Information Governance | Intelligent Information Management (IIM) | Artificial Intelligence (AI)

• Share:

Throughout my career in information governance, information management, and data governance, I’ve contributed to the development of industry frameworks and bodies of knowledge. These structured approaches help organizations navigate complex challenges and reduce risk. As AI reshapes our information landscape, it’s worth examining how our existing frameworks should evolve.

The Enduring Value of Frameworks

Frameworks provide guidance that can help organizations avoid starting from “square one.” They represent the accumulated wisdom and best practices that can significantly improve the probability of success when implementing solutions.

The value of frameworks lies in their ability to:

• Help organizations assess readiness
• Provide methods to analyze complex challenges
• Offer benchmarks for measuring progress
• Reduce risks via standardized structured approaches

Today, there are numerous frameworks across countless knowledge domains and industries, targeted towards a plethora of business scenarios and use cases. These frameworks continue to help organizations better manage risk in a structured and thoughtful manner.

Frameworks as Living Documents

It’s important to understand frameworks as reference tools, which prescribe how to approach developing a solution. Therefore, frameworks can serve as benchmarks and guides — not rigid “marching orders.”

While frameworks provide valuable structure, they must be recognized as point-in-time snapshots. The most effective frameworks evolve to address emerging challenges and technologies. This adaptability is particularly important in the rapidly evolving landscape of AI, where new capabilities and risks emerge regularly.

Identifying Framework Gaps in the AI Era

When examining existing information management frameworks in the context of AI, some key gaps become apparent:

1. AI governance models: While we have robust frameworks for information governance, AI-specific governance models are still emerging
2. Ethics frameworks: Traditional information management frameworks often lack specific guidance on ethical considerations that AI raises
3. Risk assessment models: Updated approaches are needed to evaluate the unique risks of an AI implementation, including privacy

These gaps present opportunities for industry professionals to contribute to the evolution of AI frameworks in the context of their knowledge domain, industry, and area of practice. Anecdotal evidence points to the fact that many professional associations are doing just that, along academia, consulting firms, and public organizations.

Keeping frameworks “ever-green” by responding to changes in technology changes, can help ensure that frameworks have business value with respect to adaptability, applicability, usability, and utility.

Recent Work on Framework Development

In my current work, I’ve been developing for my clients, enterprise-wide information architecture frameworks that include principles, framework elements, and a checklist to help assess different solutions and systems from an information governance and data governance perspective. The frameworks focus on key areas such as governance, digital ethics, data quality, privacy, security, interoperability, change management, and risk management.

The frameworks help my clients evaluate whether their initiatives align with their organizations’ strategies, goals, objectives, and outcomes, thereby providing a 360-degree view of stakeholder considerations before moving forward with technology investments.

Concluding Thoughts: The Future of Frameworks

Looking ahead, our industry must continue to develop and refine frameworks that address the unique AI-related challenges, risks, and opportunities, while preserving the core principles that have guided us effectively thus far. As these frameworks evolve, they will serve as critical tools for navigating the increasingly complex intersection of AI, information governance, data governance, and information management, thereby enabling organizations to proceed with greater confidence, clarity, and effectiveness.

This blog post is based on an original AIIM OnAir podcast. When recording podcasts, AIIM uses AI-enabled transcription in Zoom. We then use that transcription as part of a prompt with Claude Pro, Anthropic’s AI assistant. AIIM staff (aka humans) then edit the output from Claude for accuracy, completeness, and tone. In this way, we use AI to increase the accessibility of our podcast and extend the value of great content.

About Amitabh Srivastav, PMP, CIP, IGP, AIIM Fellow & Ambassador

Amitabh Srivastav is an expert in information governance and digital transformation who brings over 25 years of experience to the table. As the Chief Digital Officer and VP of Compliance & Risk Management at HELUX.ai, Amitabh helps organizations navigate the complex world of digital transformation, Microsoft solutions, and compliance. His expertise spans governance, automation, and risk management, and he’s a respected voice in the field - regularly presenting at major industry conferences and contributing to ISO standards. He’s an AIIM Fellow and holds multiple advanced degrees in computer science and project management, along with professional certifications including PMP, CIP, and IGP. Amitabh is also deeply involved in shaping the future of information management through his work on various boards and committees, including AIIM True North Chapter and the ARMA International Education Foundation. He is also an AIIM Ambassador.

• ** Connect with Amitabh Srivastav, PMP, CIP, IGP, AIIM Fellow & Ambassador **