AI Readiness Assessment: Preparing Your Organization's Unstructured Data for the Future

I recently had the pleasure of hosting a conversation with Rob Bogue, the core author of AIIM's new resource "Organizational Readiness for Generative AI: Leveraging Unstructured Data for Success." This assessment focuses on how to prepare unstructured data for AI implementation. In this blog post, I'll share key insights from our discussion and highlight the importance of this tool for information management professionals.

The Unique Value of Unstructured Data for AI

AI becomes infinitely more useful and reliable when married with your organization's unstructured data. As Rob explained, the assessment explores the unique "intersection of artificial intelligence and what your organization knows." In other words, your organization's information is what makes AI models and output more specific, accurate, and applicable.

However, AIIM's Industry Watch found that while organizations may be confident in their capacity to take advantage of AI, they often feel significantly less confident in the quality of their information and data hygiene processes.

How the Assessment Was Developed

Rob and I started discussing the need for a practical AI tool in early 2024. Rob had been inundated with questions from his customers interested in generative AI, but needing guidance on how to responsibly and successfully implement generative AI. During these conversations, Rob noticed that many of the practices required for good AI implementation are inforamation management best practices.

"One of the things that struck me about those customer conversations was it's the kind of things that information manager friends have been doing for awhile," Rob said. "It's managing change, getting content access, and managing content hygiene."

However, the noise around AI is causing confusion. At AIIM, we were hearing from members frustrated by the volume of theoretical content around AI who are eager for practical information about AI.

Working with a team of thought leaders, Rob and I drafted the whitepaper and assessment to help organizations assess the the state of their unstructured data.

What to Expect

The document is divided into three sections: Employee Engagement, Data Access, and Data Hygiene.

Each section provides a narrative that introduces the sections and provides helpful advice, which provides context for the assessment at the end of the section.

You can take the three assessment either online or print the PDF document. Each section includes a URL address and QR code that takes you to the online assessment. The benefit of the online assessment is we will calculate your score for you. Organizations can score themselves in each area and track their progress over time.

"Executives, for better or worse, love scorecards," explained Rob. "So you can say we're at a 67 right now, and they say, 'Well, we want to be at an 83,' and you then have a set of tactics you can work on to make the organization more able to take advantage of AI."

The whitepaper and assessment tool provides information management practitioners and organizations with the roadmap they need to create the enabling conditions for GenAI success, with a focus on leveraging unstructured data. It is a fitting addition to AIIM's library of resources that provide practical guidance on emerging technologies in the information management industry.

Three Pillars of Preparedness

The whitepaper and assessment explore three key factors organizations must address to fully leverage the value of the unstructured data and succeed with GenAI:

• Employee Engagement - Employees must be supported in a way that ensures their safety while exploring opportunities for benefit.

• Content Access - Valuable content is accessible and secure inside corporate repositories and systems.

• Content Hygiene - To improve the relevance and accuracy of GenAI results, data sources must be cleansed and maintained.
  
  

Employee Engagement

Rob emphasized the importance of change management in AI implementation.

"AI is a big change, people have to work differently," Rob explained. "They're going to get scared about 'Are they going to lose their job?' " This section of the assessment helps organization assess their ability to manage change and engage employees to address concerns and identify opportunities.

After organizations complete the assessment, they can reference the resources section in the whitepaper for tool and guidance on improving change management and engaging employees.

Content Access

This pillar focuses on making organizational unstructured data accessible to AI systems. This section of the assessment asks information management practitioners to consider:

1. Where is the information that is important in your organization located?
2. What is the volume of information?
3. Is it accessible to AI systems?
4. How often is the data needed to keep the AI system current?
5. How difficult is it to access or search the data and make it available to a Large Language Model (LLM)?
6. What security and permissions are in place to protect this data?

Security and data privacy are particularly important areas. As organizations implement AI, they must address concerns about data leakage and proprietary information protection to reduce and mitigate risk.

Content Hygiene

This area of the assessment covers familiar ground for information management practitioners who manage taxonomies, data dictionaries, and ROT (Redundant, Obsolete, Trivial) content. The assessment walks readers through a series of questions to help them assess the quality of unstructured data and also the quality of their organization's data hygiene processes.

Tips for Using the AI Readiness Assessment

During our conversation, Rob shared a few pieces of advice for using this new tool.

1. Collaboration is crucial: The assessment process often requires input from various departments, including IT, HR, and business units.
2. Realistic expectations are important: As Rob pointed out, "About 70% of large projects fail. IT projects, organizational transformation projects, they fail." The goal is to improve your odds of success, not achieve perfection.
3. Communicate the importance of quality data: Data quality is foundational to success with AI. Our research shows that while people feel confident about their ability to use generative AI, they often lack the necessary data quality processes. Tools like AIIM's new AI Readiness Assessment can help you evaluate your organization's current level of preparedness and also be used as a communication tool to build support for required information management improvements.

Download the Assessment

Take a moment to download the "Organizational Readiness for Generative AI: Leveraging Unstructured Data for Success" white paper and assessment.

The readiness assessment is designed to be a living document, and we welcome feedback from our members. As we continue to refine this tool, we hope it will serve as a valuable resource for organizations looking to harness the power of AI while addressing the unique challenges of information management.

Thank you to Rob Bogue and our sponsor Hyland, who made this assessment possible. I'd also like to thank Julie Harvey, Amitabh Srivastav, and Jesse Wilkins for their guidance and expertise throughout this project as well as our editor Dana Lheureau.

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