REPOSITORY HEALTH SERIES
Is Your Repository Ready for AI?
Why every document repository needs a health check, and why an active repository needs to be watched around the clock.
of AI projects unsupported by AI-ready data will be abandoned through 2026.1
GARTNER, FEBRUARY 2025
01 / THE EVIDENCE
AI is failing on content, not on models
Most organizations are not short of information. They hold years, often decades, of valuable content in document repositories. Much of it is hard to find, inconsistently structured, poorly classified, duplicated or out of date. AI does not repair that. It inherits it, and returns confident answers drawn from the wrong version of the truth.
of organizations do not have, or are unsure they have, the data management practices AI requires.2
or more of generative AI projects were forecast to be abandoned after proof of concept. Poor data quality led the list of causes.3
plus of agentic AI projects will be canceled by the end of 2027, on cost, unclear value or inadequate risk controls.4
is the least that poor data quality costs the average organization every year.5
What is actually in the repository
Share of all stored data6
- 52% Dark. Unclassified. Its content and value are unknown to the organization.
- 33% ROT. Redundant, obsolete or trivial, and known to be useless.
- 15% Business critical. The share identified as genuinely valuable.
of the working week is spent looking for internal information, or for a colleague who knows where it is.7 An AI assistant pointed at the same repository is searching the same mess, only faster.
02 / WHY 24/7
A health check is a snapshot. Your repository is not.
Every batch that lands in a live repository changes its condition: new duplicates, missing metadata, superseded versions, permissions that no longer match the content. A score taken in January says little about June. Yet most organizations cannot see their content as it changes, and many cannot see it at all.
is the global average time to identify and contain a data breach. Problems nobody is watching for stay hidden for most of a year.8
average breach cost, global
average breach cost, United States
have only partial visibility into where their data is stored9
report real-time scanning capability9
cannot scan their unstructured data at all9
of organizations with an AI-related breach lacked proper AI access controls8
| One-time assessment | 24/7 monitoring with CTS | |
|---|---|---|
| What you know | Health on the day of the scan | Health now, re-scored as each batch is ingested |
| New problems | Found at the next audit, if there is one | An alert the moment a KPI falls below your threshold |
| Remediation | A list of recommendations | Issues worked in order of risk; routine fixes automatic, judgement calls flagged |
| Over time | A single baseline that ages | A score you can track and prove |
03 / THE HEALTH CHECK
Measure before you modernize
Gartner reports that 59% of organizations do not measure data quality at all.5 The AITS Content Tracking System (CTS) closes that gap with a single repository health score: a composite index built from the KPIs you define and weight to your priorities. AI does the measuring, but the measuring stick is yours.
YOU DEFINE
Your KPIs
YOU SET
Your weights
CTS PRODUCES
One repository health score
Eight assessment areas
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01
Content
Document types, volumes, age, duplication and obsolete material.
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02
Structure
Folders, libraries, collections and document types; inconsistencies and gaps.
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03
Metadata
Availability, consistency and usefulness of classifications and identifiers.
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04
Search
Barriers that make information hard to locate, retrieve or navigate.
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05
Data Quality
Duplicate, incomplete, conflicting or potentially obsolete information.
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06
Security
Access, permissions and sensitivity controls that govern safe use and sharing.
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07
Governance
Ownership, classification, retention and lifecycle considerations.
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08
AI Readiness
Whether the environment is a sound foundation for AI search, retrieval and automation.
Start with the repository you already have
AITS is repository agnostic. The Health Check begins with the environments you already depend on and scores them against your metrics. No platform replacement, no migration.
Enterprise content management
Microsoft SharePoint, OpenText, IBM FileNet, Hyland OnBase, Alfresco
Cloud and specialized platforms
Box, Google Workspace, M-Files, Laserfiche, iManage
File and application stores
Network shares, NAS, Azure Blob, Amazon S3, legacy line-of-business systems
04 / AROUND THE CLOCK
From assessment to continuous assurance
The Health Check gives you a scored baseline. CTS keeps it true. As batch processes ingest new content, CTS continues to watch overall health, re-scores the repository and raises an alert whenever a KPI falls below an acceptable threshold. When you are ready, it can remediate as well.
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STEP 1
Monitor
Health is watched continuously as new batches are ingested.
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STEP 2
Re-score
The health score is recalculated against your KPIs and weights.
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STEP 3
Alert
You are told whenever a KPI drops below its threshold.
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STEP 4
Remediate
Issues are worked in order of risk. Routine fixes are automatic; judgement calls go to your team.
A practical path from repository to results
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1 Discover
Understand the repository, its content, structure, processes and operational requirements.
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2 Assess
Score information quality, metadata, search, governance, security and AI readiness against your KPIs.
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3 Prioritize
Identify the improvements with the greatest practical value, without assuming a platform replacement.
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4 Optimize
Implement improvements and introduce automation, analytics and governed AI where they make sense.
From repository health to AI opportunity
With a measured, trusted foundation in place, organizations can pursue AI search across approved sources, knowledge assistants, document intelligence that extracts, classifies and summarizes at scale, metadata enrichment and intelligent automation, all under governed AI controls for security, privacy, access and human oversight.
The caution is simple: do not introduce AI for its own sake. Find where it will deliver measurable business value, and prove it with a score you can track.
Find out your repository health
Your repository may already hold the information needed for the next generation of knowledge management and AI. Book an AITS Repository Health Check to learn how ready it really is, then keep it that way with CTS monitoring.
A scored baseline
One health score, built on your KPIs, with the detail behind it.
Prioritized actions
Actionable recommendations, ordered by practical value.
Ongoing assurance
Monitoring, re-scoring and alerts as your content changes.
SOURCES
- Gartner, "Lack of AI-Ready Data Puts AI Projects at Risk," Feb. 2025. View source
- Gartner survey of 1,203 data management leaders, July 2024 (reported Feb. 2025). View source
- Gartner, "30% of Generative AI Projects Will Be Abandoned After Proof of Concept by End of 2025," July 2024. View source
- Gartner, "Over 40% of Agentic AI Projects Will Be Canceled by End of 2027," June 2025. View source
- Gartner, Data Quality research; cost figure from Gartner research, 2020. View source
- Veritas, Global Databerg Report (Vanson Bourne; 2,550 respondents, 22 countries), 2016. View source
- McKinsey Global Institute, "The Social Economy," 2012. View source
- IBM, Cost of a Data Breach Report 2025. View source
- Cloud Security Alliance and Thales, "The Rise in Unstructured Data and AI Security Risks," Nov. 2025 (210 IT and security professionals). View source
Monetary figures in USD.