Artificial intelligence is only as reliable as the information it draws upon. As organisations accelerate the adoption of AI, many are discovering that data alone is not enough. Without strong, consistent metadata to provide context, provenance and accountability, even sophisticated systems can produce outputs that are difficult to trust or defend. Understanding the role of metadata is therefore not a technical exercise. It is a governance imperative.
What is metadata?
Simply put metadata is data that describes and gives information and context about other data.
Digital information and data depend on metadata for contextual understanding and management. Without it, data cannot be managed, understood or relied upon. There are different types of metadata at different levels of aggregation.
Descriptive metadata – Titles, descriptive text, keywords and classifications that enable reliable discovery and retrieval of information.
Provenance and process metadata – Details about who created the information, the business process it relates to, when it was captured into a system, and the events that record changes over time. This supports trust, integrity and authenticity.
Technical metadata – Information required to manage, render, preserve and maintain digital objects appropriately over time.
Security and access metadata – Classifications and controls that identify sensitive, confidential or privacy-protected information and define access permissions.
Data element metadata – Definitions and contextual information for specific data elements across datasets, systems and platforms, ensuring consistency and shared understanding.
Relationship metadata – Information that describes connections between entities, records, systems and datasets, enabling structured linkage across environments.
Metadata is key in understanding:
- Where data originated
- How it was created
- Who created it
- When it was created
- Why it was created.
Recordkeeping metadata tells us everything we need to know about information.
Recordkeeping Metadata
Information and records management practitioners across the globe have been touting the benefits of recordkeeping metadata for a very long time. Metadata models have been developed and requirements for records metadata aredocumented in ISO Standards, such as, ISO 23081 Series. Metadata for Records.
Recordkeeping approaches to metadata are designed to establish trust of information assets and to demonstrate why information can be relied upon when called into question. The outcome – is confidence in the legitimacy, accuracy, reliability, integrity and authenticity of the data.
The application of recordkeeping metadata has traditionally been addressed in electronic document and records management systems (EDRMS). These systems were designed with recordkeeping metadata to ensure compliance with relevant standards and regulatory changes. The information environment is constantly evolving. Use of business systems for specific functions, collaborative platforms, content management platforms and AI have disrupted how information and records are managed with fragmentation across diverse systems and platforms.
Consequently, metadata approaches frequently lack integration, leading to disconnected datasets and isolated information across business systems, collaborative platforms, and recordkeeping solutions.
Metadata and AI
Metadata is critical in the age of Artificial Intelligence (AI). A systematic and coordinated approach to its application and interpretation is essential across organisations.
This requires a comprehensive, organisation-wide strategy for designing and deploying metadata schemas. In today’s AI-driven landscape, it is increasingly critical for organisations to ensure the reliability of outputs, be able to provide clear explanations for decisions, and maintain transparency under examination. High-quality, well-governed metadata is fundamental to achieving this.
The Reality
The reality though is that in many organisations the management of metadata has been disjointed. Often there is no strategic direction and there are multiple approaches to metadata management with no integration.
Organisations, are struggling with:
- Poor quality data
- Information that is fragmented, scattered, poorly described, and duplicated.
- Inability to track the provenance of information and the relationships between sources.
- The volume of information and data is increasing across cloud environments, personal drives, legacy databases, and active systems.
- The different types of metadata that needs to be managed.
These issues make it very hard for organisations to effectively implement AI without exposing the organisation to risks such as:
- Reinforcing hidden bias in the data.
- Low trust in the outputs.
- The inability to defend how decisions were made can expose the organisation to legal and regulatory ramification and reputational damage.
The Solution
There may not be a magic bullet, but one thing is for sure, good quality metadata is key and a strategic, integrated and cohesive approach to this is needed.
Incorporating recordkeeping metadata within organisational metadata frameworks is essential. Metadata models should be designed to be scalable, creating relationships between people and organisations, the business being transacted, the technologies being used, and the mandates, policies and rules that govern them.
Recordkeeping metadata will:
- provide the relationships between data elements,
- track the provenance of the data over time,
- identify systems in which information is used, who has used it, and relationships to other information sources, and
- will assist in reducing over retention of data ensuring older data is disposed when necessary, reducing the risk of any infection of AI models.
A key component of the solution is the use of organisational metadata registries in which tailored metadata schemas are defined, documented and governed. The registry becomes the foundation that connects metadata schemas, systems, teams and the governance and management of schemas in one location.
As a result, organisations can look at the data and understand where it came from, why it can be relied upon and have trust in the outputs and the decisions made.
As ISO 23081 reminds us, effective metadata regimes are not static artefacts but living frameworks. They evolve alongside records, accommodating new metadata as management needs change over time. Recognising and designing for this dynamism is essential if metadata is to continue supporting reliable, meaningful, and accountable recordkeeping in an increasingly complex digital environment.
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About the Author
Adelle Ford is a Director at Recordkeeping Innovation Consulting, bringing decades of experience supporting organisations with information management, regulatory compliance, and digital recordkeeping solutions.
She specialises in information governance, digital preservation, and enterprise content management, with expertise spanning Microsoft 365 implementations and metadata standards. Adelle holds a Graduate Diploma in Data Management and is currently studying AI Governance, focusing on the intersection of artificial intelligence, information integrity, and compliance.