Employees are reshaping how companies build AI-ready teams by demanding learning experiences that fit seamlessly into their daily work rather than pulling them away for static training sessions. Usage of AI-powered conversation-based learning experiences increased 146% year over year, with simulation-based practice experiences growing even faster at 341%, according to new data from Skillsoft, an AI-native skills management platform .

What's Driving the Shift Away from Traditional Training?

The explosion in personalized, practice-based learning reflects a fundamental change in how modern workforces want to develop skills. As artificial intelligence (AI) becomes embedded in everyday job tasks, employees increasingly seek learning opportunities that let them rehearse real-world situations, receive immediate feedback, and build confidence before applying new skills on the job . This contrasts sharply with the one-size-fits-all video training modules that dominated corporate learning for decades.

The numbers tell a compelling story. Launches of simulation experiences, which let employees practice skills in realistic scenarios, rose 341% during the past year, growing 2.3 times faster than the overall learner base . This dramatic acceleration suggests that employees aren't just adopting new learning tools; they're actively choosing them over traditional alternatives.

"Since its launch in 2023, CAISY has reflected a broader shift toward learning that happens in the flow of work. By using AI-supported, practice-based experiences across a range of skill areas, Skillsoft enables organizations to help employees build and apply skills in real work contexts, rather than separating learning from day-to-day execution," explained Gina Smith, PhD, Research Director at IDC.

Gina Smith, PhD, Research Director at IDC

Why Does This Matter for Enterprise AI Investment?

The timing of this shift is critical. While organizations are forecasted to invest $2.5 trillion in AI initiatives in 2026, much of that investment risks failing to deliver meaningful return on investment (ROI) due to gaps in workforce readiness and skills alignment . The challenge isn't acquiring the technology; it's equipping employees with the practical skills to use AI effectively in their roles.

Without systems that help employees build and apply skills in real time, execution slows and value gets lost. Organizations need to strike a careful balance: enabling employees to learn in ways that fit their preferences and schedules while ensuring that learning remains guided, measurable, and aligned to actual business outcomes .

How to Implement Effective AI-Powered Learning in Your Organization

• Embed Learning in Daily Workflows: Rather than scheduling separate training sessions, integrate AI-powered learning tools directly into the platforms and systems employees use every day, allowing them to build skills without disrupting their work rhythm.
• Prioritize Practice-Based Experiences: Move beyond passive video content to interactive simulations and conversation-based learning that let employees rehearse real-world scenarios, receive feedback, and build confidence before applying skills on the job.
• Align Learning to Business Outcomes: Ensure that skill development remains guided and measurable, connecting employee learning directly to performance metrics and organizational goals rather than allowing unmanaged, inconsistent learning to occur.
• Enable Employee-Led Learning: Support employees in pulling learning into their work on their own terms while maintaining organizational oversight to ensure consistency and quality across the workforce.

The data from Skillsoft, which analyzed aggregate user activity from December 2024 to December 2025 across its Percipio platform, represents adoption patterns among thousands of organizations worldwide, including 60% of the Fortune 1000 . This broad reach suggests that the shift toward in-the-flow learning isn't a niche trend but rather a mainstream transformation in how enterprises approach workforce development.

"Employees are pulling learning into the flow of their work as AI becomes embedded in daily tasks, rather than waiting for one-size-fits-all training. The risk is that unmanaged learning can lead to inconsistency and poor execution. Organizations need to strike the right balance, enabling employees to build skills in real time, in the ways they prefer, while ensuring learning remains guided and aligned to outcomes that drive the business," stated Bernard Barbour, Chief Technology and Product Officer at Skillsoft.

Bernard Barbour, Chief Technology and Product Officer at Skillsoft

The convergence of massive AI investment, employee demand for flexible learning, and the critical need for workforce readiness creates an urgent opportunity for organizations willing to rethink their training strategies. Companies that successfully implement AI-powered, in-the-flow learning experiences are positioning themselves to close critical skill gaps faster and accelerate their AI transformation with a workforce that's genuinely prepared to use these tools effectively .