Sponsored Article
Research Report
Building the Case for Modern Public Sector Messaging
We've entered what we call the "Great Content Collapse,” and things are crumbling. The operating models that once powered digital marketing are no longer keeping pace with how content is created, discovered and delivered.
AI is dramatically changing how buyers discover brands, with answer engines and assistants increasingly influencing research before visitors ever reach a company’s website. At the same time, teams are being asked to produce more with fewer resources (hello, AI slop; goodbye, customer attention).
For brands to successfully navigate this change, content must serve two opposing audiences: people and AI agents. To check the box with people, content must be relevant and credible. For agents, it must be well-structured and easy to cite and parse.
While many companies race to adapt their content strategy to meet these new demands, the technology they rely upon is just as important. The majority of solutions were built for a different era, trapping content in disconnected tools, static pages and channel-specific workflows The result is fragmented operations, inconsistent customer experiences, and content that's difficult for AI systems to interpret.
The way out of content collapse is a content foundation built for scale. Contentful's Intelligent Experience Platform helps brands create, manage and activate structured content across every channel, market and AI experience. Here’s what that looks like in practice.
Start With Structured Content
In legacy content management systems (CMSes) and digital experience platforms (DXPs), the same product description, campaign message, customer proof point or compliance statement gets recreated again and again across pages, markets and channels. Updating that content often means tracking down every place it appears — from regional websites to campaign landing pages and mobile apps. The result is slower updates, duplicated effort and a greater risk of inconsistent or outdated information reaching customers.
Contentful takes a different approach. Instead of managing pages, teams manage structured content. Every piece of content is modeled as a reusable building block with metadata and governance, allowing it to be created once, reused across experiences, localized for different markets and updated everywhere from a single source.
As content libraries grow, Contentful’s Content Semantics makes that content easier to discover and reuse by understanding meaning — not just keywords. Teams can identify duplicate or related content, surface the right assets faster and provide richer context for AI.
The benefits extend beyond operational efficiency. Because Contentful stores information as structured content rather than embedding it within pages, AI systems receive clearer, more consistent signals. A product specification stored as structured data, for example, is easier for AI to understand, retrieve and use accurately than the same information buried in page copy.
Bring AI into the Workflow
For many marketing teams, the AI toolkit still lives outside the content workflow. Writers draft copy in ChatGPT, paste it into the CMS, send it for review, then jump back into ChatGPT for revisions or translations. Content gets created faster, but the work surrounding it — reviews, approvals, localization and governance — becomes fragmented.
Contentful brings AI into the content lifecycle. Instead of forcing teams to move between disconnected tools, AI works within existing editorial workflows, preserving approvals and governance. And because AI operates within the context of your structured content, not in isolation, it can generate outputs that are more relevant, consistent and on-brand. Teams can use AI Actions to accelerate repetitive tasks such as drafting, rewriting, summarizing, translating and tagging. AI can also help enforce quality standards by checking for brand alignment, compliance risks, grammar and translation quality before content moves forward in the workflow.
Contentful MCP extends AI capabilities to assistants and agents. Built on the open Model Context Protocol (MCP), it gives AI secure access to trusted content and business context from Contentful and other MCP-connected or integrated systems. Instead of requiring teams to gather information from multiple tools before drafting or updating content, AI has the context it needs from the start to produce more accurate and relevant outputs. Marketers can then use AI agents to create and update content, perform bulk changes or support tasks such as SEO optimization using natural language, while keeping Contentful at the center of every content review, approval, and publishing workflow.
The operational benefits quickly add up. Here’s an example: before adopting Contentful, Bossard, a global industrial fastening and assembly technology company, relied on a legacy CMS that lacked modern integrations, creating bottlenecks across content production and global publishing. After replatforming, Bossard used Contentful AI Actions to streamline translation across 16 languages and 38 locales, saving them 600 hours of work (and €27K). In the four months that followed, the company saved an additional 1,000 hours of work by using AI Actions to automate content operations at scale.
Deliver More Relevant Experiences
As AI makes content easier and faster to produce, the challenge shifts from creating more content to delivering the right content. When every brand can generate endless product descriptions, emails and landing pages, relevance becomes the real differentiator.
From Automation to Intelligence: How Leading Teams Are Rethinking Operations
Register
Content Leaders Collective: When Your Documentation Tools Can't Keep Up
Register
How to Win the War for Agentic Citations: The AEO Playbook You Need Now
Register
CX Retail Exchange USA Atlanta 2026
Register
But relevance doesn't come from AI alone. It comes from understanding who your audience is, what they're trying to accomplish and delivering content that reflects that context.
Contentful Personalization helps marketers create, test and optimize tailored experiences within the DXP. Using audience segmentation, experimentation and AI-suggested audiences and experiences, teams can adapt content based on visitor behavior, intent and preferences. Built-in analytics reveal what resonates with different audiences, enabling marketers to continuously refine every experience.
Washable rug brand Ruggable saw this in practice. Rather than sending every visitor to the same experience, the company recognized that dog owners and cat owners often have different priorities. Visitors arriving from dog-focused campaigns saw imagery, customer reviews and product recommendations tailored to dog owners. Visitors from cat-focused campaigns saw content designed around their interests instead. The products were the same, but the experience reflected why each visitor came to their site.
Influence How AI Represents Your Brand
As answer engines become a primary discovery channel, marketers need to understand both their visibility in AI-generated answers and how their brand is being represented.
Most AI visibility tools answer the first question. They measure citations, mentions and share of voice, helping marketers understand whether their brand shows up in AI-generated responses. But they offer little insight as to why AI represents the brand the way it does or what content changes would improve those answers.
Contentful's new offering, Palmata, helps marketers move beyond visibility metrics. By analyzing a company's content footprint, competitors, audiences and digital ecosystem, it reveals the factors shaping AI-generated answers and recommends the content changes most likely to improve how your brand is understood. As more customers turn to answer engines to discover and evaluate brands, Palmata gives marketers the insight they need to actively manage their AI reputation.
Frequently Asked Questions
From Content Collapse to Intelligent Digital Experiences
Escaping the Great Content Collapse requires more than adding AI to existing workflows. It requires rethinking the foundation that powers digital experiences, so content is structured, connected and ready for both people and AI systems. Organizations that build that foundation today will be better positioned to deliver the intelligent digital experiences customers expect tomorrow.
Discover how Contentful helps leading companies build AI-ready digital experiences at Contentful.com.