AI is completely disrupting how organizations need to think about their content, whether it is customer-facing or internal. The data reveals just how profound—and significant–this disruption has become:
- According to KMWorld, 73% of businesses are embracing AI today, with 74% seeing positive results and 62% planning to invest even more in the coming year.
- A 2024 Deloitte study reveals that 67% of organizations are increasing their AI investments, having already experienced significant benefits.
- Gartner highlights a critical insight: AI projects need strong knowledge management foundations to succeed.
- IDC’s research shows that nearly half of organizations (49%) are thinking carefully about how to protect their proprietary content while using AI.
Looking ahead, we see four key trends that will shape how organizations use AI. Based on our experience and research, we’re sharing some practical insights about how businesses can make the most of AI while addressing real challenges around data quality, security, and knowledge management.
1. Content Quality: The Foundation of AI Success
Think of AI like a brilliant student – it can only learn from the materials we give it. Right now, many organizations are rushing to implement AI without considering the quality of their content. This content lives in company policies, procedures, technical documentation, and training materials. Making this information clear, accurate, and well-organized is essential for AI success.
When we talk to organizations, we’re often surprised that content quality isn’t at the top of their AI planning list. It should be. After all, if you want AI to give great answers, you need to feed it great information. We believe now is the time organizations need to prioritize getting their content AI-ready.
2. The Rise of Conversational AI: Making Information Actually Useful
Remember the frustration of searching through endless documents to find one specific answer? That’s about to change. Instead of diving into multiple documents like you’re solving a puzzle, imagine having a conversation as natural as asking a colleague for help. That’s what AI is bringing to the table.
Traditional search feels like playing a game of “guess the right keyword.” You type in what you think might work, click through various documents, and piece together information from different sources. It’s time-consuming and often frustrating. But in 2025, we’re seeing a shift to something much more intuitive: simply asking questions and getting complete answers.
With AI, organizations can now unlock all their valuable knowledge – from technical guides to training materials – through natural conversations. Team members can find exactly what they need, when they need it, without the traditional scavenger hunt through multiple documents.
There is one important detail to consider, though. Most organizations have unique, internal knowledge that public AI models can’t and shouldn’t access. To make the most of conversational AI, companies need to thoughtfully prepare their proprietary internal content. This means creating clear processes for organizing, updating, and delivering this information in order to train their own AI systems.
3. The Evolution of Content Operations: Welcome to Content Engineering
Making information easily accessible through AI isn’t magic – it requires solid groundwork. We’re seeing a shift from basic content management to what we call content engineering. This isn’t just a fancy term—it’s a practical approach to making content work harder for your organization.
Many companies still create and store content the same way they did twenty years ago: writing documents and saving them in folders. But today’s fast-paced business environment needs something more sophisticated.
Content needs to be as flexible and reusable as software code. This means three key changes:
- Making content machine-readable and easily processed by AI
- Separating the content itself from how it’s presented
- Adding smart labels (metadata) to make content more findable and useful
Organizations that make these changes will see their content become more valuable across all their systems – not just for AI, but for everything from employee training to customer support.
4. AI and Compliance: Making Reporting Smarter and More Reliable
AI is transforming one of business’s most challenging tasks – regulatory compliance and reporting. This is particularly game-changing for heavily regulated industries where documentation requirements can be overwhelming.
Take the pharmaceutical industry as an example. According to Accenture, companies using AI-powered regulatory systems are seeing remarkable results: 99.9% on-time submission rates and less than 1% document errors. These systems handle over 1,000 submissions across 90+ countries annually, showing just how powerful AI can be at scale.
But this isn’t just about pharmaceuticals. Any industry dealing with complex reporting requirements can benefit. Instead of the traditional cut-paste-format approach, AI can help create accurate, consistent reports while significantly reducing the time and effort involved.
What we’re excited about is AI’s ability to understand the intent behind regulatory requirements. We expect to see systems that not only compile information but ensure it truly meets regulatory needs, making compliance both faster and more reliable.
Looking Ahead
These trends point to a fundamental shift in how organizations handle information. Success with AI isn’t just about having the latest technology – it’s about having quality content that’s well-organized, accessible, and ready for AI to use. Organizations that focus on these fundamentals will be better positioned to take advantage of AI’s growing capabilities.
Remember Adam Grant’s insight: “The hallmark of expertise is no longer how much you know. It’s how well you synthesize.” From here on out, AI will help us synthesize information better than ever – but only if we give it high-quality content to work with.
