to react to, estimate, design, build, review, sell. However, they can also pull attention away from the thing that should be guiding the work in the first place — the goal. It matters, so much so that it frames what success actually looks like for the product/feature/team.
That part gets overlooked, forgotten or ignored completely (intentionally, or not).
A requirement is one possible response to a goal, not the goal itself. When teams stop making that distinction, the work can become very narrow, very quickly.
I have seen teams fail to make that distinction so many times. The result — they stay busy, work keeps moving, features ship, but the outcomes feel thinner than they should:
User satisfaction improves a little, maybe, but not enough.
Business value is harder to point to.
The effort is real, but the payoff is weaker than expected.
Goal vs requirement driven work
Goal driven work starts earlier. Before the solution hardens and the request becomes sacred.
It starts with asking what actually needs to change and why.
What are we trying to improve here?
What problem is worth solving?
What are we trying to reduce, enable, validate, or learn?
Asking those questions early on, changes the conversation more than people sometimes expect. It becomes easier to question requests without sounding difficult, to look at alternatives, make trade-offs grounded in something real, instead of just negotiating scope around half-examined ideas.
None of this happens in a vacuum, of course — real work comes with constraints, time, budget, technical limitations, dependencies, the burden of legacy systems, stakeholder pressure and often imperfect information. That is exactly why aligning around a goal matters so much. It helps teams move forward with informed decisions, instead of just reacting to whatever landed on the table first, and got labelled as a requirement.
Requirements still matter, of course. Teams need clarity. They need structure — at some point work does have to become concrete. However, if that happens too early, before a team has actually anchored in the goal, then their work starts orbiting the request instead of the outcome. That is usually where value starts leaking out, rather than accumulating.
Strategy matters even more now, than ever before
AI is changing the cost and speed of execution significantly. It’s easier to write, build, test, rewrite, explore and rework than it has ever been. That is incredibly useful, it removes friction in a lot of places.
What AI doesn’t do is improve judgement on its own.
If the direction is weak, AI does not solve that. It will simply enable a team to move faster with weak direction. It helps build around an idea that, maybe, should have been challenged much earlier on. More screens, code, content. More visible progress around something that isn’t necessarily well-aimed.
The easier execution becomes, the more important it is to know what is actually worth pursuing.
Yes, one of the clear benefits of AI is how much cheaper backtracking can be. Rework is less painful — trying something, learning from it and redoing it is faster than ever.
But Cheaper ≠ Free.
Wrong direction still costs. It costs time, focus, context switching and noise. It can chip away at confidence and morale when a team keeps moving quickly and then having to reverse, revise, undo what it just aligned on. It can be messy.
Right now, clear direction and goal alignment is particularly important, as it is easier than ever to build momentum around the wrong thing.
AI is raising the speed baseline for everyone, not just one single company or team. So in any competitive market, speed on its own is not going to be much of a differentiator. Instead, it’ll be the team that is:
✅ Clearer on their goals
✅ Better at setting priorities
✅ Understands really is worth pursuing before they start accelerating
✅ Uses AI to sharpen thinking, not just increase output
The real advantage sits upstream
The point was never to just ship faster. It is to create products that deliver in user experience, business value and make better use of time, budgets, and effort. AI can absolutely help with that, but only if the work is pointed in the right direction first.
When everyone can execute faster, speed stops being a differentiator and clear direction becomes one.
