The hidden bottleneck in your AI initiative: Content Chaos

Content is a strategic asset

In enterprise organizations, content is increasingly becoming a strategic asset — not just a communication layer, but a foundation for personalization, customer support and compliance. A lack of content quality and availability can seriously hurt your business. Think about:

• Regulatory risks due to outdated or inconsistent information
• Brand and trust damage from incoherent customer experiences
• Decreased engagement and retention from poor content relevance
• Inability to deploy modern AI experiences like chatbots or semantic search

This is especially critical in industries such as:

• Finance & Insurance – where product data, policy documents, and legal terms need to be accurate and consistent
• Healthcare – where up-to-date, accessible content directly impacts patient safety and experience
• Public Sector – where information must be clear, multilingual, and compliant
• Manufacturing – where technical documentation underpins operations and customer service
• Telecom & Utilities – where product comparisons, support content, and terms change rapidly
• Retail & eCommerce – where product data and self-service content drive conversion

For these sectors, content is more than text — it’s business logic, regulatory control, and customer interface all rolled into one.

The symptoms: when content gets in the way

Despite investing in powerful tools and AI platforms, many organizations still struggle to deliver on their content potential. When working with our customers or talking to prospects, we often detect one or more of the following issues:

• Irrelevant or outdated content being published
• Customers getting inconsistent information across channels
• Content that’s too generic and not aligned with customer needs
• Customers keep asking the same questions in support channels
• Support agents struggling to find accurate responses quickly
• Digital assistants providing wrong or contradictory information
• High costs and long lead times for content operations

If any of this sounds familiar, you’re surely not alone.

Technology ≠ strategy

Too often, content efforts are reactive and technology-centric — focused on fixing symptoms, not root causes.

One classic example: investing in a new CMS and attempting to centralize all content in a single “source of truth.” Sounds great — until you realize different types of content require specialized tools and structures to manage effectively. A monolithic “content hub” rarely resolves the deeper issues.

Another? Spending months fine-tuning or swapping Large Language Models to improve chatbot responses — without addressing the poor-quality, hard-to-parse source content those models rely on.

Technology is important. But without addressing the quality, structure, governance, and accessibility of your content, you’re building on shaky ground. If the input is junk, the output will be too.

What’s really causing the chaos?

Here are the most common root causes we encounter:

• Content is scattered across organizational silos and stored in disconnected systems
• There’s no clear governance, ownership, or accountability
• Content lacks semantic clarity — meaning it’s vague or ambiguous
• Some critical content is simply missing
• Metadata is incomplete, incorrect, or missing altogether
• Content is written in a design-first and channel-specific manner, with limited potential for reuse
• Search engines index outdated or irrelevant content
• Content is not machine-readable or not accessible to AI tools. When machine-optimized formats such as JSON or Markdown are missing, the "human" version of the content (e.g. a webpage in HTML) needs to be interpreted on a best-effort basis, causing issues with ambiguity and other semantic challenges.

Ask the right questions first

To start solving these challenges, ask yourself:

• WHY invest in content? What business value can it deliver across domains? These are your use cases.
• WHAT content is needed to support those use cases? These are your Content Products.
• WHO needs to be empowered to improve content quality, and what tools do they need?
• HOW will you move toward your desired state? This defines your Content Strategy.

This means aligning people, processes, and technology around a sustainable Content Program — and doing so iteratively, not in a big bang. This is what the emerging field of Content Science is all about.

Small steps, big impact: how to get started

Your next move depends on your maturity level. But here’s a proven pattern that helps most organizations get on track toward becoming content-driven:

Appoint a Content Program Manager

This person owns the content vision and is responsible for shaping and driving a Content Strategy. Their first step? Understand the current state: what content types exist, who manages them, in which tools, and whether that content is machine-readable and AI-ready.

Detect content issues and root causes

Using Content Auditing tools, the Content Program Manager identifies symptoms of low content quality — missing metadata, outdated information, poor readability, and more. AI tools like Large Language Models can assist in detecting gaps or inconsistencies.

Build a Content Quality Backlog

Prioritize improvement tasks based on business impact and estimated effort to execute. Fixing a backlog item likely requires cross-silo collaboration. Let’s take the following example: an issue with response accuracy for the company's chatbot might require the team who owns the problematic content to optimize its structure and metadata, while IT might need to implement an API to improve machine interpretability. It might also be needed for people working in customer service to provide customer feedback to further improve the content quality.

Introduce Content Monitoring

Track content performance in downstream systems. For instance, measure how often your chatbot surfaces the correct answer or how many queries result in failed searches.

Launch a Content Catalog

Create an organization-wide overview of content assets and associated content models. This increases visibility, reduces duplication, and supports better governance.

Build a Content Quality Pipeline

Connect raw content sources and transform them into structured, enriched, AI-friendly formats. This pipeline ensures that content reaches downstream use cases like search or digital assistants in optimal condition.

Increase content accountability

Empower domain teams to take ownership of their own content. Over time, they develop their own “Content Products” aligned to specific business use cases.

Close the loop with feedback

Set up an agentic flow from Content Monitoring back to content owners. For example, when a chatbot answer receives negative feedback, the system automatically generates a backlog item to update and improve the source content.

Ready to get started?

We believe that every organization has the potential to become content-driven and start practicing Content Science. But we also understand that initiating a Content Program can feel overwhelming.

With our AI Content Readiness service, we can therefore help your organization to bootstrap and accelerate its Content Strategy and Program — bringing clarity, structure, and momentum from day one:

• We begin with an in-depth analysis of your content governance, existing tools, and organizational silos
• We deliver a detailed report and roadmap, identifying quick wins and long-term improvements
• We help you set up the initiative, including appointing a Content Program Manager and facilitating internal buy-in
• We help boost content literacy across teams, helping everyone understand what good content looks like
• We support technology selection and adoption, ensuring you pick the right stack for your needs

No matter the industry you are in, we can help you bring order to content chaos — and unlock the full potential of your AI and digital ambitions.