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Home»Uncategorized»How companies train millions of workers when their products never stop shipping
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How companies train millions of workers when their products never stop shipping

By June 11, 2026No Comments4 Mins Read
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The data on workforce development tells a contradictory story. 85% of companies plan to prioritize upskilling their workforce through 2030. At the same time, 63% of employers still identify skills gaps as the single biggest barrier to business transformation.

The explanation for this is that the model most organizations use to develop their people was built for a slower world, and it hasn’t kept up. Learning and development content needs to get scripted, created, reviewed, localized and published.

Even in large, well-resourced organizations, that process can take weeks. By the time most training reaches an employee, the product it was designed to explain has shipped two new updates. The compliance process it covers has been revised. The sales motion it was meant to reinforce has already been changed by the team in the field.

We’ve all had the experience of sitting through mandated corporate training that felt more of a check-box exercise rather than an experience where we actually learn and retain something. To make that learning and development more relevant, companies are changing both the format and the time to delivery.

The Chief Learning Officer’s new mandate

Jayney Howson, Chief Learning Officer at ServiceNow, is working through what a better model actually looks like. ServiceNow University, the company’s initiative to upskill more than three million people by the end of 2027, was recently rebuilt to be AI-native.

The challenge her team faced will be familiar to most L&D leaders: a business shipping AI products on a continuous cycle, a global workforce that needs to stay current and a content production process that couldn’t move fast enough to serve them.

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Howson’s response was to rebuild the infrastructure around AI, including AI-generated video, reducing course production time by roughly ten times.

Her team was able to use Synthesia and produce more than 5,000 videos in 18 months, with programs like Sales Academy for their global sales team and partner enablement running consistently and globally. Learning content now reflects what the business is doing today, not what it was doing a few months ago.

According to Jayney, “It feels like a Netflix experience, where it serves up personalized recommendations for each employee. But it can also see that for the job I’m doing right now, the proficiency level I’ve got on a skill is a one and it needs to be a four. So it serves me up that training, too.”

Production is no longer the constraint

ServiceNow’s experience reflects a shift visible across enterprise L&D more broadly. Our research found that 87% of learning professionals are already using AI in their workflows. 72% say the biggest future gain they expect from AI is more personalized learning delivered closer to the moment of need, not just cheaper production.

Those two things have always been linked. Personalization at scale was the stated goal of corporate learning for years, and also its persistent failure. Building individualized learning paths for thousands of employees is not feasible when a single course takes weeks to produce.

When video content can be created, updated and translated in hours, that changes. Programs can be built for specific roles, regions and points in someone’s tenure, rather than averaged out across an entire workforce and useful to no one in particular.

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What changes for learning leaders

Organizations that solve the production capacity problem through AI free up their learning function to focus on harder questions.

Which skills actually drive business performance? What does good look like in a specific role, and how do you build toward it? How do you measure whether learning changed behavior, rather than just which employees clicked through a module?

Those are the questions that connect L&D to business outcomes in a way that completion rates never did. The organizations making progress on the skills gap tend to be the ones where learning leaders have been given permission to rethink the operating model, and where AI is being used to close the gap between when knowledge is needed and when it actually arrives.

For Howson, the infrastructure changes matter, but so does the environment around them. She describes her goal for ServiceNow University in terms that go beyond output to making sure the learning experience itself feels like a place where people can take risks.

“We all can remember being a kid and feeling like we were safe,” she said. “This needs to feel like you’re safe to push yourself and not get it right the first time.”

That combination of learning that’s faster, more relevant, and psychologically safe is what separates the organizations closing the skills gap from the ones still trying to solve a 2026 problem with a 2016 model.



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