Organizations have never invested this much in learning, yet one challenge remains:
How to turn learning into real behavior change.
At DEVELOR, we see a consistent pattern: learning often stops at understanding, while performance depends on application.
A strategic partnership
To address this, DEVELOR has entered a long-term strategic partnership with AIBLE Simulations, founded by Marianna Khonina, former Managing Director of DEVELOR Ukraine & Central Asia.
This collaboration spans the DEVELOR network and strengthens our Development Journey methodology with a critical element: scalable, AI-powered practice.
The missing link: practice
Most development programs build knowledge, but behavior change requires more. Without practice, feedback, and repetition, learning rarely translates into action.
As Marianna Khonina puts it: “AI finally lets us do what we always knew mattered – practice.”
From knowledge to performance
By integrating AIBLE Simulations, DEVELOR enables participants to practice in realistic, AI-driven scenarios, receive immediate feedback, and build confidence through repetition.
This creates a safe environment to experiment, learn, and improve, before it matters in real situations.
A long-term ambition
This partnership is not about adding a tool. It is about evolving how learning works. Our goal is clear: to turn learning into measurable performance across the DEVELOR network.
To explore this topic further, we spoke with Marianna Khonina, founder of AIBLE Simulations and former Managing Director of DEVELOR Ukraine & Central Asia.
With over 18 years of experience in Learning & Development, she offers a clear perspective on why the current market approach often fails to drive behavior change and how practice-based learning can close this gap.
In the interview, she explains:
- What is truly needed for behavior change after training?
- How does AI enable scalable, realistic practice environments?
- Why the future of learning lies in action, not just knowledge?
- At DEVELOR, we use solutions like AIBLE Simulations to strengthen the application phase within development journeys – before, during, and after training – ensuring that learning does not stop at insight, but continues into real behavior.
Why explore this topic?
- Understand why training effectiveness is still a challenge despite increased investment
- Discover what is missing from most learning journeys
- Learn how practice-based learning supports real behavior change
- See how AI can create scalable, realistic learning experiences
- Gain insights from an experienced L&D leader on the future of learning
Who is this article for?
- HR and L&D professionals looking to improve training impact
- Leaders responsible for capability development and performance
- Organizations exploring AI in learning and development
- Anyone interested in the future of workplace learning
Frequently asked questions about AI-powered learning and behavior change
Most training programs focus on knowledge transfer, often in short formats due to time constraints. However, without enough time for practice, feedback, and repetition, new behaviors rarely translate into real workplace performance.
AI-powered simulations allow participants to practice real-life scenarios in a safe environment, even beyond the limited time of training sessions. They provide immediate feedback and enable repeated practice, helping turn knowledge into confident, consistent behavior.
Practice is what transforms understanding into action. Especially when training time is limited, continuous practice opportunities are critical to reinforce learning and ensure long-term behavior change.
