Stop buying, start building: How to win the digital skills race

Technology teams the world over are used to working in sprints but as we look ahead to 2026, the digital agenda will be dominated by a different kind of sprint: one that will see organisations racing to acquire the skills they need to stay relevant and compete. 

Against the backdrop of a tough economy, rapid environmental change, and AI-everything, upskilling is now the most important race that organisations need to win. In fact, the stakes have never been higher and skills - especially digital skills - represent the ultimate prize. 

Buying skills, either through recruitment or by hiring a contractor, has been the default approach for many years. But as the rate of knowledge change increases, and as AI skills gaps continue to grow, business leaders are having to face facts: procuring digital skills from outside the business is no longer a sustainable option, and certainly not at scale. 

Digital skills: why it's better to build

The reality is that most organisations are struggling to plug emerging tech and AI skills gaps. Demand for digital skills outstrips supply so even if organisations could afford to keep buying skills, chances are they wouldn't be able to source the right ones anyway.  

The only sustainable solution is to build skills within the organisation by enabling continuous, skills-relevant learning in the flow of work.

AI-powered skills mapping

So how can organisations build an effective digital skills strategy? 

The best starting point is framed around three key questions: What skills do we need next year? Which of these skills do we currently have? How can we plug the gaps? 

The second of these questions can be especially difficult to answer. Manually mapping skills requirements against existing capabilities presents a monumental task for those with any sizable workforce. It's incredibly time-consuming and worse still, by the time the L&D team has finished, the data is often already out of date. In such a fast-changing climate, it's simply not fit for purpose. 

This is where AI itself is helping to plug digital skills gaps by accurately mapping, assessing, and documenting every employee's skills capabilities in days or weeks rather than months. Equipped with this holistic and current view of capabilities, business leaders can see exactly what skills they need to build, where, and when. 

Upskilling and cross-skilling: a lateral shift

Another factor at play here is the question of digital workers needing to broaden their skill sets - and not just to compete with their industry colleagues, but to out-skill tech and AI innovation itself. Coders, developers, and engineers are recognising that, to future-proof their careers, they need to keep growing and diversifying their skills portfolios.

But the digital skills gap isn't just about coding or AI literacy. It's about foundations, too. And if people don't have the broader digital skills to adapt, collaborate, and problem-solve, the reality is that advanced initiatives are more likely to fail. As part of this, we're already seeing industry innovators moving from T-shaped to M-shaped skills models. The days of hyper-specialisation are over, and organisations must now prioritise digital cross-skilling as well as upskilling.  

There is opportunity in this shift, of course. Companies can expect to reap associated cost efficiencies and productivity gains, while tech talent will gravitate to employers who can support their upskilling, cross-skilling, and future-proofing needs. 

Skills development - at speed and scale

In an environment where the fastest learner wins, enabling digital workers to develop skills quickly and effectively is the top priority. This calls for the right learning content, delivered in context, as well as the coaching and instant feedback that enables people to put learning into practice. 

If we were to rewind five to ten years, this is where you'd find a paragraph about building a great learning library. But a lack of learning content is no longer the problem. In fact, we have an abundance of great content. Many learning platforms can also deliver this in context. What very few can do, though, is provide the guidance and two-way dialogue that helps employees to quickly grasp and apply new concepts.

What we're talking about here is great teaching - and we all know how important this is for learning success. The problem is, until recently, great teaching has always been difficult to scale due to cost.

Hyper-personalised teaching

AI learning agents are now making it possible to scale hyper-personalised teaching across an entire workforce - on-demand, in context, and in the flow of work. Powered by credible and verified learning resources, these agents are purpose-built to understand and interact in meaningful, context-aware ways. They understand a learner's job role, their skill level and goals, and they can tailor their teaching to specific challenges, adapting dynamically over time. 

As demand for digital skills reaches cataclysmic heights, these AI learning agents are also presenting organisations with a new - and highly effective - route to rapid upskilling and cross-skilling. 

So as we look to 2026 and beyond, here's my prediction: the organisations that will win the race for digital skills are not those with the biggest learning libraries. Instead, those who emerge triumphant will be the ones who succeed in unlocking great teaching for every employee. This is where the real opportunity lies - and it marks a whole new era for people and business success.