University of Education and Entrepreneurship
Learning • Work • Enterprise
Institutional Policy on the Adoption, Compliance and Ethical Use of Artificial Intelligence (AI)
For Teaching, Learning, Assessment, Research, Innovation and Administrative Activities
Approved and adopted by the University Senate at its 8th Regular Meeting, Thursday, 29 January 2026, Senate Chamber.
| Policy title | Institutional Policy on the Adoption, Compliance and Ethical Use of AI |
|---|---|
| Institution | University of Education and Entrepreneurship (UEE), Akamkpa |
| Approving authority | University Senate |
| Approval record | 8th Regular Meeting, Thursday, 29 January 2026 |
| Policy administrators | AI Ethics and Compliance Committee, CTLE and ICT Directorate |
| Scope | Staff, students, researchers, contractors, consultants and authorised collaborators using AI for University activities |
| Review | At least annually and following material legal, NUC or technological changes |
Artificial Intelligence (AI) is increasingly influencing higher education, including teaching, learning, assessment, research, innovation, student support and institutional administration. Appropriate use can strengthen educational quality, research productivity, entrepreneurship, accessibility and operational efficiency. Improper use can create risks involving inaccurate outputs, bias, privacy, cybersecurity, intellectual property, academic integrity, over-reliance on automation and unequal access.
The University of Education and Entrepreneurship, Akamkpa (UEE), recognises the need to encourage beneficial innovation while protecting human dignity, academic standards, institutional information and the rights of members of the University community. This Policy establishes a framework for responsible, transparent, accountable, secure, inclusive and human-centred AI adoption.
This Policy is grounded in the University's institutional proposal and the Senate approval information supplied for its 8th Regular Meeting on 29 January 2026. It shall be implemented consistently with applicable National Universities Commission (NUC) frameworks and directives, Nigerian law, University regulations and relevant international guidance. Where a binding law or applicable NUC directive imposes a higher or more specific requirement, that requirement shall prevail.
1.1 This instrument shall be cited as the University of Education and Entrepreneurship, Akamkpa, Institutional Policy on the Adoption, Compliance and Ethical Use of Artificial Intelligence (AI), 2026.
1.2 The Policy records Senate approval and adoption at its 8th Regular Meeting held on Thursday, 29 January 2026. It shall operate from that date, subject to any further ratification or commencement requirement under the University's governing instruments.
1.3 The Policy shall be implemented through University Management, the AI Ethics and Compliance Committee, the ICT Directorate, the Centre for Teaching and Learning Excellence (CTLE), faculties, departments and relevant units.
1.4 This Policy supplements, and does not replace, University statutes and regulations, academic integrity and examination rules, research ethics requirements, staff and student disciplinary procedures, data-protection requirements or applicable law.
AI refers broadly to computational systems that perform tasks associated with human cognitive abilities, including prediction, classification, language processing, pattern recognition, content generation and decision support. Generative AI can produce text, images, audio, video, code and other content in response to instructions.
UEE's education and entrepreneurship mandate makes AI literacy and responsible technology use important to preparing educators, researchers, innovators and graduates. A clear institutional framework is necessary to ensure AI supports rather than replaces human judgement, and that its use respects academic integrity, valid assessment, research ethics, privacy, equity and institutional accountability.
The purpose of this Policy is to provide a clear institutional framework for the adoption, regulation, compliance and ethical use of AI at UEE. Its objectives are to:
4.1 This Policy applies to all academic staff, non-teaching staff, undergraduate and postgraduate students, researchers, research assistants, visiting scholars, consultants, contractors, vendors and external collaborators when conducting University business or using University systems, data, facilities, accounts or resources.
4.2 It covers University-related use of AI tools and systems, whether University-provided, procured, licensed, open-source, embedded in other software or accessed through third-party services.
4.3 Personal use unrelated to University activities is outside the direct operational scope, but remains subject to applicable law and University rules where it affects University data, people, systems, duties or reputation.
Artificial Intelligence (AI): Computational systems that generate predictions, recommendations, classifications, content or decisions.
Generative AI: AI that creates or transforms text, images, audio, video, code or other content.
AI tool/system: Any application, model, platform, feature or service incorporating AI functionality.
AI-assisted work: Work to which AI materially contributes, including writing, analysis, design, teaching materials or administrative outputs.
AI disclosure: A statement identifying the AI tool used and the material nature of its contribution where disclosure is required.
