Some people on your team pick up a new AI feature in Excel within a week. Others still avoid PivotTables. That gap does not close on its own, and in 2026 it shows up in reporting delays, inconsistent numbers, and a fair amount of quiet frustration between HR, team leads, and the employees stuck in the middle.

The gap is not really about who is smarter or who tries harder. It is about who got structured training, who feels confident enough to experiment, and who has been left to figure Copilot out between meetings. This article looks at why the gap forms, what it costs a team when nobody addresses it, and what HR managers and team leads can actually do about it this year.

What Is the AI and Excel Skills Gap?

The AI and Excel skills gap is the difference between the tools a company has rolled out, Copilot, AI functions in Excel, automated reporting, and what employees actually know how to do with them. A company can buy every license available and still see almost no change in output, because the software was never the bottleneck. The skill was.

This gap actually has two layers, and most companies only address one of them. The first layer is basic Excel fluency: structured data, formulas, PivotTables, the fundamentals that have not changed. The second layer is knowing how to work alongside AI inside that same spreadsheet, writing a clear prompt, checking whether a Copilot-generated formula is doing what it claims, and knowing when to trust an AI summary versus double checking it manually. Teams often get trained on the second layer while assuming the first one is already solid. It rarely is.

EY’s 2026 workplace AI survey found that 88 percent of organizations already use AI at work, yet only 28 percent have managed to get employees using it in ways that actually change how work gets done. That gap between adoption and capability is the problem in one statistic. A separate 2026 workforce report from Mercer found that 59 percent of HR leaders now name building critical digital skills as their top workforce challenge, ahead of budget or headcount concerns.

Why Do Some Employees Fall Behind on AI and Excel Skills?

Not everyone falls behind for the same reason. A few patterns show up on almost every team, and they tend to compound each other rather than exist on their own.

Confidence Gaps, Not Just Skill Gaps

Plenty of employees know more Excel than they think. What holds them back is not wanting to break something, so they stick to the three formulas they already trust and avoid the rest of the workbook. An AI layer on top of a program someone was already unsure about just adds one more thing to be cautious around. Some employees quietly avoid Copilot altogether rather than risk asking what looks like a basic question in front of colleagues.

Training That Never Happened

Formal training is rarer than most managers assume. Only 13 percent of workers have received any AI training in recent years, and just 38 percent of companies offer AI-related training at all. Most employees are figuring Copilot out through trial and error on their own time, which produces very different results depending on how much spare time and patience someone has. A manager who assumes training happened somewhere along the way is usually wrong.

Different Starting Points on the Same Team

A team of ten people can walk in with ten different Excel skill levels. Someone who learned Excel properly years ago picks up an AI layer on top of it fairly fast, because they already understand what correct output should look like. Someone who never had formal training is now trying to learn two things at once instead of one, which is exactly why generic, one-size-fits-all sessions tend to lose half the room within the first twenty minutes.

Tools That Assume a Baseline That Is Not There

AI features in Excel are built for someone who already understands what a well-structured spreadsheet looks like. Copilot can suggest a formula, but it cannot tell an employee whether the underlying data was entered correctly in the first place. Employees without that baseline end up trusting outputs they have no real way to evaluate.

How the Skills Gap Shows Up in Everyday Work

Before it becomes a visible problem, the gap is usually quiet. Reports take longer to put together than they should. The same figure gets calculated three different ways by three different people, and nobody notices until the numbers do not match in a meeting. Someone pastes an AI-generated summary straight into a report without checking whether the underlying numbers actually make sense.

It also tends to concentrate risk on one or two people. Most teams have that one colleague everyone quietly forwards their spreadsheet questions to. When that person is on leave or leaves the company altogether, the gap becomes visible fast, because nobody else was ever expected to close it.

If any of that sounds familiar, it is worth reading 5 Signs Your Team Needs Excel Training, which walks through the warning signs in more detail before they turn into bigger problems.

