The L&D Blog

Future-ready learning: where to start with AI capability

In our previous article, From awareness to application, we explored how AI training is evolving as organisations move beyond basic awareness towards practical workplace application.

Since then, two important publications from Skills England and the Department for Work and Pensions have highlighted the growing importance of AI capability across the UK workforce:

The Skills England Annual Skills Report and Sectoral Skills Needs Assessments 2026
Skills for AI: What Works for AI Upskilling in the UK

Rather than summarising the reports, we’ve reflected on what they mean in practice for organisations looking to build AI capability.

One question keeps coming up: Where do we start?

Every organisation’s starting point will be different. However, based on what we’re seeing across our clients and the wider learning market, we’d encourage organisations to begin by asking four simple questions:

  • What business capability are we trying to build?
  • How will we build capability over time?
  • How does AI fit within our wider learning strategy?
  • How will we coordinate learning as our needs evolve?

The answers will vary from one organisation to another, but they provide a useful starting point for building future-ready capability.

1. Start with business capability

When AI becomes a priority, it can be tempting to begin by looking for courses or technology.

Our view is that organisations should first step back and ask:

What capabilities are we trying to build?

Rather than starting with learning solutions, consider:

  • Where could AI create the greatest business value?
  • Which teams or roles are likely to benefit most?
  • What level of capability is needed across the organisation?
  • How will AI complement existing ways of working?

Starting with business capability helps ensure learning supports organisational priorities rather than simply responding to the latest technology trend.

2. Build capability over time

Future-ready capability is rarely developed through a single training course.

Like leadership, technical and professional development, AI capability grows over time as people gain confidence, experience and opportunities to apply new skills.

Taking a phased approach allows organisations to respond to changing technologies and business priorities without needing to redesign their learning strategy every time something new emerges.

3. Keep AI within your wider learning strategy

Although AI is attracting significant attention, it is only one part of a much broader learning landscape.

Alongside AI, organisations continue to invest in leadership, compliance, technical, professional and operational capability.

Future-ready learning is not about replacing one priority with another. It is about balancing established learning needs with emerging skills, ensuring people have access to the right expertise at the right time, and adapting learning as organisational priorities evolve.

4. Plan how you’ll coordinate learning

As learning needs become more diverse, organisations are increasingly working with a wider range of specialist providers.

In our experience, the challenge is no longer simply finding training. It is coordinating learning across multiple subjects, suppliers and business areas while maintaining visibility, consistency and governance.

Future-ready learning isn’t simply about accessing more learning. It is about making increasingly diverse learning requirements easier to manage.

For many organisations, having an independent, vendor-neutral learning partner provides an effective way to access the right expertise while maintaining oversight of external learning across the wider organisation.

Looking ahead

AI capability will continue to evolve, but the challenge for organisations is unlikely to be choosing a single course or technology. It will be deciding how AI fits alongside wider learning priorities and how capability can be developed over time.

Whether the requirement is AI, leadership, compliance or technical development, the principles remain the same: start with business needs, build capability over time, keep learning aligned to organisational priorities and ensure increasingly diverse learning can be coordinated effectively.

Future-ready learning isn’t about preparing for one technology. It’s about building the capability and flexibility to respond to whatever comes next.

ITIL 5: The next evolution of digital service management

ITIL 5 is the latest AI-native evolution of the globally recognised service management framework, redesigned for increasingly digital and AI-driven business environments.

Launched in 2026, ITIL 5 places greater emphasis on customer and employee experience, AI governance, value co-creation, and modern digital service management. It also introduces a more simplified and role-aligned qualification structure designed to support practical capability development across organisations managing digital products and services.

Continue reading “ITIL 5: The next evolution of digital service management”

What does future-ready learning really look like?

Building capability has always been important for organisations navigating change. But as learning requirements become broader, faster, and more complex, the challenge is no longer simply delivering training – it is creating learning approaches that can evolve alongside the business itself.

This is what makes “future-ready learning” such an important conversation.
Continue reading “What does future-ready learning really look like?”

Reflections from Learning Technologies: Innovation, AI and the future of client learning

Last week, I attended Learning Technologies to explore new developments that could enrich our clients’ learning journeys, identify the latest advancements in AI for both our clients and our own business and discover new technologies that could improve efficiency while reinforcing the value we deliver.

Continue reading “Reflections from Learning Technologies: Innovation, AI and the future of client learning”

From awareness to application: how AI training is evolving in practice

AI is now firmly a business tool.

Across organisations, access to AI – particularly large language models – has increased rapidly. People are experimenting, exploring, and beginning to use these tools in their day-to-day work.

But what’s becoming clear is that access and effective use are not the same thing.
Continue reading “From awareness to application: how AI training is evolving in practice”

Regaining confidence and control in learning decisions

As learning ecosystems expand, decision complexity increases.

New priorities emerge. Suppliers multiply. Tools evolve. Budgets shift. Expectations rise. Each decision is made with good intent, responding to a genuine need. Over time, however, it can become harder to see how everything connects.
Continue reading “Regaining confidence and control in learning decisions”

Why capability needs to be built together

When organisations talk about capability, the focus often lands on learning activity: programmes, platforms, content or engagement.

Capability rarely fails through lack of effort or investment.

It fails when ownership is fragmented, follow-through is unclear, and responsibility is spread so thin that no one is accountable for how it all fits together.

Continue reading “Why capability needs to be built together”