AI compliance: Awareness, responsible use and functional competence in AI tools relevant to a user's role.
Human oversight: Meaningful review by a competent person able to question, correct, reject or override AI output.
Human-centred use: AI shall support, not displace, human judgement, expertise, creativity, critical thinking and responsibility.
Transparency: Users shall disclose material AI assistance when required by this Policy, course instructions, research protocols or publication requirements.
Accountability: Users remain responsible for work, decisions and actions informed by AI.
Accuracy and verification: AI-generated facts, references, quotations, statistics, code and interpretations must be independently checked.
Privacy and confidentiality: Personal, confidential, sensitive or restricted information must not be entered into public or unapproved AI systems without authorisation and suitable safeguards.
Fairness: AI must not unlawfully discriminate or reinforce unjustified bias.
Integrity: AI must not be used to fabricate evidence, falsify data, plagiarise, impersonate others or circumvent examination rules.
Security: AI systems must be assessed for access control, reliability, security and relevant operational risks.
Inclusion: Implementation should consider disability access, language, connectivity, affordability and equitable access.
Proportionality: Controls and review shall reflect the risk and potential consequences of the AI use.
All academic and non-academic staff shall obtain AI certification approved or recognised by the University within twelve (24) months of the Policy's adoption, by 29 January 2028, unless the competent University authority formally amends the deadline. Newly employed staff shall obtain the required certification within twelve (12) months of appointment.
Training may be delivered through University workshops, recognised online platforms or partnerships with competent training providers. The University shall communicate approved options, acceptable certificates, evidence-submission procedures and any exemptions. Mention of a commercial platform in training materials does not by itself constitute University accreditation.
The University shall provide students with programme-appropriate AI literacy and responsible-use guidance. Any certification made a condition of graduation must be established through a formally approved academic regulation specifying scope, assessment, accessibility arrangements and transitional provisions.
The University shall organise digital literacy and professional development programmes at least twice in each academic session. Training should address AI literacy, data privacy, cybersecurity, AI-enhanced pedagogy, assessment integrity, research innovation, digital collaboration, social and emotional intelligence and leadership in digital education.
Training and certification records shall be maintained with appropriate data-protection safeguards. Refresher training or renewal may be required where justified by technological change, role or University requirements.
Subject to course, research, professional, confidentiality and system-specific rules, AI may be used for:
Listing a use here does not automatically authorise it in every context. Users must follow lecturer instructions, assessment conditions, research protocols, data classification, procurement rules and University restrictions.
The following are prohibited unless a specific lawful exception is authorised by the appropriate University authority:
Restricted or high-impact uses shall be referred to the AI Ethics and Compliance Committee and relevant professional unit before implementation. A privacy, security, fairness, academic-integrity or other risk assessment may be required.
10.1 The University shall promote a blended and intelligent learning model combining face-to-face teaching, online or virtual learning and appropriate AI-supported learning pathways.
10.2 Staff may use AI for lesson planning, learning materials, simulations and student support, but must review outputs for accuracy, relevance, inclusivity, copyright compliance and alignment with approved course outcomes.
10.3 AI shall not replace essential practical, laboratory, fieldwork, interpersonal or independent-learning experiences.
10.4 Course outlines and assignment briefs should specify whether AI use is prohibited, permitted for specified support, or permitted with disclosure.
10.5 Staff must not present AI as infallible or use AI-generated material without professional review.
11.1 AI may support formative assessment, feedback, learning analytics, rubric-based marking and assessment administration, subject to human oversight.
11.2 AI-assisted grading or feedback that may affect marks, progression, awards or disciplinary status must be reviewed by competent academic staff. The staff member remains accountable for the final decision.
11.3 AI detectors shall not be the sole evidence for finding academic misconduct. Allegations must be considered through the applicable fair process and on appropriate evidence.
11.4 Assessment instructions shall state the permitted AI-use category and disclosure expectations. Students must follow the rules for each assessment.
11.5 Clear rubrics and safeguards shall reduce bias, error and inconsistent treatment. Students retain access to applicable clarification, review and appeal procedures.
11.6 High-stakes grades, examination results and disciplinary decisions shall not be released or determined solely by AI without authorised human validation and established controls.
12.1 AI may support literature discovery, research design, coding, translation, transcription, analysis, visualisation and language editing, provided the researcher retains methodological control and accountability.
