I Watched Companies Fail with AI and Change… Until They Did This

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I once worked with a manufacturing company that had decades of knowledge stored in thousands of files spread across network drives, email attachments, and personal computers. When they needed to make an important strategic change, finding the right information was like searching for a specific grain of sand on a beach. The knowledge was there, but practically inaccessible when needed.

This experience highlights exactly why smartnotes are revolutionizing how strategic AI systems help organizations better deal with change. But what makes them so special? And why should you, as a change leader or organizational consultant, pay attention? Let me explain through the lens of real organizational challenges.

A few months ago, I was working with a technology company that is undergoing a major digital transformation. The company's leadership had invested heavily in AI tools, including Microsoft Copilot, to manage the transition. However, six weeks into the process, frustration was setting in. "The AI keeps giving us outdated information," the CIO told me. "It's referencing policies we changed three months ago and suggesting approaches we've already tried and discarded."

The Problem With Traditional Files and AI

This situation shows you a fundamental problem with how most AI systems handle organizational knowledge—they rely on files. And files, as any change leader knows, are where information often goes to die.

Most current AI systems like ChatGPT or Microsoft Copilot use a simple but flawed approach: they train on whatever files you feed them. On the surface, this seems reasonable. You upload your strategic plans, process documents, and organizational charts, and the AI learns from them.

But in reality, this creates several critical problems that directly impact change initiatives.

First, files quickly become outdated. I've seen several organizations where policy documents sit unchanged for years while actual practices evolve rapidly. When you train AI on these files, you're essentially teaching it yesterday's truth. During change initiatives, when information evolves daily, this creates a dangerous knowledge gap.

Second, file management is inconsistent. Some teams meticulously update their documentation; others rarely bother. Some departments excel at clear writing; others produce dense, jargon-filled text. This means AI trained on files develops an uneven understanding of your organization, with deep knowledge in some areas and dangerous blind spots in others.

I recently watched a retail company struggle with this exact issue. Their AI had been trained on detailed files from their marketing department but minimal documentation from operations. When store managers asked the AI for guidance during a new point-of-sale implementation, they received marketing-centric answers that ignored operational realities. The result? Frustrated employees and slowed implementation.

Third, and perhaps most problematic, is what I call "training drift." Organizations often don't carefully curate which files are used for AI training. Some critical documents never make it into the system, while tangential or outdated files are included. Over time, the AI develops a distorted understanding of organizational priorities and processes.

Multilevel training doesn't exist in AI

Beyond these file-related problems lies another critical limitation of systems like Copilot: they lack multilevel capability. What does this mean, and why does it matter for change initiatives?

Any company change inherently involves different information needs at different organizational levels. Executives need strategic overviews and financial implications. Middle managers need implementation roadmaps and resource allocation guidance. Frontline employees need practical "how-to" information and answers to specific process questions.

With file-based AI systems, you face an impossible choice: either everyone sees everything (creating confusion and potential security risks) or you maintain separate AI instances for different groups (creating fragmentation and contradictory guidance).

I saw this problem several times. This lack of multilevel intelligence creates particular problems during sensitive change initiatives, where timing and controlled information flow are crucial. When planning workforce restructuring, for example, executives need early access to planning tools that shouldn't be visible to the broader organization until appropriate. Traditional file-based AI can't manage these nuanced information boundaries.

How Smartnotes Transform Change Management

This is precisely why smartnotes represent such a breakthrough for change leaders. Unlike files, smartnotes are designed for dynamic organizational knowledge that evolves at different rates across different levels. (you can try them here for free)

Smartnotes are available in Strategic AIs instead of general purpose AIs.

Smartnotes fundamentally change how organizational knowledge works in three ways:

First, they encourage continuous updating. While files tend to be updated in major revisions (if at all), smartnotes can be quickly modified as new information emerges. I've seen change teams use daily stand-up meetings to update smartnotes on implementation progress, ensuring the AI always provides current guidance.

Second, smartnotes use multilevel visibility by design. Each piece of knowledge exists at exactly the right level – personal, team ("initiative"), or organization-wide. This means:

• Executives can maintain strategic smartnotes visible only at leadership levels
• Department heads can create team-specific implementation details
• Individual contributors can maintain personal notes about their specific role changes

When someone asks a question, they receive precisely the information appropriate to their position—not generic answers that ignore organizational hierarchy, and not information they shouldn't have access to.

Third, smartnotes create clear accountability for knowledge. With traditional files, ownership often becomes unclear over time. With smartnotes, each piece of information has a clear owner responsible for its accuracy. This transforms how organizational knowledge evolves during change initiatives.

Why Change Leaders Should Care

If you lead organizational change efforts, the shift from file-based to smartnote-based AI isn't just a technical detail—it fundamentally changes what's possible.

Consider how change typically unfolds. You start with a strategic vision that gradually translates into specific plans, then implementation details, then individual behaviors. At each stage, knowledge requirements shift. With file-based AI, you're constantly battling outdated information and inappropriate access.

With smartnotes, you can create a knowledge ecosystem that evolves alongside your change initiative:

Early in the process, executive smartnotes might outline strategic objectives visible only to leadership. As plans solidify, department-level smartnotes can detail specific implementation approaches visible to relevant teams. As training begins, company-wide smartnotes can provide consistent messaging about the "why" behind changes, while team-specific smartnotes address unique departmental challenges.

This graduated unfolding of knowledge mirrors how effective change actually works in organizations. Rather than overwhelming people with complete transformation plans at once, you can progressively reveal information as teams are ready to absorb and act on it.

The multilevel nature of smartnotes also respects the reality that different parts of your organization will move at different speeds during change. Your pilot team might be ready for advanced implementation details while other departments are still grappling with basic concepts. Smartnote-based AI can simultaneously serve both groups with appropriate guidance without confusion.

Perhaps most valuable for consultants and change leaders is how smartnotes capture learning throughout the change process. When a team discovers an effective approach to overcoming resistance, that knowledge can be immediately captured and made available to other teams facing similar challenges. This creates a continuous learning cycle that accelerates change adoption.

The shift from files to smartnotes in AI represents more than a technical improvement. It reflects a fundamentally different way of thinking about how knowledge should function during organizational change.

Files represent static, point-in-time documentation. They embody the outdated assumption that organizational knowledge can be captured in periodic snapshots. In contrast, smartnotes represent dynamic, evolving understanding. They acknowledge that organizational knowledge is constantly in flux, especially during change initiatives.

For change leaders and consultants, this shift enables a new kind of change management – one where guidance evolves in real-time, where learning from one area immediately benefits others, and where information boundaries reflect organizational realities rather than technical limitations.

If you want to try how smartnotes work, you can do it for free. Go to HannaProdigy.com and register a free account for you and your team!