How to Write an ANECA Verification Report with AI — 2026 Guide
Business11 min read·By Guillermo Gómez Benavides

How to Write an ANECA Verification Report with AI — 2026 Guide

An ANECA Report costs €10,000-€50,000 if commissioned to an academic consultancy. With AI, a Spanish university can produce the complete first version in hours and dedicate the academic team to personalization.

The ANECA Report: the most feared document in Spanish higher education

To verify a new Bachelor's, Master's, or Doctoral degree at a Spanish university, the institution must submit to ANECA (National Agency for Quality Evaluation and Accreditation) a Verification Report that complies with the 9 official criteria of the VERIFICA protocol. The typical document runs 200-400 pages, covering everything from academic justification of the degree to the quality assurance system, and must be coherent across every section.

The traditional process: a faculty commissions the report from a specialized academic consultancy, pays €10,000-€50,000 per degree, waits 3-9 months, and then spends several more months personalizing the result. The bottleneck is rarely academic knowledge (which already exists in the faculty): it's drafting 300 pages with the exact structure ANECA requires.

This is where AI changes the equation entirely.


What the ANECA Verification Report is

It is the official document a university must submit to verify an official university degree under:

  • RD 822/2021 (Bachelor's and Master's degrees)
  • RD 99/2011 (Doctoral programs)
  • ANECA's VERIFICA protocol

Once verified, the report is the reference document governing the degree throughout its lifetime. Any significant modification (new curriculum, new mode, new center) requires submitting a modification report that also goes through evaluation.

Every 6 years (Bachelor's) or 4 years (Master's and Doctoral), the degree also undergoes an accreditation process verifying that the report's commitments are being met.


The 9 official ANECA criteria

Criterion 1: Degree description

  • Name, knowledge branches, ECTS credits, mode (in-person, online, hybrid)
  • Responsible and collaborating centers
  • Institutional agreements where applicable

Criterion 2: Degree justification

  • Academic, professional, and scientific justification
  • National and international external references
  • Internal and external consultation procedures

Criterion 3: Competences and learning outcomes

  • Basic, general, transferable, and specific competences
  • Learning outcomes aligned with MECES (Spanish Higher Education Qualifications Framework)
  • Competence-to-subject mapping

Criterion 4: Access and admission

  • Prior information systems
  • Access requirements and admission criteria
  • Student support and orientation
  • Credit recognition

Criterion 5: Curriculum planning

  • Curriculum structure
  • Modules, subjects, and courses with associated competences
  • Teaching activities, methodologies, and assessment systems
  • Mobility where applicable

Criterion 6: Teaching staff

  • Faculty roster with research and professional experience
  • Research milestones and credentials
  • Workload and category balance

Criterion 7: Material resources and services

  • Infrastructure, laboratories, library
  • Technology platforms
  • Support services

Criterion 8: Projected results

  • Estimated performance indicators (graduation rate, efficiency, dropout)
  • Justification based on similar degrees

Criterion 9: Quality assurance system

  • Responsible structure
  • Evaluation and improvement procedures
  • Public information mechanisms

Why AI dramatically accelerates this process

A Verification Report is the ideal use case for multi-agent architecture:

  1. It's very long (200-400 pages)
  2. It has a rigid, well-known structure (9 criteria with fixed subcriteria)
  3. It requires coherence across criteria (the competences in Criterion 3 must appear mapped in Criterion 5; the resources in Criterion 7 must justify the results in Criterion 8, etc.)
  4. It repeats information in different formats (the same competence appears in tables, prose, and subject mapping)
  5. It is generated many times (each university has 50-200 active degrees)

Generic ChatGPT fails here for one specific reason: it loses coherence between criteria when the document exceeds 30 pages. Specialized AI with persistent memory across sections maintains it from page 1 to page 400.


The step-by-step process

Step 1: Upload reference materials

The most powerful thing you can upload is a previously verified report from your university — even from a different degree. Why: it contains your quality assurance system, your typical academic staff, your institutional infrastructure, your internal regulatory references. The AI replicates all of that in the new report without you having to re-write it.

