In today’s rapidly changing workforce, efficient onboarding of new employees has become a crucial competitive advantage. Every additional week needed to train employees is a week of lost productivity.
AI offers the opportunity not only to accelerate learning, but also to sustainably increase the efficiency of companies. One global survey by the consulting company Cegos from 2024 found that 44 percent of employees are already using AI-supported learning and 81 percent of HR departments are integrating such technologies or planning to introduce them. This shows that AI is becoming established in the training sector of companies. At the same time, this also raises an important question: How can companies ensure that faster learning does not come at the expense of comprehensive knowledge transfer and long-term anchoring of knowledge?
“Time to Competency” counts
In corporate learning Time to competence a central factor. This refers to the time required by employees to acquire the skills, knowledge and security so that they can do their work effectively and independently. It is an important metric because reducing this time can increase productivity, reduce training costs and provide a competitive advantage. However, rapid knowledge acquisition can prove counterproductive if the knowledge acquired is superficial or does not last.
AI is changing learning
Humans’ ability to learn has developed over thousands of years – it only took AI a few years to do so. When aligned with learning best practices, AI can transform learning in three key ways: personalization, practice, and measurement. For example, let’s take a look at what these three factors look like in practice when training new sales employees.
Personalized learning journeys increase employee engagement
First, AI-powered personalization drives employee engagement. Generative AI tools can help learners tackle complex topics based on their individual knowledge gaps. In the case of sales employees, AI can analyze employee performance patterns and knowledge levels. From this, she can create tailor-made learning paths that focus on the skills that individual employees need to acquire – be it product knowledge, negotiation techniques or dealing with customer objections. This personalized concept leads to significantly better knowledge anchoring and application because the learning is directly relevant to the respective role.
Simulated practice accelerates the acquisition of knowledge
Second, hands-on learning accelerates onboarding and knowledge acquisition. For example, sales employees can use AI-supported simulators to practice customer conversations with virtual buyers who naturally respond to different pitches and sales methods. They receive immediate feedback on their communication style, how they handle customer objections, and how clearly they explain the benefits of products. These simulated interactions increase self-confidence before real customer meetings and significantly reduce training time.
Measure and maintain knowledge levels
Thirdly, measurement ensures that the knowledge remains permanently anchored. Sustainable learning requires more than speed. It must ensure that the material is fully understood and can be applied over the long term. AI learning platforms not only monitor that training is completed, but also track how knowledge is evolving through ongoing assessments. Repeated on-the-job training and extensive practical experience can help consolidate knowledge. For example, sales teams can use AI tools that analyze real customer interactions after training and measure how effectively new techniques are applied. And you can continuously offer micro-learning units to refresh if what you have learned is slowly being forgotten. This way you can ensure that investments in sales training lead to lasting performance improvements.
From knowledge gaps to strategic learning
But even with these tools, learning and continuing education professionals face challenges. As the Cegos study reports, almost half of HR employees have difficulty adapting their training offerings quickly enough to their actual needs. Employees, on the other hand, often have the feeling that their training needs are addressed too late. AI can bridge this gap using learning analytics to identify knowledge gaps early and take timely action.
The real opportunity lies in balancing rapid knowledge acquisition with building long-term skills and knowledge. Companies must not only measure how quickly employees achieve a certain level of knowledge, but also ensure that this knowledge and skills are permanent. The most important strategies include microlearning, customized learning content, mentorship and integration of practical phases – all of which aim to firmly anchor knowledge and reduce unnecessary delays.
Ensure long-term anchoring of knowledge
To truly shorten the time it takes to acquire knowledge while ensuring a comprehensive, lasting level of knowledge, companies need structured, scalable learning solutions. One such solution is SAP Learning Hub. It offers comprehensive access to expert-led resources to help you both Obtain SAP certifications as well as keeping it up to date. Structured learning journeys ensure an individual learning pace and continuous development. They enable employees to continue their professional development while completing their daily tasks. By integrating SAP training into daily workflows, companies can promote sustainable learning habits and equip employees with the skills they need for long-term good performance.
AI will not replace human learning, but will improve it – but only if we use it in a targeted manner. As managers, we must measure learning success not only by how quickly we acquire knowledge, but also by how durable and sustainable the knowledge is.
Markus Marsch is Global Head of Product and Solution Learning for SAP Industries & Experiences.
