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I’ve walked into boardrooms the place the power is excessive, the budgets are accredited and the ambition is obvious. Everyone seems to be speaking about AI. Only a few can reply the one query that really issues.
Not “What can we construct with AI?”
Not “How will we sustain with rivals?”
However this: What downside are we really attempting to unravel, and for whom?
The query sounds easy. It isn’t.
It forces precision in environments that reward momentum. It shifts the dialog from pleasure to accountability. And it shortly exposes whether or not you might be constructing one thing significant—or just reacting to noise.
Why readability breaks down inside organizations
Within the absence of a transparent sign or validation, the thoughts fills within the gaps. Groups persuade themselves they’re proper earlier than something has been confirmed. Leaders greenlight course earlier than the issue has been absolutely outlined.
That’s the place costly errors start.
Understanding the issue clearly — and confirming that the proposed answer really resolves it in a measurable means — is what separates progress from exercise. With out it, even well-funded initiatives drift into complexity that appears like progress however delivers little worth.
I discovered this early in my management profession, working with extremely succesful engineering groups. We constructed highly effective capabilities, however not all the pieces we constructed created worth. In some instances, we shipped options prospects by no means requested for and infrequently used. The end result wasn’t failure in execution — it was misalignment in definition.
When scope creep hides the true downside
I see this sample repeatedly. An organization identifies an actual, tangible downside. Then execution begins — and focus begins to blur.
For instance, I labored with organizations attempting to enhance monetary reporting. The issue was easy: it took two months to supply a P&L that ought to have taken one week. Clear downside. Clear alternative. However as a substitute of fixing it immediately, groups expanded the scope. Dashboards had been added. Visualizations multiplied. New options appeared that nobody requested. In the meantime, the accounting workforce nonetheless simply wanted one factor: correct information, delivered sooner.
The end result was predictable — extra complexity, extra effort, and fewer affect. That’s what occurs when the unique query is now not anchoring the work.
When one query redirected a $1.5 billion technique
I labored with a big personal firm the place the chairman, CEO and head of expertise had been aligned on a daring imaginative and prescient: AI-driven product suggestions. The ambition was to create a extra personalised, Amazon-like expertise — and probably flip it right into a standalone product providing.
On paper, it was compelling. However after we slowed down and requested a primary query — what downside are you really fixing, for whom and why — the cracks appeared shortly. Every chief had a distinct interpretation of the issue. Not one of the assumptions had been validated with the groups who would use the system or the shoppers who would profit from it.
So that they paused. They ran structured workshops, interviewed inner groups and examined assumptions immediately with customers. Inside weeks, alignment improved. Inside a month, the technique modified solely.
They walked away from a multi-million-dollar course that may have scaled into tens of tens of millions in funding — and as a substitute targeted on a narrower set of use instances that really improved buyer expertise and operational effectivity. The affect didn’t come from constructing extra. It got here from defining much less.
When AI turns into an alternative to considering
One other warning signal seems when leaders begin reacting to headlines as a substitute of their very own enterprise realities.
“We have to do AI as a result of everybody else is doing it.” That sentence alone is usually the place technique stops being technique.
I’ve seen organizations reallocate sources, launch initiatives and sundown priorities based mostly not on buyer want, however on exterior narrative strain. That’s how drift begins. Not by way of dangerous intent, however by way of borrowed urgency.
The issue is straightforward: rivals don’t share your context. What works for them might not apply to your prospects, your information, or your constraints. Typically probably the most strategic transfer is to decelerate lengthy sufficient to regain readability.
A sensible strategy to reset focus this week
You don’t want a full transformation to repair this. You want higher framing.
Begin with one initiative your workforce is actively engaged on and drive readability round the issue. Write it in a single sentence. If it will probably’t be made particular and measurable, the work downstream will mirror that ambiguity.
Subsequent, outline who particularly advantages from fixing it. Clients, staff, or inner groups—if the “who” is obscure, the worth might be too.
Then outline what success seems to be like in measurable phrases. What modifications if the issue is solved? What turns into sooner, cheaper or simpler? In case you can’t reply that, you’re not able to construct but.
Earlier than execution begins, validate the idea immediately with the individuals affected. Perceive how they clear up the issue right now, the place the friction really is and what enchancment would genuinely matter. A handful of actual conversations right here will outperform weeks of inner debate.
And as you progress into execution, resist the pure tendency to develop scope. Most tasks fail not as a result of they’re too small, however as a result of they attempt to turn into too full earlier than fixing something actual.
The hidden lure of AI-washing
We’re in a second the place almost each product, roadmap, and pitch contains AI.
However the presence of AI doesn’t assure the presence of worth.
Many organizations fall into what could possibly be referred to as AI-washing—rebranding initiatives in AI language with out making certain the underlying downside is actual or significant to customers.
A easy take a look at cuts by way of it:
In case you eliminated the phrase “AI” from this initiative, wouldn’t it nonetheless matter? Wouldn’t it nonetheless clear up an actual downside for an actual particular person? Wouldn’t it nonetheless get funded?
If the reply isn’t any, the technique isn’t prepared.
Why this query issues greater than ever
“Transfer quick and break issues” labored when the price of failure was low. That period is over.
Right now, the winners aren’t the quickest builders. They’re the clearest thinkers.
As a result of when the issue is well-defined, the viewers is particular, and the result is measurable, execution turns into considerably simpler—and way more precious.
Every thing begins with one query:
What downside are we really attempting to unravel, and for whom?
I’ve walked into boardrooms the place the power is excessive, the budgets are accredited and the ambition is obvious. Everyone seems to be speaking about AI. Only a few can reply the one query that really issues.
Not “What can we construct with AI?”
Not “How will we sustain with rivals?”
However this: What downside are we really attempting to unravel, and for whom?
The query sounds easy. It isn’t.