What Happens When the Gap Goes Unaddressed

IDC projects that more than 90 percent of enterprises will face critical AI skill shortages in 2026, with the resulting productivity losses estimated at 5.5 trillion dollars globally. Most of that is not one dramatic failure. It is small, repeated inefficiency across thousands of teams: manual workarounds, unchecked errors, and AI outputs nobody has the baseline knowledge to question.

For operational teams specifically, the cost shows up in places that are easy to miss until they add up. Procurement teams end up with supplier comparisons built on inconsistent formulas. Logistics teams lose visibility when shipment trackers get rebuilt slightly differently by every new hire. Finance teams spend review cycles hunting for the source of a discrepancy that a structured process would have caught earlier. And capable employees who feel like they are constantly behind on tools everyone else seems to understand are more likely to disengage or leave.

Research on underperforming AI rollouts backs this up. Most of them trace back to people and process, not the technology itself. The tools work fine. The team using them was never given the foundation to use them well, which means the license spend does not translate into the productivity gain it was supposed to deliver.

How to Close the AI and Excel Skills Gap in 2026

Closing the gap is less about finding a bigger course library and more about building a structure the whole team actually follows.

Start With an Honest Skills Check

Before assigning training, find out where people really are. A quick skills assessment across the team, not a self-reported one, gives HR and team leads a real baseline instead of a guess, and it makes it much easier to spot who needs foundational Excel work versus who is ready to move straight into AI-assisted workflows.

Tie Training to Real Workflows

Generic Excel lessons rarely stick. Training that mirrors the reports, trackers, and dashboards someone already uses is far more likely to change daily behavior than a course built around abstract exercises. Do Teams Still Need to Learn Excel in the Age of AI? covers why the Excel foundation still matters even as AI tools take on more of the manual work, and why skipping straight to AI training without it tends to backfire.

Give People Structured Time to Learn

BCG research found a clear threshold: employees who get at least five hours of structured AI training show significantly higher regular use and confidence afterward. Without protected time, that training gets pushed aside the moment a deadline shows up, and it never actually happens no matter how good the intentions were. How to Build an Excel Training Plan for Employees in the Age of AI breaks down what a realistic plan looks like for a team that cannot afford to lose full working days to it.

Make Someone Responsible for Tracking Progress

Training without visibility tends to quietly stall. HR or the team lead needs a way to see who has finished what and who still needs a nudge, otherwise the gap just moves further down the calendar and resurfaces at the next busy period.

Reinforce the Habit After the Course Ends

A single training session rarely survives contact with a busy quarter. Teams that actually close the gap build in a light refresher a few months later, once employees have had time to apply what they learned and run into new questions along the way.

Why Nordic Teams Choose Learnesy 

Learnesy is the only digital skills platform built specifically for Nordic business teams, delivering Excel, data analysis, and AI training in Swedish and Norwegian, designed for the way real departments work, and managed by HR rather than left to individuals.

That last part matters more than it sounds. Most Excel and AI training was built for individual learners browsing on their own, not for an HR manager rolling out training across a logistics, procurement, or finance department. Learnesy’s admin dashboard gives managers visibility into who has completed what, courses are built around real industry workflows instead of generic office scenarios, and every client gets a dedicated Customer Success Manager and a kickoff meeting instead of a support ticket queue. Lessons are short enough to fit around a normal workday rather than pulling a whole team offsite for a full day of training.

Explore Learnesy Courses

Summary: Closing the AI and Excel Skills Gap

AI and Excel skills gaps form because tools get rolled out faster than training does, and confidence, formal instruction, and starting skill level all vary more across a team than most managers realize. Left alone, the gap shows up as manual rework, inconsistent reports, risk concentrated around one or two people, and AI outputs nobody double-checks. Closing it takes an honest skills check, workflow-specific training, protected time to learn, and someone tracking progress. Learnesy gives Nordic HR managers and team leads a structured way to do exactly that, in their own language, built around their own industry.