Less than 25% of learning leaders say their learning strategy is fully aligned to their organization’s business strategy.

You can find that eyeopening stat in our “AI readiness gap: The 2026 Enterprise Learning Wake up Call” report, where we polled over 1,000 learning leaders about how in sync they felt their organization’s learning and business strategy were, among other things.

In essence, three out of four L&D teams are designing, delivering, and defending programs that aren’t fully in agreement to what the business actually needs. Which might explain why getting stakeholder buy-in feels like pushing a boulder up a hill.

This is a tale as old as L&D, and it’s a costly one, especially today. Our report, which also surveyed over 1,000 enterprise learners found that 85% of learners felt the training they received did not help them fully understand how AI relates to their roles. Oof. 

That’s the issue; a learning function that can’t connect its work to business outcomes won’t be able to close the AI readiness gap. Is this because L&D functions don’t have the data to show its importance?

The data problem hiding in plain sight

To put it lightly, no. Here’s what Derek Mitchell, CEO of Gallus Insight, said in our 2026 AI Readiness Gap Report, and it’s worth reading slowly:

“Organizations aren’t struggling with AI because they lack data. They’re struggling because they don’t use it. They already have rich data about people, roles, and business priorities, but learning is still designed in isolation and measured by activity rather than outcomes.”

Derek Mitchell, CEO of Gallus Insight

So, the data exists. The problem is what we’re doing (or not doing) with it.

In our AI Readiness Gap report, we found that 44.4% of organizations still rely on completion rates as a primary way to understand learning progress. Completion. Whether someone clicked through a module and hit submit. Not whether they can do the thing. Not whether the thing they learned changed how they work. Just, did they finish?

This might explain why fewer than half of learning leaders feel confident they can connect learning to business results. It’s likely they might be mainly measuring things like completion, and then struggling to justify their budget to a CFO who wants to know what they’re actually getting for it.

It’s like going in circles. Misaligned measurement creates weak business cases. Weak business cases create skeptical stakeholders. Skeptical stakeholders don’t prioritize learning. And learning that isn’t prioritized doesn’t get the resources it needs to actually move the needle.

Why alignment breaks down (it’s not what you think)

The instinct is to blame executive support. And yes, 21.5% of learning leaders cite stakeholder buy-in as a challenge. But the real issue runs deeper.

Most L&D teams are designing learning in isolation. Content gets built based on what someone requested, or what a training vendor pitched, or what worked two years ago. It gets delivered. Completion rates get reported. The business moves on.

What’s missing is the connection from the start: What business outcome are we trying to affect? What does someone need to be able to do differently? How will we know if it worked?

Charles Jennings, co-founder of the 70:20:10 Institute, put it plainly in our report:

“L&D must focus on the critical tasks that drive business success, align closely with stakeholders, and measure how learning changes performance at scale. Without tying learning directly to organizational objectives, AI readiness will remain an aspiration rather than an outcome.”

Charles Jennings, Co-founder of the 70:20:10 Institute

What it looks like when it works

CSI, a technology partner to community and regional banks across the US, was running into exactly this problem, and fixed it in a way that’s worth understanding.

Katie Dyer, Manager of Training Logistics at CSI, was responsible for compliance and product training across more than 1,000 employees and 500 client banks, which meant over 24,000 individual bankers in the platform. The reporting situation was, in her words, “an absolute nightmare.” She was pulling data from multiple systems, spending half a day consolidating and reformatting it, and still couldn’t answer the question she got asked constantly: what’s the ROI on your training program?

That question matters a lot when you’re in a compliance-heavy industry. Community banks need to know their people are trained, certified, and current. “We don’t have the data” isn’t an acceptable answer when regulators show up.

CSI moved to Docebo and added Advanced Analytics, which let them connect learning data directly to their CRM, Power BI, and Smartsheet. This shift changed what Katie’s team could actually do.

The implementation team got a real-time dashboard showing new client progress through certification and onboarding, login trends, and learner activity. That alone saved them 52 hours a week compared to exporting reports into Excel and manually hunting for what they needed. Katie’s team reduced their overall admin burden by more than 50%. Training optimization cycles got 2x faster because they finally had feedback they could act on quickly.

And here’s the alignment piece: with attendance data sitting alongside customer tenure and support case volume, CSI could start connecting training behavior to customer outcomes. They spotted consistent attendance drops in July and November and made a smart call: dedicate those months to content development instead of delivery. That’s a learning team making decisions based on real patterns, not gut instinct.

The result was a program that CSI could prove worked, so confident in its value, in fact, that they started offering their foundational Banking 101 suite to clients at no extra cost. That’s what happens when a learning team can finally answer the ROI question.

The shift worth making

If the report surfaces one clear action, it’s this: instead of designing learning programs, design business outcomes, then build the learning backward from there.

In practice, that means a few things:

Start with the business metric

Before any program gets designed, ask what success looks like in terms the business cares about. Not “learners will understand the new process.” More like “error rates on X will drop” or “time to first sale for new reps will shrink by Y weeks.”

Measure the right things

Completion rates tell you who showed up. Performance metrics tell you if anything changed. Skills data tells you where the gaps still are. The organizations bridging the AI readiness gap are tracking all three, not just the first one.

Get your data connected

One of the structural reasons learning stays misaligned is that learning data lives in a silo. When it can’t talk to your CRM, your HRIS, or your business intelligence tools, you’re always going to be making the case for L&D with incomplete information. Integration isn’t a nice-to-have; it’s the mechanism that makes alignment possible.

Bring stakeholders in early

Alignment isn’t a reporting problem; it’s a design problem. If L&D isn’t in the room when business priorities get set, learning will always be playing catch-up. The teams that have earned a strategic seat at the table got there by speaking in business outcomes, not learning outputs.

Where do you stand?

The AI Readiness Gap Report has the full data, along with a framework for assessing where your organization sits on the maturity curve and what to do about it. If you’ve read this far, it’s probably worth knowing your number.

Download the AI Readiness Gap Report: The 2026 Enterprise Learning Wake up Call.

Up next in the series

Alignment and measurement get you to the table. But staying there requires a learning ecosystem that continuously senses what your people need, develops them, and validates that it’s working.

In our next post, we’re talking about skills intelligence. We dive deep into why 40% of employees cite career growth as their main motivator for completing training, what it actually means to build a skills-driven learning ecosystem (hint: it’s not a static framework gathering dust in a SharePoint folder), and why Gartner found that companies using skills intelligence platforms see a 30% increase in internal mobility.

It’s the piece that connects everything. Stay tuned.