Additional materials that significantly improve the result:

  • Reports from similar degrees at other universities (external academic reference)
  • Framework document for the new degree (objectives, justification, initial proposal)
  • Draft curriculum with credits and subjects
  • Faculty CVs
  • Current institutional data (QA system, recent quality indicators)

Step 2: Define the degree

Specify:

  • Exact degree name
  • Knowledge branches
  • Total ECTS credits
  • Mode (in-person, online, hybrid)
  • Responsible center
  • Whether it's new or a modification

Step 3: Generate the complete report

The AI produces the structured document across the 9 criteria. Typical time: 15-30 minutes for a 250-page report.

What you get:

  • Complete report in Word with automatic table of contents
  • Mandatory tables filled in (competence map, curriculum, faculty)
  • Quality assurance system adapted to your university
  • Projected indicators justified with references

Step 4: Internal academic review

This step is irreplaceable. The academic team responsible for the degree reviews:

  • Degree justification (the section ANECA examines most thoroughly)
  • Specific competences and their mapping to subjects
  • Curriculum with its teaching activities and methodologies
  • Projected results (especially the justification of the rates)

Review time is 2-4 weeks. Significantly less than the 12-20 weeks of review when starting from an external consultancy draft.

Step 5: Institutional approval

The report goes through:

  • Center Academic Committee
  • Center Board
  • University Studies Committee
  • Governing Council

This circuit cannot be shortened by AI. But the document arrives more mature at the committees, reducing iteration.

Step 6: Submission to the educational administration

The report is uploaded to the electronic portal of the relevant educational administration (Ministry or regional government), which forwards it to ANECA for evaluation.

Step 7: ANECA evaluation

ANECA issues its report in 3-6 months. Possible outcomes:

  • Favorable report: the degree is verified.
  • Favorable report with recommendations: the degree is verified; improvements are incorporated in the next modification.
  • Unfavorable report: significant changes are required before resubmission.

The favorable-report rate is high when the report is well-prepared. Rejected reports usually fail because of generic content, lack of specific justification, or internal inconsistencies — exactly what AI grounded in your sources avoids.


Special cases

Modifying a verified report

When you want to change something in an already-verified degree (curriculum, mode, name), you submit a modification document to ANECA marking the changes against the current version. AI generates this document by uploading:

  • Current verified report
  • List of changes you want to introduce
  • Justification for each change

Time: hours instead of weeks.

Accreditation (ACREDITA)

Every 4-6 years the degree undergoes accreditation, which verifies that the report's commitments are being met. It requires a self-assessment that AI can generate from:

  • Verified report
  • Recent indicators (rates, satisfaction, employability)
  • Previous monitoring reports

Doctoral programs (RD 99/2011)

Doctoral program reports follow a slightly different structure (RD 99/2011 instead of RD 822/2021), but the principle is the same: 7 mandatory sections, high internal coherence, large amounts of structured information.


Times and costs compared

PathCost per degreeTime
Specialized academic consultancy€10,000 - €50,0003-9 months
In-house from scratchPersonnel cost (3-6 months)4-12 months
Downloaded template + adaptation€0 - €1,0004-8 months
Specialized AI + internal review€50 - €5006-12 weeks

For a university with 50 active degrees updating reports every 4-6 years, this can mean saving €300,000-€1,500,000 per year in external consultancy.


Conclusion

The ANECA Verification Report is one of the clearest, highest-ROI use cases for generative AI specialized in long documents. It is not a case where AI replaces academic knowledge: it is a case where AI eliminates the manual work of drafting 300 structured pages, freeing the academic team to focus on what genuinely adds value — the degree proposal, the teaching methodology, and the program justification.

For Spanish vice-rectorates, deans' offices, and university quality services, adopting AI in this process is no longer optional: it is the only way to manage the degree portfolio without externalizing institutional knowledge or spending fortunes on academic consulting.

Generate reports with AI

Try the Nomos tool focused on what you just read.

Open tool

Ready to try it?

200 free credits when you sign up. No card required.

Get started free
GG
Guillermo Gómez Benavides

Founder of Nomos

Guillermo Gómez Benavides is the founder of Nomos, where he builds AI tools for drafting technical documentation and responding to public tenders and RFPs. He writes about government contracting, AI for long documents, and productivity.