We manage in real time, but most organizations still measure execution after the fact. Now we can close that visibility gap in real-time: to see the decisions, behaviors, handoffs and friction that shape execution while they are happening.
Measure in real time. Support in real time. Execute in real time.
For decades, I learned to dive into the root cause of a problem. To ask why things happened, what broke, and what was really behind the outcome. I learned the methodologies, the mindset, and most importantly, how to turn the analysis into action.
But there was always one limitation I couldn’t solve:
By the time we analyzed the root cause, the problem had already happened.
Today, AI gives us an opportunity to change that.
For decades, we have accepted something strange in management.
We manage in real time.
But we measure after the fact.
A manager leaves a meeting without a clear decision.
We don’t measure it.
Two teams leave with different interpretations of who owns what.
We don’t measure it.
A handoff gets stuck between Product and Sales.
We don’t measure it.
A manager repeatedly avoids a difficult conversation.
We don’t measure it.
Instead, we wait.
Eventually, the KPI turns red.
The project is delayed.
The customer escalates.
Engagement drops.
Someone resigns.
And then we start analyzing what happened.
This is the visibility gap.
The distance between the moment execution starts to break and the moment the organization can finally see it.
And that distance is expensive.
Microsoft found that employees are interrupted by a meeting, email or notification every two minutes during the workday. Nearly half of employees describe their work as chaotic and fragmented. (Microsoft, Work Trend Index, “Breaking down the infinite workday” (2025)).
Think about how much execution happens inside all of those interactions.
A decision gets delayed because nobody frames the tradeoff.
An important meeting ends with five action items and no clear owner.
A team spends three weeks solving the wrong problem because nobody challenged the original assumption.
A manager senses tension between two functions but moves on because there are eight more items on the agenda.
These moments matter.
But they don’t appear in the dashboard.
The dashboard sees the outcome.
It doesn’t see what created it.
AI gives us a chance to change that.
Not because AI can produce another dashboard.
And not because we need another tool summarizing meetings.
The real opportunity is that, for the first time, we can start measuring the signals that happen while work is happening.
Was a decision actually made?
Is ownership clear?
Are teams aligned on what happens next?
Is the same bottleneck appearing again and again?
Is a process moving forward, or looping between teams?
Is unresolved tension starting to affect execution?
And once we can see these signals, something much more important becomes possible.
We don’t have to wait to measure the problem. We can intervene while there is still time to change the outcome.
Imagine a manager finishing a meeting and knowing immediately that the team discussed the issue for 40 minutes but never made the decision.
Or being alerted that three different meetings this week ended with unclear ownership around the same strategic priority.
Or seeing that a process that looks perfectly healthy in the project management system has actually bounced between two functions four times.
Or recognizing that one manager consistently gets decisions made quickly, while another repeatedly reopens decisions that were supposedly closed.
Now we are no longer doing post-mortem analysis.
We are managing execution.
And there is another important shift here.
For years, HR has measured many of the most important things through surveys, assessments and lagging indicators.
Engagement.
Leadership.
Collaboration.
Manager effectiveness.
Gallup estimates that managers account for 70% of the variance in team engagement. (Gallup, “Managers Account for 70% of Variance in Employee Engagement).
Yet much of what managers actually do every day remains invisible.
AI can change that too.
Not by judging people.
By making behaviors measurable.
We can start connecting what managers do with what happens to execution.
Did ownership become clearer?
Did decision speed improve?
Did collaboration improve?
Did meetings become more effective?
Did the team learn to resolve problems differently?
That is a significant opportunity for HR, Operations and leadership.
Because suddenly, behavioral change doesn’t have to live only in workshops, surveys or annual reviews.
It can become part of how the organization executes every day.
Measure in real time. Support in real time. Execute in real time.
That, to me, is one of the biggest opportunities of the AI era.
Not simply automating more work.
Closing the distance between what is happening, what leadership knows, and when we can still do something about it.
The organizations that close this visibility gap won’t just understand execution better.
They will have the opportunity to change the outcome before it becomes a number on the board deck.