The Excel Effect

A Story Worth Sharing

Years ago, someone asked me a question that made me stop and think. "Should we invest in Excel training?"

At first, it seemed like an odd question. Everyone already had Excel. It was installed on every computer in the company. People opened it every single day.

But when we looked closer, something became impossible to ignore.

Most people were using only a sliver of what the tool could do. Some spent hours each week manually copying numbers from one spreadsheet into another. Others rebuilt the same report from scratch every month, never knowing a faster way existed.

And then there was a small handful of people who could make Excel feel almost like magic—turning a morning of tedious work into a two-minute formula.

Multiply that across a few hundred people, and the real cost comes into focus. Not in software licenses—those were already paid. The cost was hidden inside everyone’s week, one manual workaround at a time.

The difference wasn’t the software. Everyone had the same version, the same buttons, the same blank cells.

The difference was readiness.

A few people had simply learned to think differently about the work in front of them. They didn’t have better tools. They had better questions.

When we finally ran that training, the real surprise wasn’t that people learned new functions. It was what happened to their thinking. Once someone discovered that a task they had dreaded for years could be done in seconds, they started looking at everything differently. “What else am I doing the hard way?” became the most valuable question in the room.

I think about that team every time someone tells me, with great confidence, that their organization is “doing AI.”

Access has never been the advantage. Capability is.

Crossing the Bridge

Today, nearly every organization has access to powerful AI tools—just as nearly every organization once had access to Excel.

But access has never been the advantage. Capability is.

The numbers make this uncomfortably clear. In 2025, a widely discussed MIT study found that roughly 95% of corporate generative-AI pilots delivered no measurable impact on the bottom line.[1] The researchers were careful about the reason: the failures had little to do with the quality of the models, and almost everything to do with how organizations learned to use them.

McKinsey’s global research shows the same gap from the other side. Nearly all companies now report using AI in some form, yet leaders consistently underestimate how their people are actually using it—and almost half of employees say the biggest thing holding them back is a lack of training.[2]

Sound familiar? Everyone has the tool. Far fewer know how to use it well.

Notice what that really means. The gap was never about who owned the software. It was about who had been given the time, the encouragement, and the permission to get truly good at it.

The organizations creating real value aren’t necessarily running the most sophisticated technology. They’re asking sharper questions. They’re redesigning the work itself. They’re giving people permission to experiment without fear of getting it wrong.

Readiness is what closes the gap. It isn’t a product you purchase or a platform you switch on. It’s the quiet, unglamorous work of helping people build the confidence and the habits to use what they already have.

Technology doesn’t create transformation on its own. People do.

Build the Bridge

This month, ask yourself three simple questions:

•Where are people still doing work by hand simply because “that’s how we’ve always done it”?

•Who on your team is quietly using AI in ways the rest of the organization could learn from?

•What small experiment could build your team’s confidence before you chase a bigger transformation?

You don’t need a strategy off-site or a seven-figure budget to start. Find one repetitive task. Find the one person already experimenting. Give them room to share what they’ve learned.

Readiness isn’t built all at once. It’s built one practical step at a time.

Until next time, keep building the bridge.

Reflection

If everyone in your organization woke up tomorrow with access to the world's best AI tools...Would your organization be ready to use them?

[1]Source: MIT NANDA, “The GenAI Divide: State of AI in Business 2025,” as reported by Fortune, August 2025.

[2]Source: McKinsey & Company, “Superagency in the Workplace: Empowering People to Unlock AI’s Full Potential at Work,” 2025.