Digital Skills for 2026:

Building Inclusive AI Capacity

Why SMEs and the Heritage Sector Must Act Now and How to Upskill Without the Hype

Across the UK, demand for AI-capable workers is rising faster than supply. Yet most of the national conversation focuses on large technology firms, data scientists, and cutting-edge research labs. Left out of the narrative are the organisations who arguably need AI skills the most:
SMEs, microbusinesses, and cultural institutions, the groups who form the backbone of the UK economy and safeguard its collective heritage.

As we approach 2026, the question is no longer whether these organisations need AI capacity, but how they can build it affordably, inclusively, and sustainably. The emerging skills landscape shows that practical competence, not deep technical expertise, will be the defining requirement.

This blog explores UK-centric training trends, accessible upskilling pathways, and what SMEs and the heritage sector can prioritise now to remain competitive, compliant, and confident in an AI-first workplace.

The Skills Gap Is Shifting and Becoming More Practical

Early AI policy focused on PhDs and high-performance computing specialists. By 2025, industry needs had changed. The biggest UK workforce gaps are now in:

• AI literacy and critical evaluation

• Prompting and workflow automation

• Data governance and responsible use

• Domain-informed AI deployment, particularly in culture, education, and public service

This shift means SMEs and heritage bodies do not need teams of machine-learning engineers. They need staff who understand:

• what AI can and cannot do

• how to use the right tool for the right job

• how to check outputs, mitigate risk, and document decisions

• when to escalate technical issues

• how AI affects copyright, data protection, and ethics

The emerging consensus, echoed by UKRI, Innovate UK, and the Alan Turing Institute, is that inclusive AI understanding, not technical specialism, will underpin national competitiveness.

The 2026 Trend: Accessible, Sector-Specific AI Training

1. UK Government Support Is Expanding

Policy signals point to increased investment in SME-focused digital capability, including:

• targeted AI literacy programmes for local authorities and cultural organisations

• refreshed Skills Bootcamps with applied AI modules

• expanded Innovate UK BridgeAI offerings, with stronger heritage and creative-sector components

• increased funding for regional digital skills partnerships

While details will vary, the direction is clear: public funding is shifting from frontier research to practical adoption.

2. Sector-Led Learning Is Growing

Cultural and heritage bodies, from English Heritage to local museums, are developing:

• AI ethics guidelines

• open-access digital training

• role-based skills frameworks (curators, archivists, educators, conservators)

This sector-defined learning is critical, because general-purpose AI training rarely covers:

• intellectual property in cultural contexts

• data sovereignty for community-owned archives

• 3D/XR literacy

• public trust and interpretability in heritage storytelling

3. New “Lightweight AI Roles” Are Emerging

SMEs increasingly hire or upskill into practical hybrid roles such as:

• AI-aware project managers

• Digital heritage technicians

• Content professionals with data familiarity

• XR-capable educators

• AI compliance coordinators

None require advanced mathematics. All require confidence in workflows, judgement, and governance.

Where SMEs and Heritage Organisations Should Focus Their Upskilling

✔ AI Literacy for Everyone

The ability to evaluate AI outputs is now more valuable than the ability to train models. This includes:

• identifying bias

• detecting hallucinations

• understanding uncertainty

• interpreting provenance and model limitations

This is the foundation of responsible, cost-effective adoption.

✔ Data Governance & Copyright

With the EU AI Act and the UK’s post-regulatory framework evolving, organisations must ensure:

• clarity of data ownership

• careful metadata and documentation

• copyright-respecting workflows

• transparent decision logs

• auditable training sources (especially for cultural data)

✔ Workflow Integration & Automation

The next productivity wave will come from:

• integrating AI outputs into existing systems

• building small automations

• improving data flows

• shifting repetitive tasks to AI-assisted processes

This is where SMEs gain real operational advantage.

✔ 3D & XR Competence

For heritage organisations, local councils, and education providers, the next frontier is:

• understanding XR capture methods

• reviewing 3D reconstructions

• validating model quality

• preparing spatial data responsibly

Tools like Elata demonstrate that XR literacy is no longer specialist — it is becoming standard.

Avoiding Common Pitfalls

1. Overtraining and Underskilling

Many organisations focus on complex tools they will never deploy, while missing foundational literacy that every staff member requires.

2. Vendor-Driven Learning

Training supplied exclusively by commercial AI providers often lacks neutrality and rarely covers rights, risks, or sector-specific ethics.

3. One-Off Workshops

Real capability is built through repeated practice, embedded workflows, and shared organisational standards, not single training days.

4. Misunderstanding “AI Careers”

Most heritage and SME roles will remain fundamentally human, AI is a tool, not a replacement.
Training should broaden skills, not force staff toward unrealistic technical paths.

Practical UK-Centric Upskilling Routes

Free or Low-Cost Training

• UKRI & Innovate UK BridgeAI programmes

• Jisc digital capability frameworks

• The National Archives' digital preservation training

• Nesta: data & AI literacy modules

• OpenLearn (Open University) AI fundamentals

Supported Learning Through Partnerships

• Local Digital Skills Partnerships (LDSPS)

• Regional creative-tech clusters

• University knowledge-exchange collaborations

• Museum Development networks

In-House Capability Building

• shared AI policy documents

• workflow-specific training (acquisition, curation, outreach)

• team-level data standards

• staff-led “AI clinics” for questions and practice

Final Thought

Inclusive AI Skills Are a Cultural Investment

Building AI capability in the UK is not simply an economic initiative, it is a cultural one.
SMEs and heritage bodies are custodians of knowledge, stories, and public trust. Their staff do not need advanced machine-learning expertise, but they do need confidence, literacy, and a clear understanding of how to use AI responsibly.

By focusing on practical, accessible, and locally relevant upskilling, the UK can create an AI-literate workforce that is inclusive, resilient, and ready for 2026, without sacrificing creativity, autonomy, or the integrity of our cultural heritage.