AI, Data Provenance, and the Future of Metadata

As we enter 2025, it’s remarkable to reflect on how much technology has evolved in just 25 years. The pace of technological advancement since the turn of the century has been breathtaking, transforming how we do business and interact with the world. One topic that continues to dominate recent tech conversations is artificial intelligence (AI). However, the hype has begun to settle, making way for a more pragmatic focus on how AI can deliver tangible benefits. This means harnessing AI for operational efficiencies and cost reduction in the media and entertainment industry.

But AI doesn’t work in a vacuum. It depends on high-quality, accurate, and diverse data. As metadata management specialists, data is our lifeblood. We’re especially focused on data provenance—a concept critical for ensuring transparency, reliability, and accountability in AI systems.

Understanding Data Provenance

Data provenance refers to the complete record of a dataset’s journey, from its origin to its current state. It’s the story of how data has been collected, transformed, and used. For AI systems, data provenance is essential. It ensures that decisions based on AI are grounded in trustworthy, well-documented data.

A recent Harvard Business Review article highlighted that effective decision-making isn’t just about aggregating data or applying algorithms. It also involves selecting credible data sources, envisioning possibilities beyond the immediate facts, and making nuanced judgments—areas where humans excel. Data provenance plays a vital role in this process, offering a clear view of where data comes from and how it’s been handled.

Tracking Metadata with the Atlas Platform

At the heart of our work is the Atlas platform, which empowers our customers to manage and prioritise metadata effectively. Atlas provides:

• Tools to track data sources and attributes.
• Insights into data lineage, showing the lifecycle of content records.
• Relationship mapping to understand connections between data points.

For example, users can view data sources, mapped content IDs, and merged records, ensuring their metadata is not only accurate but also actionable. This capability is especially crucial as we support customers in aligning their metadata with AI initiatives.

Data Governance: A Pillar of Success

Accurate, complete, and consistent data is the foundation of AI success. As data stewards, we take this responsibility seriously. Titles, release dates, cast, and crew information are factual elements that must be meticulously managed. Without strong data governance, it’s impossible to aggregate, normalise, or enhance data to meet our customers’ needs.

Our commitment to data governance ensures that:

• Metadata repositories are of the highest quality.
• Data gaps and inconsistencies are minimised.
• Customers can trust the data to drive their strategic goals.

AI and Metadata: Two Perspectives

We approach AI in two complementary ways:

1. Enhancing Our Platform: We use AI to streamline metadata management, reduce repetitive tasks, and accelerate quality assurance. Automated processes help assess data quality, map content IDs, and resolve ambiguities, enabling us to deliver even greater value to our customers.
2. Supporting Customer Initiatives: We ensure that the fire hydrant of data that we manage is fit for purpose. High-quality data is essential for customers training AI models to deliver more data such as suitability ratings, tags or event markers effectively. Poor-quality data leads to unreliable outcomes, but our focus on clean, standardised metadata mitigates these risks. 

Looking Ahead

As we navigate 2025, our goals remain clear: to provide metadata solutions that support our customers’ evolving needs. The media and entertainment industry faces constant pressure to manage costs and improve efficiency. Clean, reliable data is the linchpin of these efforts. We’re excited to continue innovating and evolving our capabilities to meet these challenges head-on.

Change is inevitable, and with it comes opportunity. Here’s to a year of growth, innovation, and collaboration as we embrace the future of AI and metadata management.