Beyond the Final.Final.Really_Final Version: 3 Steps to Rethinking Documents and Enterprise Knowledge

Documents are a funny conundrum for the modern enterprise. From brochures and presentations to reports and documentation, from spreadsheets and summaries to agreements and quotations, documents can be the catalyst to creation and the origination of obsolescence. They can be the cornerstone of a business, the central if not critical output of any number of functions. They can be easily overlooked once the final version is approved and used…relegated to cold storage and forgotten. All the work, the collaboration, the insights, the wisdom and the institutional knowledge can be lost. The end of that document’s journey often involves a passive destination where value is tabulated in how many times the freezer door opens to grab it for use.

But what if documents were meant for more?

The age of AI has opened the door for a new call to action for documents across every organization. It issues an invitation to revive the conversations and interrogate the work in brand new ways. In 2024, I asked, “what if documents could talk?”, investigating a future when generative AI turned a document into a conversation. Chatting PDFs were just the starting point. In a time when AI agents search for more data to satiate its hunger, documents become micro-repositories of knowledge and context, but only when we stop thinking of a document as a final destination. Instead, documents are vessels, carrying everything from answers to ideas…all destined to fuel AI and her voracious appetite. Moreover, the knowledge extracted from documents represents a starting point.

Documents are not a destination. Here are 3 steps to rethinking what comes next.

AI has business leaders rethinking where fresh, renewable data to represent business, operational, employee and customer context. For AI to deliver on its promise of improved business outcomes, we must start thinking about where and how the fuel to power more precision decisions, not to mention recommending improved workflows to power autonomous enterprise action. Much of the conversation until this point has been focused on the capacity of AI to generate content, leveraging existing documents and knowledge about markets and customers, to create new assets to suit an audience of one. This is just the first step from the starting point. To truly capitalize on the AI + documents opportunity, its time to think differently.

Step one: Thinking about documents differently. Smart organizations have already established IT and operationally driven strategies that collect, secure and store documents. Teams leading with AI have also thought about documents as the output from agentic workflows, empowering content tools to generate new assets autonomously. But to shift from documents as passive assets to active AI fuel, we need to think beyond what happens to an asset after the fact and shifting the continuum to a more continuous cycle that starts with the genesis of the document itself but extends to the next decision, action or asset. For every answer, every update or every point of collaboration and refinement, there is a trail of insights that can and should contribute to enterprisewide intelligence and understanding. For every final document, there is a wealth of understanding about the document itself, but also the work that went into and the work that comes after that document’s existence. By thinking of a document as an open vessel that holds intelligence, systems, especially AI-empowered systems can navigate and extract knowledge that can be set to work once again.

Thinking about a document as a form of renewable energy opens up opportunities to think about continuous improvement—not just of that document, but of the processes, actions and workflows it is attached to. Take for example how a document intersects with and impacts the sales process: from the customer’s initial quote to the end statement of work, documents carry the end output, but also all the insights drawn from requests, comments, edits, strikethroughs and additions. If we think about these documents as active assets, knowledge about business process, workflow and the customer can be extracted and set to work, helping a seller better enter a renewal conversation, armed with knowledge and ready to materially shift the experience. Looking beyond the final and thinking about a document as a lifecycle allows systems to operate on context and intelligence, not passive reaction.

Step two: Think about knowledge differently. Much like shifting away from a document being a passive asset, organizations should think differently about knowledge. For some organizations, knowledge, much like a document, is the end destination for insights, intended to answer a question or resolve an issue. As an example, within the context of customer service, a knowledge “base” is often established to help service agents resolve key issues. This is less about knowledge and more about establishing a database of answers. Leveraging templates and content management, these knowledge repositories have become the epicenter for self-service or automated service, allowing customers and employees to solve problems or get answers to questions 24/7. In this service scenario, knowledge is a passive database, now being updated with AI tools that focus on new knowledge aggregation and database entry curation and generation.

Thanks to AI, accessing knowledge can be conversational, new knowledge articles can be autonomously generated to assist the next user, out of date answers can be automatically removed. As active as this knowledge base seems, it is still based on content marked “final”. True knowledge can be derived from the information memorialized within a document, but also from the work, collaboration and contributions along the way. Knowledge isn’t just the final thought, but should curate the institutional insights, contributions and options voiced and contributed along the journey. Knowledge can be institutional, historical and thanks to AI, increasingly predictive and proactive. Knowledge can chronicle the ebb and flow of real work, not just learn from the documented processes implemented. But perhaps most importantly, knowledge can and should be put to work. Instead of knowledge as being something retrieved and recommended, knowledge can become something that flows across multiple systems, impacting forward looking strategies and decisions. In the same way that a document should be thought of as a continuous lifecycle, so too should knowledge.

