According to the World Economic Forum's Future of Jobs Report 2025, the landscape of upskilling, reskilling, and talent acquisition (often referred to as talent management) has never been more dynamic - and more challenging.
The numbers reveal both an urgent need for change and an exciting opportunity:
- 39% of today's skills need to be transformed or replaced by the end of the decade.
- 63% of employers identify skills gaps as a major barrier to growth.
- 85% plan to prioritise upskilling their workforce.
- 70% aim to hire staff with entirely new skills.
For L&D and talent managers, this is a pivotal moment to shape the future of work. By designing strategic, tailored development programmes, they can bridge skills gaps, future-proof their workforce, and drive long-term success.
And, this proactive approach reduces the high costs associated with recruitment and turnover while ensuring the workforce is equipped to meet future challenges.
But, how can a L&D manager achieve all this and stay on top of the day-to-day?
Rethinking AI’s role in talent management
When we think about AI in L&D, it’s tempting to focus solely on its ability to automate content creation or streamline workflows. While these are valuable applications, the true potential of AI in talent management extends far beyond administrative efficiency.
AI has the power to revolutionise how learning is delivered, tracked, and applied, offering personalised, data-driven solutions that align both employee growth and organisational goals. A robust AI-enabled learning system can function as a personalised career coach for every employee, delivering tailored guidance to support their unique development journey.
The future of talent management: Combining AI with the human touch
From predicting skill gaps to crafting individualised development paths, AI can transform an organisation’s entire talent management strategy. However, the effectiveness of AI depends heavily on the quality of expertise and the data it’s built on. Put simply, AI is only as good as the human utilising it—you may have seen examples of this when poor prompts have been used in the likes of ChatGPT compared to specific and context-aware prompts.
A learning system that integrates 20+ years of talent management expertise into its AI tools will generate far more tailored and actionable insights than a generic AI platform relying on information gathered from search engines. By leveraging deep industry knowledge, such systems can deliver precise, impactful recommendations that truly meet the needs of both employees and organisations.
A talent manager’s guide to AI:
Here are a few examples of how an AI-powered talent management strategy can leverage this context to drive meaningful results:
1. Hyper-personalised career pathways
As we know, engagement is a perennial challenge in L&D. For many teams, it can feel like an uphill battle to keep learners motivated—especially in mid to large enterprises where you’re catering to over 500 employees with diverse needs. It’s easy to feel like there’s nowhere to turn.
This is where AI can step in to lighten the load for L&D managers. By leveraging the content created through conversations with line managers and aligning it with business objectives, an AI-powered system can take this contextual understanding and transform it into actionable insights.
Using data such as employee 360 evaluations and the company’s competency frameworks for specific departments, a well-designed AI agent can craft hyper-personalised career pathways. These pathways clearly outline how each individual can achieve their goals with tailored learning content, relevant events, and targeted assessments that make each step of the journey relatable and attainable.
2. Focused, self-directed learning
With the abundance of learning content available and the increasing ease of generating it, learners can feel overwhelmed by where to start and which resources are most relevant to their specific goals.
Traditional learning systems often rely on basic keyword searches, which require users to know exactly what they're looking for. This can create barriers to engagement, as users may not immediately find content that meets their needs. When learners don’t encounter the right, personalised resources from the start, they may feel frustrated, disengaged, and even discouraged from continuing their learning journey.
Consider a learner who seeks advice on handling a specific career challenge—perhaps they've just stepped into a management role and need guidance on addressing expectations around remote work policies. Without knowing the exact title or search terms, finding the right resource can be difficult, and the urgency of the situation may make this even more stressful.
This is where AI can transform the learning experience. By acting as an expert user within the system, AI can eliminate the need for managers or L&D professionals to manually assist learners in finding the information they need. A context-aware AI agent can analyse the learner’s search, recent evaluations, and career development plan to deliver highly personalised, relevant content—without having to narrow down search terms.
Moreover, AI can proactively suggest additional content and learning pathways after the initial query is addressed, helping learners stay engaged without overwhelming them with too much information at once. This ensures a more focused, efficient, and fulfilling self-directed learning experience.
3. The power to proactively fill skill gaps
Over the past eight years, the average LinkedIn member has experienced a 25% shift in the skills required for their job—a trend that shows no signs of slowing down. For L&D and talent managers, it often feels like being on a never-ending hamster wheel—constantly striving to keep up with emerging skills and trends. By the time a skill gap is identified, stakeholders are consulted, and a learning programme with updated content is designed and delivered, the content can quickly become outdated—especially when the skill gap is related to fast-changing technologies.
This is where an AI assistant can make a real impact. It can support the identification of skill gaps and leverage existing learning content to create new, dynamic pathways with clear success criteria to answer a critical question: Has the skill gap been closed?
By analysing organisational data, structure, and employee performance, AI can even predict where a skill gap is likely to emerge—enabling L&D and talent managers to act proactively. This data-driven approach empowers managers to make informed decisions without the need to sift through overwhelming amounts of data and reports.
Why expertise-driven AI matters
An AI platform infused with decades of talent management expertise doesn’t just respond to user queries; it anticipates needs and provides meaningful guidance. By blending cutting-edge AI technology with deep industry knowledge, organisations can empower talent managers to create personalised, impactful learning experiences that drive engagement, growth, and success.
Ready to introduce AI into your talent management strategy?
Discover how tools like Thinqi Q can help your organisation bridge skill gaps, retain top talent, and build a future-ready workforce. Request a demo today.
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