/>iLast week, we outlined the building blocks for a strong IG program. Now that you’ve laid the groundwork, it’s time to bring your IG program to life. The ARMA IGIM framework emphasizes operational execution in three key areas:
- Procedural Framework
- Capabilities
- Information Lifecycle
These domains are where your framework tangibly interacts with AI systems, ensuring tools like machine learning models work with clean, structured data.
1. Procedural Framework
Your Procedural Framework establishes consistent policies, roles, and accountability measures. For AI, having standardized processes ensures that models produce reliable outputs.
Key for AI Adoption:
Without uniform procedures, AI systems can misinterpret data. For example, inconsistent naming conventions in datasets can skew analytics or predictions.
Actionable Tip: Create a policy requiring metadata tagging for all incoming data to improve accessibility for AI models.
2. Capabilities
Capabilities refer to the tools and technologies that power your IG program. AI tools are only as good as the systems they connect with.
Key for AI Adoption:
Role-based access controls prevent sensitive data from being used irresponsibly in AI training, while metadata management enhances the searchability of training datasets.
Example: A retail company equipped its e-commerce platform with AI product recommendations. By integrating IGIM-driven policies on access control and metadata, they ensured only accurate, permissible data informed the algorithms.
3. Information Lifecycle
AI relies on data that evolves through its lifecycle—from creation to disposition. The Information Lifecycle ensures that outdated or incorrect data doesn’t compromise AI tools.
Key for AI Adoption:
By defining retention schedules, organizations ensure AI models are trained on relevant data, reducing errors and increasing trust in outputs.
Next week, we’ll discuss how to sustain your IG program, enabling continuous innovation with AI.
What can you do now? Make sure that your data policies, tools, and lifecycle management strategies are aligned to support your AI-driven initiatives.