12.2 Researchers must verify references, quotations, data, calculations, code, interpretations and claims. AI must not be used to fabricate data, participants, results, sources or peer-review evidence.
12.3 AI tools shall not be treated as authors where authorship requires human accountability. Material AI assistance shall be disclosed according to University, funder, journal, publisher and professional requirements.
12.4 Required research ethics approval must be obtained before relevant data collection or processing. Identifiable or confidential research data must not be uploaded to AI services unless authorised and legally compliant.
12.5 Research teams shall document material AI use where needed for reproducibility, audit or publication disclosure, including the tool and purpose, nature of assistance and human verification.
12.6 Research ethics, intellectual-property and academic-integrity requirements continue to apply to theses, dissertations, publications, consultancy and funded projects.
13.1 AI may support records management, scheduling, workflow automation, student support, information retrieval, communication, planning and reporting.
13.2 Institutional use shall be limited to systems approved through applicable ICT, procurement, data-protection and information-security processes.
13.3 AI-generated official letters, reports, statistics and recommendations must be checked by an authorised officer.
13.4 Decisions with significant effects on a person's rights, status, opportunities or access to services shall not be delegated solely to AI. Meaningful human review and applicable correction or appeal routes must be available.
13.5 Staff must not use AI to disclose information or alter official records outside approved procedures.
14.1 AI use shall comply with applicable Nigerian law, including the Nigeria Data Protection Act 2023, and University data-protection and security procedures.
14.2 Users must classify information before using AI. Student and staff records, passwords, examination materials, confidential financial or legal information, unpublished research and restricted data must not be entered into public AI systems without explicit authorisation and suitable safeguards.
14.3 The University shall apply appropriate data minimisation, access controls, secure storage, retention limits, vendor due diligence and incident-reporting arrangements.
14.4 Providers and systems handling University data shall be assessed for data retention, model-training use, security, access, processing location, contractual terms and deletion arrangements.
14.5 Suspected exposure, loss or unauthorised processing of data through AI must be reported promptly through designated University ICT/security and data-protection channels.
14.6 Users must not assume that information submitted to a third-party AI service is private or will not be retained.
15.1 AI use shall comply with applicable copyright law, licences, contractual commitments, research agreements and University intellectual-property rules.
15.2 AI-generated output is not automatically original, accurate, free of third-party rights or owned by the user or University.
15.3 Users must respect authors' and creators' rights and attribute third-party sources where required.
15.4 Before commercialising, publishing or distributing AI-assisted material, users and responsible units shall consider ownership, licence, confidentiality, originality and disclosure requirements.
16.1 AI systems acquired, developed or deployed for institutional use shall be reviewed by the ICT Directorate and relevant procurement, legal, data-protection, cybersecurity, finance and user units.
16.2 Review should consider purpose, benefit, cost, vendor reliability, accessibility, interoperability, data protection, security, bias, transparency, human oversight, support and exit arrangements.
16.3 Subject to institutional need and budget, systems may include AI-enabled learning-management platforms, tutoring and student-support tools, research and data-analysis platforms, library retrieval systems, academic-integrity tools, administrative automation, career guidance and entrepreneurship tools.
16.4 Products mentioned in training or policy discussions are illustrative; their mention does not constitute University endorsement or procurement approval.
16.5 An inventory of institutional AI systems shall be maintained, with a responsible unit assigned to each material system.
Senate shall exercise its academic governance responsibilities relating to teaching, assessment, research and academic integrity, and consider substantive amendments where required.
Management shall oversee implementation, designate responsible officers, facilitate training, consider resource requirements and submit matters requiring Senate or Governing Council action to the appropriate authority.
The University shall maintain an AI Ethics and Compliance Committee. Membership shall include representatives of University Management, ICT Directorate, CTLE, the University unions, Legal Unit, Quality Assurance, Student Affairs and other relevant units. The appropriate authority shall approve its chairmanship, tenure, quorum and reporting arrangements.
The Committee shall develop operational guidance; advise on AI system approval and risk; coordinate compliance monitoring and certification records; receive or refer reports of misuse; recommend fair corrective action; review incidents and complaints; promote equity, privacy, security and academic integrity; and submit an annual implementation report to Management and Senate.
CTLE shall coordinate or support pedagogical training, staff development, responsible instructional use, assessment design and evaluation of AI-supported teaching and learning.
