How Leaders Must Evolve with AI-Driven Metrics

by | Feb 6, 2025 | Leadership, Management, Strategic Execution | 0 comments

“Without data, you’re just another person with an opinion.”

~ W. Edwards Deming

Do metrics drive the right behaviors – or do they just create noise?

Because here’s what I’m seeing: Most organizations are drowning in data but starving for clarity.

And the irony? The more we measure, the harder it is to focus on what actually matters.

Where We Started: The Birth of Business Metrics

Business metrics weren’t always this complicated.

In the beginning, they were simple: Revenue. Profit. Cost Control. The numbers that mattered most were financial. And for a while, that worked. Leaders relied on gut instinct, experience, and a few key financial indicators to guide decisions.

Then businesses got bigger. Much bigger. Organizations became more complex. And leaders needed better ways to align goals across teams.

So, cascading scorecards, KPIs, and OKRs were born.

  • Scorecards gave leaders a snapshot of performance – balancing financial and non-financial metrics.
  • KPIs (Key Performance Indicators) helped organizations track specific performance areas.
  • OKRs (Objectives and Key Results) linked ambitious goals to measurable outcomes.

Each new system improved measurement but did not guarantee improved decision-making.

Then came the digital explosion.

The AI Revolution: Metrics That Predict the Future

After everything went digital, we entered a new era. And it is constantly evolving. I liken it to the early days of the Industrial Revolution. What started with the invention of a single machine (essentially, the steam engine) became entirely new economies, geopolitics, and urbanization at an unprecedented scale.

I believe AI is doing the same thing. And getting back to today’s thread, AI is going to fundamentally change how we measure success.

Traditional metrics were rearview mirrors – they told us what happened last quarter, last month, last week. AI flips that. Now, metrics aren’t just historical; they’re predictive.

This changes everything.

  • AI can detect hidden patterns in massive datasets, surfacing insights humans might miss.
  • Machine learning continuously refines predictive models, improving forecasting accuracy.
  • Automated reporting eliminates time-consuming data crunching, freeing leaders to focus on execution.

Think about sales forecasting. In the past, teams analyzed historical data, made projections, and hoped they were right. Now, AI can pinpoint where the buying journey is at risk and recommend tactical behavior changes to fix the problem.

I’ve done it. Not with AI, but with an analyst who worked with me.

We took a major market’s sales pipeline and discovered that pipeline erosion was cut in half (wow…) by one simple yet very intentional customer interaction. We shared the insight with the greater team and worked together to fix that. The win rate went from 17% to over 30% in just a matter of quarters. Revenue surged… and so did employee morale.

That’s what I mean when I say that we are going to fundamentally change how we measure success.

Imagine if our own AI had been taught how to look for this and surface the insight in real-time – before the win rate dropped to below 20%.

The same applies to everything from employee engagement to customer churn to supply chain efficiency.

We will be more proactive than ever before. We will be more targeted than ever before. We will be more successful than ever before.

But here’s the catch: More data doesn’t mean better decisions.

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Transparency: Using Metrics to Build Trust

Metrics shouldn’t just be a measurement tool. They should be a leadership tool.

Yet too many companies use data as a weapon – a top-down enforcement tool instead of a shared reality. Which ultimately ruins the data quality because people stop putting in the unvarnished truth and cherry-pick what gets recorded. Potential wins and good news get elevated while delays and bad news get buried.

Transparency fixes this. When employees understand how metrics are chosen, why they matter, and how they impact strategy, three things happen:

  1. Trust increases – because people know the numbers aren’t being manipulated.
  2. Decision-making improves – because teams have access to real-time, relevant data.
  3. Accountability grows – because success is defined openly and fairly.

These are the behaviors we want our metrics to produce, right? We want metrics because they help us be the best version of ourselves SO THAT our potential for greatness can be achieved. This kind of transparency produces the opposite of resulting, no? This is the dream that AI is offering.

But – again – there’s a catch: Transparency must be voluntary.

And I’m not sure that we are able to deliver that.

There are far too many examples of companies that illustrate this dynamic.

Especially when “success” is on the line.

The Human Factor: How Metrics Get Corrupted

At the end of the day, AI and metrics are just tools. The real question is: How are we interpreting and applying them?

Because data doesn’t drive decisions – humans do.

And at some point, humans bring misinformation, bias, and hidden fears into every decision-making process. Which is why better decision-making is not guaranteed – regardless of how “cool” your metrics are.

And this is why AI can either enhance leadership thinking or amplify existing dysfunction.

When we measure success, we assume the data tells a clear, objective story. But the moment unhealthy ego enters the equation, that story changes.

The Ego/Fear Loop distorts how we collect, interpret, and act on insights.

Here’s how:

  1. Unhealthy ego craves success, significance, and control. Leaders want to be seen as high performers, so they fixate on metrics that validate their decisions – not necessarily the ones that reveal the truth.
  2. Fear kicks in – especially the fears of failure, rejection, and risk. Instead of asking, “What does this data teach us?” teams start asking, “How does this data make us look?”
  3. Resulting takes over. Leaders judge decisions only by outcomes, not by the quality of the process that led there. If a target is hit, the assumption is that the decisions were good – even if they weren’t.
  4. Metrics become weapons, not tools. Instead of fostering insight and course correction, data gets manipulated, misinterpreted, or selectively ignored to fit narratives that protect egos and reduce perceived risk.

Have you ever seen the above in action? More importantly, is it in action now?

I ask because the outcome is all but guaranteed… flawed decision-making, short-term thinking, and ultimately, underperformance.

Breaking Free: Using AI-Driven Metrics the Right Way

To avoid falling into the Ego/Fear Loop, leaders must approach metrics differently:

  1. Detach from the data. Look at what the potential insights say with a neutral mindset. Ask: Am I measuring this to understand and learn, or to validate my assumptions?
  2. Check for fear-driven bias. When reviewing metrics, ask: What are we avoiding? What tough truths are we resisting?
  3. Redefine success. Focus on the quality of decision-making, not just outcomes. AI should help refine the process – not just confirm what we want to hear.

The goal here is to become adaptive and proactive. Shift when the metrics tell you. Change metrics when the data demands it. Challenge the data to teach you. Program your AI to deliver these kinds of behavioral triggers.

This is the potential of great metrics. Great metrics drive the right behaviors.

A Final Word

Pause. I have to add one final thought. Metrics won’t fix bad leadership. It takes quality leadership to make metrics helpful.

But when paired with self-awareness and a willingness to challenge assumptions, metrics can transform how we lead. It leads to greater clarity AND empowerment. With clarity and empowerment in place, employee engagement thrives – and so does accountability. The resulting culture becomes vibrant and fun to be part of.

And that’s where real high performance begins.

Holomua. Onward and upward.

Originally published at: https://www.linkedin.com/pulse/how-leaders-must-evolve-ai-driven-metrics-tim-ohai-makgc/

PS When you are ready, here are a few ways for us to continue your journey together.

An extra thought:

“To improve is to change; to be perfect is to change often.”

~ Winston Churchill

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