AI maturity levels in FE and HE libraries
As part of Higher Education Library Technology (a free open access and open data community resource), we wish to validate/challenge our draft AI 'maturity model' for UK HE and FE libraries.

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AI Maturity Levels
As part of Higher Education Library Technology (a free open access and open data community resource), Ken Chad Consulting has developed a draft AI 'maturity model' for UK HE and FE libraries. It measures library capability, not simply the number of AI tools deployed. It is based on work with libraries, published literature and the work by Jisc on institutional maturity models to support their Digital Transformation work.

Many libraries are experimenting with AI, but maturity depends on governance, workforce capability, integration with services, and alignment with changing student expectations. We now wish to validate our draft model to improve it and make it more useful to libraries to help them characterise/understand where they are and how they might progress in terms of their maturity level.

Our six-level model distinguishes between experimentation and enterprise adoption. It can be summarised as:

Level	Name	Characteristics
0	Unaware	No coordinated AI activity
1	Aware	AI recognised as important but largely unmanaged
2	Experimenting	Individual pilots and staff use emerging
3	Operational	AI embedded in selected library services
4	Integrated	AI incorporated into library strategy and institutional governance
5	Transformational	AI becomes a strategic capability underpinning library services, research support and digital learning

The characteristics are described in more detail in the sections after the main questionnaire. AI is changing fast. The characteristics are not fixed or definitive but serve as a guide to help you make a judgement about what maturity level you think your library is at

Some example characteristics of Level 0 – Unaware
Student behaviour:

• Many students already use ChatGPT and similar tools
• Library has little understanding of changing information behaviours
• Students receive inconsistent advice

Library staff

• Minimal awareness
• Individual curiosity only
• AI viewed largely as a threat

Policy

• None

Services

• Traditional information literacy
• No AI guidance

Challenges

• Lack of awareness
• Risk of becoming irrelevant
• No institutional conversation

Some example characteristics of Level 1 – Aware: The library recognises AI will change higher education.

Student behaviour
Students increasingly use AI to

• ask AI instead of using library discovery systems
• summarise articles
• generate search terms
• explain concepts
• write drafts

The library begins observing these changes.

Library staff
Some staff begin using AI for

• meeting notes
• emails
• document summaries
• marketing

Adoption remains individual.

Policy
Typically

• institutional AI policy exists
• library has no local guidance

Services
Occasional workshops
For example : "Using AI responsibly"

Challenges

• Uncertainty
• Staff anxiety
• Fear of misinformation
• Copyright concerns

Some example characteristics of Level 2 – Experimenting: AI becomes an active programme rather than individual curiosity.

Student behaviour
Get library support for:

• AI search behaviour
• Prompt engineering
• Information evaluation
• Citation practices

Information literacy evolves.

Library staff
Pilot use includes:

• literature searching
• metadata enhancement
• collection analysis
• LibGuides
• FAQs
• marketing
• accessibility

Policy

• Initial guidance
• approved tools
• acceptable use
• data protection
• confidentiality
• copyright

Services
Pilot projects- Examples

• AI chat assistant
• AI-supported enquiry service
• AI-assisted cataloguing

Challenges

• Skills gap
• Uneven adoption
• Tool proliferation
• Procurement uncertainty

Some example characteristics of Level 3 – Operational: AI becomes part of day-to-day library operations.

Student behaviour
Students expect

• conversational discovery
• AI-enhanced search
• personalised support
• instant assistance

Library services adapt accordingly.

Library staff
Routine use

• cataloguing assistance
• metadata generation
• collection management
• research support
• learning resource creation
• workflow automation

Staff understand

• prompt engineering
• verification
• bias
• hallucination
• human oversight

Policy
Formal governance -including

• approved platforms
• procurement standards
• risk assessment
• accessibility
• equality
• human review

Services- Examples

• AI discovery layer
• AI chat services
• AI-assisted systematic searching
• research consultation support

Challenges

• Integration
• Quality assurance
• Measuring value
• User trust

Some examples of the characteristics of Level 4 – Integrated: AI becomes embedded across library strategy.

Student behaviour
Library understands AI is changing:

• information seeking
• critical thinking
• digital literacy
• research practice
• assessment support

Information literacy becomes AI literacy.

Library staff
AI supports

• acquisitions
• repositories
• preservation
• analytics
• licensing
• research data
• scholarly communications

Professional development becomes continuous.

Policy
Comprehensive governance covering:

• ethics
• procurement
• transparency
• copyright
• intellectual property
• data governance
• vendor management
• environmental sustainability

Services
Integrated

• AI-enabled discovery
• research support
• learning analytics
• accessibility services
• knowledge management

Challenges

• Legacy systems
• Vendor lock-in
• Data quality
• Long-term sustainability

Some example characteristics of Level 5 – Transformational: The library helps shape institutional AI strategy.

Student behaviour
Students see the library as:

• trusted AI adviser
• digital scholarship partner
• critical evaluation expert

The library teaches:

• AI literacy
• verification
• source evaluation
• responsible AI
• academic integrity rather than traditional database instruction alone.

Library staff
Staff operate alongside AI.
Routine work is automated.
Professional expertise focuses on:

• judgement
• ethics
• research support
• knowledge curation
• partnerships

Policy

• Dynamic governance
• Updated continuously
• Evidence-based
• Institution-wide influence

Services examples

• AI research assistants
• multimodal discovery
• personalised learning support
• AI-enhanced repositories
• institutional knowledge graphs
• semantic search
• automated metadata enrichment

Challenges

• Keeping pace with technology
• Maintaining public trust
• Ethical leadership
• Workforce redesign
• Sustainable funding