Mila Smart Semeshkin argues that traditional training cycles can’t keep up with today’s pace of change. With AI reshaping work, fast reskilling through microlearning is essential. Mila explores how personalised, in-context learning, supported by culture and data, helps organisations close skill gaps and stay competitive in a rapidly evolving market.

Five years ago, nobody was hiring prompt engineers, but today AI is revolutionising job roles faster than most organisations can keep up with. It’s expected that 39% of workers’ core skills will change by 2030. The market is flooded with new tools and workflows to match new job expectations. However, many companies still use traditional L&D cycles with quarterly and annual planning, and these old systems can’t match AI’s speed.

L&D needs to embrace “reskilling fast”

To keep up with techniques and technology, L&D needs to embrace “reskilling fast”. That doesn’t mean squeezing a year’s worth of training into a week. It’s about creating short, focused learning moments that help employees learn current AI skills without stepping away from their day-to-day work.

Microlearning as the engine of fast reskilling

We often treat learning and speed as opposites; one measured in depth and the other in deadlines. But AI development isn’t slowing and waiting a year to master new skills isn’t realistic. Learning shouldn’t be rushed, but it needs to be rethought.

Microlearning offers a practical middle ground between speed and real understanding. When lessons zero in on a single skill and stay short enough to finish between meetings, people use what they learn instead of filing it away for later.

If a company rolled out a new AI tool, employees would immediately receive short modules showing how to apply it right away. L&D teams don’t have to start from scratch either; they can curate from existing online micro-courses that are already up to date. That approach gives everyone, wherever they’re based, quick access to dependable content that keeps pace with the way their work keeps changing. To ensure relevance, these courses should be based on three factors: how current they are, how easily they integrate into existing platforms, and how well they align with skills the business needs.

The real value of microlearning shows up when it’s built into everyday work. Instead of treating training as something that happens outside the job, short, focused lessons can appear right when people need them most. It might be a quick message in Teams, a short tutorial before a client call, or even a brief reminder after trying out a new tool. Learning that happens in context sticks better. It helps employees apply new knowledge straight away and keeps development woven into the flow of work rather than sitting in a forgotten library of resources.

Personalisation is key to keeping it relevant. Different roles demand different skill refresh cycles, so microlearning paths should adapt to each employee’s responsibilities and proficiency level. Even simple data signals, such as role, department, or recent project activity, can guide what to surface next. The result is learning that feels individualised, not generic, and immediately useful.

Companies can formalise this concept through ‘micro-sprints’, weekly skill drops tied to emerging AI tools or business priorities, so employees can immediately apply what they learn while momentum is high. Through microlearning, L&D teams aren’t building a course; they’re building an adaptable and personalised living curriculum.

Building a culture and system that learns in real time

No learning initiative lasts long if it’s just built on compliance but has no room for curiosity and creativity. Therefore, for fast reskilling through microlearning to have a real impact, it needs to be accompanied by a culture that encourages growth and experimentation.

Leaders shape the tone by seeing learning not as a tick box, but as a way to raise performance and open career opportunities. When leaders talk about what they’re learning, make time for development during the workday, and recognise progress publicly, it sends the message: growth matters here. Reskilling is rarely easy, especially when workloads are heavy, so leaders must make learning feel supported and worth the effort.

But culture alone won’t sustain progress. It needs systems that keep up with it. L&D teams work best when all their skill data, course results, and feedback live in one place, making patterns visible and decisions faster. Simple metrics like time-to-skill, completion speed, and engagement levels show whether people are learning quickly enough and in the areas that really count. Those insights turn learning from a feel-good initiative into something that truly drives performance.

Fast reskilling is about shortening the distance between need and knowledge, which is only widening as technology evolves faster than training cycles can adapt. Doing that requires modular learning that’s easy to update, systems that bring learning into the flow of work, and a culture that treats growth as continuous. When skills expire in months, the advantage won’t belong to those who learn the most, but to those who learn soonest.

Mila Smart Semeshkin is CEO of Lectera and Founder of WE Convention