According to Mercer’s 2024–2025 Global Talent Trends report, 58% of executives agree that digital innovation is outpacing their firms’ ability to retrain employees1.
For Learning and Development (L&D) leaders, this widening gap brings both urgency and opportunity. Their role is no longer simply to train employees to use new tools; it’s about ensuring every individual understands how AI can drive productivity, unlock marginal gains, and reshape everyday tasks and processes.
In the following sections, we’ll explore how L&D leaders can empower managers with the right tools and data to help employees understand their own capabilities and how to use technology to their advantage.
Over half (54%) of workers and leaders are concerned about the increasingly blurred lines between work performed by humans and work handled by technology2. Encouraging employees to adopt new tools and thrive in a digital age begins with creating clarity around the skills they already possess. Before people can fully embrace AI, they need to understand how their existing capabilities fit within an evolving landscape of human–machine collaboration.
This clarity starts with skills mapping, aligning employees to a structured skills framework that provides a clear, data-driven view of skills from an employee level to a holistic organisational level. By identifying and analysing both technical and soft skills, organisations gain a true picture of what their people can do today and their potential to grow into future roles. Rather than relying on assumptions or outdated job descriptions, skills mapping establishes a solid foundation for a more agile, future-ready workforce, one that evolves in step with changing business priorities and technological advancement.
By making employees’ skills more visible, organisations also create a shared language for growth and collaboration. Employees and managers can start to determine which tasks are best performed by people and which can be supported by technology. Yet despite this potential, 47% of employees report lacking clarity about what’s expected of them3. This challenge can be addressed when managers have a clear understanding of their employees’ current skills, interests, and skill gaps and communicate this effectively across their teams.
Once organisations establish the need for clarity and can visualise the skills of their people, the next crucial step is generating deep insights into employee capability. Capability must be defined broadly, encompassing traditional technical skills and proficiency levels as well as identifying soft skills such as emotional intelligence, critical thinking and communication.
To achieve this visibility, organisations can leverage various tools to gather talent intelligence. This process involves identifying and recording workers’ entire skill portfolio, that reveals capabilities beyond formal job descriptions and validating these skills and levels with employees and managers. Alongside gathering technical skills data, organisations can use tools like psychometric assessments to measure work style, motivations and soft skills. According to Mercers global talent trends report4 only 31% of workers say they are currently required to enter their skills into a centralised database.
Once you’ve achieved clarity around the current skills and capabilities of your workforce, you can begin to see the skills gaps and where the real opportunities lie. With this visibility, L&D teams can distinguish between gaps that can be closed through traditional learning and development courses and those that can be augmented through AI enablement.
For example, some roles may benefit from structured upskilling in emerging technical or digital skills, while others may focus on learning how to use AI tools to enhance decision-making, automate repetitive tasks, or boost creativity. The goal is not to replace human skills, but to extend them, designing L&D programmes that balance human insights with machine augmentation.
This marks a fundamental evolution in the role of L&D: from providing courses to enabling continuous adaptation. As AI capabilities evolve, so too must people’s skills and their ability to learn, unlearn, and relearn. The evolution of technology and the skills needed to work alongside it means that the learning cycle no longer has an end point, it becomes a living process, constantly refreshed by new technology and new ways of working.
In this new era of the augmented workforce, success will belong to organisations that see learning not as an event, but as a perpetual journey one where every employee is empowered to evolve alongside AI.
Drive AI readiness in your organisation through skills mapping and continuous learning. Get in touch to find out more.