As we rethink knowledge, there is another conversation that should go hand-in-hand with this examination: how can we trust any of this? And this is where our first step becomes critical to empowering the second. To trust in any AI output, there need to be guardrails, safeguards and continuous reinforced learning and confirmation. One of the best ways to proactively assess and understand if the output captured in a document is to have AI trained, tuned and reinforced by a fresh, renewable source of intelligence about the work, the workflow, the expected output and the anticipated outcome. Thankfully much of this content and intelligence can be captured from a document’s lifecycle. When the active insights from a document’s lifecycle is included in the knowledge agentic workflows can tap into, an organization’s understanding of approval cycles, brand style requirements, legal standards, and organizational norms becomes part of that workflow and agentic reasoning.

Let’s revisit the example of a sales SOW. No sales contract is the same. They shift and update based on the requirements of the customer, of the business and of the larger market that can be impacted by regulatory demands. When knowledge and documents are rethought, workflows that account for required checks against knowledge to crosscheck documents for regulatory updates, company policies around discounts and historical knowledge around past contract terms can be woven into the workflow so that these time-consuming back-and-forth checks are completed even before the first draft of a new contract is submitted for management review. Knowledge fueled by document intelligence can surface recommendations for updates, insights into content updates all while saving time and reducing the friction of manual document reviews.

When knowledge lives beyond a database, it breaks the cycle of knowledge for knowledge’s sake. Instead, it becomes part of a larger business process purpose built to accelerate trusted business outcomes.

Step three: Think about how to put documents to work differently. Access to enterprise documents, just like data warehouses and enterprise knowledge bases, tend to be far more limited than expansive. Who can access documents is limited and rightly so. The idea of cross-organization collaboration, creation, and distribution of documents is safeguarded. But sometimes, the natural ebb and flow of functional work can create artificial limitations. Once again, let’s revisit that sales document process: Does marketing have access to those critical quotes, comments and contract outputs? Does service? Who should be able to ask 5-years’ worth of quotes and contracts where and how variants have impacted end results or revenues? Is it a sales-only question? Legal? Finance?

Traditional functional thinking would say that these functions don’t need access to the potentially sensitive contracts or quotes now stored as institutional documents. Access and authorization are necessary, but don’t erase the truth that each one of those sales documents could unlock intelligence critical to a decision marketing or service must make around that same customer.

The suggestion here is not to do away with the security, safeguards and controls that any responsible document or asset management strategy would include. Instead, this is more about redefining where, when and how intelligence in a document can be accessed and turned into action. The opportunity is to rethink how a document gets put back to work. What workflow could be documented? Can it become an automomous flow thanks to the updated knowledge derived from the process? What teams can unlock the intelligence that influences new answers?

Revisiting that sales SOW for the last time…once legal, compliance and sales leadership have reviewed and blessed the document, and the client has executed the final agreement that saw 7 stops until it truly became “final”. In a rethought document lifecycle, this is not the end, but rather a call for that document to go back to work. Marketing receives signals based on insight from sales and directly from the client’s comments and collaboration that the key message of the last webinar did not strike a chord, in fact, the language was intentionally struck from early drafts. Service can pull documents into their document collaboration to enhance customer FAQ content around terms, shipping and sales-established expectations that have become common language across multiple contracts and accounts. Instead of the contract being shared and each function extracting and interpreting knowledge in isolation, this document’s intelligence from content to workflows can be institutionalized and uniformly shared.

These three steps aren’t the only steps…they are the starting point. As an individual or an organization starts to ask these new questions, it will invariably invite new questions around the platforms and solutions that can bring this to life. And this is where a real word of caution comes to play: new systems may NOT be the best systems to deploy in these knowledge investigations. Sometimes the answer already exists on a user’s desktop or within the enterprise stack. Sometimes the real power of knowledge and documents can collide thanks to integrations that allow for knowledge bases to become truly collaborative with our people, our systems and documents. For example, newly introduced capabilities from Adobe Acrobat Studio brings the power of its newly launched Knowledge Base directly in Slack or Teams, bringing knowledge directly into organizations work.

This rethought world of documents and knowledge—and the new conversations true enterprisewide knowledge can amplify and accelerate—can drive real business velocity and unlock the output all leaders seek in exponential growth. This lifecycle continues, improves, accelerates and changes direction as more decisions are influenced, more collaboration cycles are completed and more work is done. It links and connects the workflows and the tools where work happens. This lifecycle evolves, connecting the dots between documents to knowledge, between knowledge and action,and between action and proactive strategy and planning.

Looking beyond the age of “final, final, finally done, final perfect content” as a passive destination isn’t aspirational or far from reach…it is possible now. This is an opportunity to actively rethink where and how documents link to action in an agentic enterprise, without rethinking how and where work happens. For those organizations willing to take these steps, the reward will be renewable intelligence to power context and knowledge. But there is also a prediction to be made through this: velocity, not just speed, will be the reward. Speed is the capacity to move faster…but doesn’t specify if that acceleration will have direction or impact. Growth demands velocity, a focused combination of both speed and direction. The knowledge and intelligence from documents will power the continuum of data to decisions thanks to data that is derived from decisions. So here’s to putting documents back to work, not for the sake of more work, but rather for the sake of more successful outcomes.