AI isn’t just changing jobs – it’s transforming how we work. The World Economic Forum’s 2025 Future of Jobs Report shows that AI’s greatest potential lies in augmenting human capabilities, not just automation. This shift creates both opportunities and challenges for organisations racing to keep pace.
The skills gap is wide. While specialised roles in AI and data science remain hard to fill, every employee needs stronger technology skills. At the same time, distinctly human capabilities like creative thinking, resilience and adaptability are becoming more crucial for working effectively with AI.
Traditional L&D approaches are too slow to keep up. Even with AI accelerating course development, employees have limited time for formal training. Standard programs often miss individual skill gaps and career goals. Most importantly, learning in isolation from real work makes it hard for people to practice and apply new skills effectively.
Let’s explore four practical strategies L&D teams can use to tackle these challenges and prepare their workforce for an AI-driven future.
Talent Marketplace: Match skills to opportunities
AI-powered talent marketplaces transform career development by matching employees with projects, mentorships, and roles based on their skills and aspirations. This approach puts experiential learning at the centre of development while enabling organisations to deploy talent where needed.
Schneider Electric1 demonstrates the power of this approach. Their marketplace created over 13,000 mentoring relationships in 2022, with 9,000 being connections across borders or functional silos that traditional approaches would have missed. They also facilitated 6,000 project placements, creating opportunities for hands-on learning while solving real business challenges. Their AI engine analyses both current capabilities and potential, creating matches that benefit both employees and the organisation.
For L&D teams, this shifts the focus to enabling self-directed development. Instead of managing all learning centrally, L&D supports personalised learning pathways and resources aligned with employees’ chosen opportunities. This approach works particularly well for organisations with distributed workforces or strong silos that limit collaboration. It’s also effective when limited career progression or lack of transparency is affecting retention. Most importantly, it empowers employees to actively shape their development path while building skills through real work experiences.
Skills Accelerator: Build critical capabilities fast
Skills accelerators combine intensive learning with immediate application to address urgent skill gaps. Success requires collaboration across functions to create the right conditions for skill development and application.
A leading professional services firm2 used this approach to rapidly build AI expertise. They launched bootcamp-style intensives combined with client project work, ensuring consultants could immediately apply new skills. Crucially, they also updated their talent practices to prioritise assignments that reinforced new skills, adapted performance metrics to recognise skill application and equipped managers to support skill development in daily work. This comprehensive approach helped embed the new capabilities.
For L&D teams, skills accelerators offer an opportunity to drive measurable business impact through integrated learning experiences. The key is combining structured learning with hands-on practice, while ensuring systemic changes support skill application. This approach works best when organisations face urgent, high-stakes skill gaps and business leaders support making necessary changes. Success requires close partnership with other functions to identify critical gaps and create conditions for skill application.
Skills-Based Organisation: A new workforce management paradigm
A skills-based organisation puts skills, not jobs, at the centre of workforce planning and management. This creates a more fluid, adaptable workforce where skills drive all talent decisions.
EPAM Systems exemplifies3 this approach with their 50,000+ technology professionals. They use advanced analytics and AI to dynamically map skills to tasks, project roles, and business objectives. This enables rapid project staffing based on skills while giving employees clear visibility into development needs. Their capability academies help close skill gaps using formal and informal learning, while real-time validation ensures both technical and human skills are recognised through work. This approach helped them respond swiftly to the emergence of generative AI.
For L&D teams, this enables data-driven decisions about development investments and creates clear growth pathways. With solid skills data, L&D can design targeted initiatives that address specific gaps and prepare for emerging business needs. This approach works best when your industry demands high workforce adaptability and leadership commits to data-driven talent decisions. Success requires high investment in skills data, dynamic frameworks and workforce transformation.
External Ecosystems: Partner for innovation
External partnerships with universities and technology providers expand development options while accessing specialised expertise. These collaborations help organisations explore new technologies, tackle skill gaps and build strong talent pipelines for the future.
Telstra demonstrates this through university partnerships4 that enhance student learning and strengthen Australia’s tech talent pipeline. The Telstra-University of Wollongong AI of Things Solutions Hub5 connects industry leaders, including Microsoft and NVIDIA, with researchers to advance emerging technologies. Through pilot projects and collaborative research, this partnership addresses real-world challenges while building cutting-edge skills in AI and IoT.
For L&D teams, external partnerships offer new ways to develop cutting-edge skills development and build talent pipelines. By collaborating with universities and technology leaders, organisations can shape future talent while accessing expertise for current workforce development. This approach works best when internal capacity or expertise is limited for emerging skill needs, or when innovation and leadership in specific fields is a strategic priority. It’s particularly valuable when building future talent pipelines is crucial for long-term success.
Next Steps: Build your AI-ready strategy
These four approaches offer different paths to building an AI-ready workforce. The right mix depends on your organisation’s context, resources and strategic priorities. Success requires a clear learning strategy that aligns with business goals and deepens collaboration with others to help create the conditions for sustainable skill development.
Need help choosing and implementing the right approach for your organisation? Book a strategy call using our online calendar to explore how we can help you develop a learning strategy that prepares your workforce for an AI-driven future.
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Explore the examples
[1] For more on Schneider Electric’s talent marketplace listen to Learning Uncut Ep 118: Talent Marketplace at Schneider Electric
[2] This example is from the paper CLO Lift: The Skills Accelerator
[3] For more on EPAM System’s approach listen to the Skills: Yes, the Juice is Worth the Squeeze. Explore a second example by listening to Learning Uncut Ep 147: Putting Skills to Work at Ericsson
[4] This Telstra media release outlines five university partnerships
[5] For more on this solutions hub refer to the UOW website at this link