The ICT Directorate shall coordinate technical implementation, infrastructure, system inventory, vendor relationships, support, access controls, cybersecurity and AI-related incident response with relevant units.
Deans, heads of department and unit heads shall communicate the Policy, identify training needs, clarify course-level rules and refer concerns through established procedures. Every user shall complete required training, verify AI outputs, disclose assistance where required, protect University information and report suspected breaches.
| Phase | Indicative period | Activities |
|---|---|---|
| I: Adoption and awareness | Months 0–3 | Communicate the Policy; establish or confirm the Committee; conduct sensitisation; identify priority tools and initial controls. |
| II: Capacity and infrastructure | Months 4–12 | Deliver mandatory staff certification; provide digital literacy programmes; prepare guidelines; assess infrastructure and approved systems. |
| III: Integration and improvement | Months 12–24 | Expand suitable AI integration; evaluate assessment and operational outcomes; monitor and review implementation. |
Implementation costs may include infrastructure, software licences, learning-management systems, staff and student training, professional development, cybersecurity, data protection, technical support, accessibility, monitoring and policy review. Funding may be sought through University allocations, eligible TETFund interventions, research and innovation grants, partnerships and donor support, subject to applicable conditions and procurement rules.
The ICT Directorate shall work with the Bursary, Planning, CTLE and relevant units to prepare a financial estimate of annual implementation plan for consideration through established budgetary processes.
The University shall monitor implementation using measurable indicators, including:
The Committee shall submit an annual report to University Management and Senate. Monitoring shall be proportionate, respect privacy and due process, and avoid unnecessary collection of personal data.
21.1 Breach of this Policy or failure to complete required certification may lead to corrective action or disciplinary proceedings under applicable University regulations, employment conditions, academic rules and law.
21.2 The University shall prioritise education and remediation where appropriate. Deliberate, repeated, dishonest or harmful conduct may warrant formal disciplinary action.
21.3 Responses, depending on seriousness and applicable rules, may include guidance or written reminder; mandatory retraining or reassessment; correction or re-evaluation of affected work where permitted; temporary restriction from a particular system where necessary; or referral under established staff or student disciplinary procedures.
21.4 Restrictions affecting promotion, grants, leadership, examination setting, grading, supervision or other duties may be imposed only where authorised by applicable regulations and following due process. They shall not arise automatically from an allegation.
21.5 The Committee may investigate or refer concerns within its mandate and recommend proportionate action, but shall not displace established disciplinary bodies.
21.6 A person affected by an allegation or sanction shall be informed of the case, given a fair opportunity to respond and have access to applicable review or appeal procedures.
21.7 The University shall communicate the certification deadline, provide reasonable access to training and establish a process for exceptional circumstances. Any sanctions for non-compliance shall follow University rules and due process.
Users may report suspected misuse, unsafe deployment, privacy or security incidents, unfair automated outcomes or other concerns through designated University channels. Reports shall be handled confidentially to the extent practicable. The responsible unit shall assess urgency, preserve relevant evidence, protect affected persons and refer the matter to the appropriate authority. Challenges to AI-assisted decisions shall receive meaningful human review under applicable procedures.
The Policy shall be published on the official University website and communicated through appropriate channels. Staff and students shall be informed during induction and training. Accessible formats and reasonable support should be provided where practicable for users with disabilities, limited connectivity or other barriers.
The Policy shall be reviewed at least once every twelve months, and earlier where required by NUC direction, changes in Nigerian law, a material incident, significant technological developments or evidence that the Policy is ineffective. Substantive amendments shall be submitted to the appropriate University authorities, including Senate where required.
Implementation shall be consistent with applicable requirements, including:
UEE adopts this Policy as its institutional framework for responsible AI use in teaching, learning, assessment, research, innovation and administration. All units and users within its scope shall support its implementation. AI shall enhance human capability and institutional effectiveness, not remove human responsibility. Its use shall remain ethical, transparent, inclusive, secure and consistent with academic integrity, data protection, applicable law and the University's educational and entrepreneurial mission.
| Approved and adopted by | University Senate, University of Education and Entrepreneurship, Akamkpa |
|---|---|
| Meeting | 8th Regular Meeting of the University Senate |
| Date | Thursday, 29 January 2026 |
| Venue | Senate Chamber, University of Education and Entrepreneurship, Akamkpa, Cross River State, Nigeria |