As we look ahead to 2026, new standards are starting to emerge that reflect how work is actually changing inside organisations. Less focus on narrow technical roles. More emphasis on practical capability. And a recognition that AI and automation are no longer niche skills reserved for specialist teams. Richard Peters, CEO of Decoded, shares his perspective on why this shift matters now.
There is a quiet shift coming in the world of AI apprenticeships. The proposed AI and Automation Practitioner Level 4 apprenticeship is the first of these new standards we have seen, and a welcome direction of travel.
Of course automation is common to a greater or lesser extent within most businesses, but often at the surface level.
Behind the scenes, teams are still drowning in manual, cognitive work. Tasks like triaging emails, reviewing invoices, researching leads, preparing reports, or managing workflows across disconnected systems. This is not simple “click-button” automation. It requires judgement, context and decision-making.
IT teams are often too stretched to build bespoke solutions for every function. As a result, operational bottlenecks persist, and the people who understand the processes best are left working around them with spreadsheets, inbox rules and manual admin.
This is the context gap. And it is exactly what the new AI and Automation Practitioner apprenticeship standard is designed to address.
The AI and Automation Practitioner Level 4 standard focuses on empowering business practitioners.
It is designed for those who already understand how work gets done inside an organisation. Operations, finance, HR and other process owners who sit closest to the problems, but who have not traditionally had the tools or skills to redesign them.
The intent is to enable these practitioners to move from manually executing processes to orchestrating digital workers. Using low-code AI tools, they can design workflows and build AI-powered agents that are capable of perceiving information, reasoning about it, and acting to achieve defined business outcomes.
This is a significant shift. It recognises that the future of automation is not just about efficiency, but about augmenting human expertise with systems that can handle complexity and context.
This standard is emerging at a time when many organisations are experimenting with AI, but struggling to scale it responsibly.
Leaders often tell us the same thing. Pilots look promising, but impact is patchy. Tools are introduced, but capability is uneven. And governance, ethics and oversight lag behind adoption.
By embedding responsible AI, workflow design and practical application into an apprenticeship pathway, this standard aims to build capability that is both sustainable and defensible. Not just people who can use tools, but people who understand when, why and how to apply them in real operational environments.
There is also growing conversation across the skills ecosystem about shorter-form apprenticeship programmes, particularly aimed at more senior or experienced professionals.
While details are still emerging, the direction is clear. Organisations want flexible, focused pathways that allow leaders and practitioners to build AI and automation capability without stepping away from their roles for extended periods.
This is an approach Decoded is already taking through its Accelerator programmes, including work supporting the UK government to build practical AI capability across public sector teams. These programmes focus on applied skills, real use cases and immediate organisational impact, rather than abstract theory.
If shorter-form apprenticeships do become part of the landscape, they will sit naturally alongside this kind of applied, outcome-led learning.
If shorter-form apprenticeships do become part of the landscape, they will sit naturally alongside this kind of applied, outcome-led learning.
The emergence of the AI and Automation Practitioner Level 4 apprenticeship is an important signal.
It reflects a shift away from viewing AI as purely a technical discipline, and towards recognising it as a core business capability. One that needs to be developed across functions, embedded into processes, and governed responsibly.
As new apprenticeship standards take shape over the next year, organisations would do well to start thinking now about where their real automation bottlenecks sit, who understands those processes best, and how they want to build capability for the long term.
At Decoded, we see this as a positive step forward. One that aligns closely with how we have been training teams in data and AI for years. And one that could help many organisations finally move from experimentation to meaningful, scalable impact.
We’re already in conversation with organisations about what the next wave of apprenticeship standards and short-form AI learning could mean for building capability at pace.
If you’re thinking about how apprenticeships, accelerators and other applied learning pathways might fit together to support AI and automation adoption, we’d love to talk.
Get in touch to start the conversation and stay informed as these new standards take shape.
If you’d like to learn more about Decoded and how we can help transform your
organisation, we’d love to hear from you.
