Why HR and L&D Leaders Should Prioritise AI Training Now

1. The Tipping Point for Workforce Skills

The UK workforce is at a skills crossroads. While AI technologies are rapidly reshaping how teams operate, many organisations have yet to adapt their learning strategies. According to the Learning and Work Institute, employer investment in training has fallen by more than a quarter over the past decade, even as AI tools become integral to daily operations. The result is a growing mismatch between the technology businesses adopt and the skills employees need to use it effectively.

HR and L&D leaders are now under pressure to bridge that gap, not by adding more training content, but by embedding AI fluency into the core of workforce development. This isn’t just about futureproofing roles, it’s about maintaining competitiveness today.

2. AI Training Is No Longer Optional

AI adoption is accelerating across every sector, from automating admin workflows to driving customer insights, marketing optimisation, and product design. Yet many employees still lack the confidence or knowledge to work effectively alongside these tools.

Recent research from PwC suggests that UK businesses risk a £200 billion productivity loss by 2030 if they fail to equip employees with AI and data skills. The challenge goes deeper, as many existing training models still treat AI as a technical specialism rather than a workplace necessity.

Forward-thinking organisations are reframing this. AI training isn’t just about learning to prompt a chatbot or analyse data, it’s about empowering teams to think, plan, and execute differently. Those who make that shift early will gain a measurable advantage in efficiency, innovation, and talent retention.

For evidence, IT Brief recently reported that although AI adoption is growing, workforce training has not kept pace, creating a widening gap between technology capability and human confidence.

3. From Cost Centre to Capability Engine

One of the biggest barriers to investment is perception. Training budgets are often seen as cost centres, especially in tight economic climates. But AI capability should be viewed as an operational enabler, a multiplier that improves speed, accuracy, and decision-making across departments.

For HR and L&D leaders, the question isn’t whether to invest, but how to integrate AI literacy across existing learning structures:

• Embed AI modules into leadership and management development programmes.
• Encourage functional teams, such as marketing, HR, and finance, to explore AI use cases relevant to their daily work.
• Incentivise peer learning and experimentation through internal AI “champion” networks.

When AI literacy becomes part of the organisational fabric, training stops being an expense and becomes a driver of measurable performance gains. Resources such as the Access Group’s “AI Skills Gap in the UK” report provide practical insight into which skills matter most for building AI-ready teams.

4. Apprenticeships and Funded Opportunities: An Untapped Resource

While the UK government has made progress in funding digital apprenticeships and Skills Bootcamps, most schemes remain focused on entry-level roles. This leaves mid-career professionals, often those who most need AI fluency, without structured development routes.

The UK Government’s guide to apprenticeship funding clarifies how employers can use the Apprenticeship Levy to train both new hires and existing staff. Yet billions in levy funds still go unspent each year.

For HR and L&D leaders, this presents both a challenge and an opportunity. Levy funds can be used more creatively to build in-house AI capability by:

• Repurposing apprenticeship pathways to support continuous upskilling within existing roles.
• Partnering with accredited providers to develop bespoke AI learning frameworks for teams.

Recent initiatives, such as Multiverse’s commitment to train 15,000 new AI apprentices across the UK, show the growing recognition that AI and apprenticeships can coexist as a national strategy for digital capability. The infrastructure for AI training already exists, it’s just underused. More still needs to be done at a policy level to make these schemes accessible for all career stages, but forward-leaning employers don’t have to wait.

5. Building Confidence and Trust in AI

AI adoption isn’t just a technical challenge; it’s a cultural one. Employees need to understand not only how to use AI, but when and why to use it. Concerns about job security, data privacy, and ethics can stall adoption if not addressed directly.

Training that includes practical ethics, data literacy, and responsible AI use helps build trust and transparency. When employees feel confident and informed, they’re more likely to innovate and less likely to resist change. The UK Government’s report on AI skills for the workforce reinforces this, highlighting the need for ethical awareness and inclusive design as key components of any AI training strategy.

6. The Call to Action for HR and L&D Leaders

AI training should now sit at the heart of every workforce strategy. The cost of inaction is no longer just inefficiency; it’s irrelevance.

Practical next steps:

1. Audit your workforce: Identify where AI knowledge gaps exist across teams and functions.
2. Leverage funding: Revisit Apprenticeship Levy and Skills Bootcamp opportunities for digital and AI programmes.
3. Integrate AI into existing learning pathways: Don’t create standalone courses, embed AI modules where people already learn.
4. Build a hybrid model: Combine structured learning with practical experimentation so employees can apply AI tools directly to their roles.
5. Champion AI literacy from the top: Senior leaders must model engagement with AI tools to normalise adoption.

Final Thought

For HR and L&D leaders, prioritising AI training now means equipping teams with the skills and confidence to thrive in a rapidly changing landscape. The organisations that act early won’t just survive the AI shift, they’ll lead it.