A decade ago, the concepts of machine learning (ML) and artificial intelligence (AI) seemed theoretical and complex, with few practical use cases. Fast forward to today, and we’ve witnessed remarkable growth in the popularity of ML and AI, driven by their diverse and valuable applications.

When integrated with a content management system (CMS) like Tridion, semantic AI can unlock new capabilities, providing an improved digital experience.

Businesses often find themselves navigating siloed, unorganized, and duplicate information as they try to generate insights that form new ideas. Machine learning and semantic AI are valuable assets in this context, particularly in content management, personalization, and creating engaging content experiences.

According to McKinsey, global AI adoption is now 2.5 times higher than in 2017, despite leveling off at around 50% over the last few years . Whether through chatbots, virtual assistants, or automation tools, machine learning empowers companies to elevate workforce productivity and efficiency, enabling them to achieve key objectives more rapidly.

In this article, we’ll explore the concept of semantic AI, its benefits, and its practical implementation in Tridion.

What is Semantic AI?

Semantic AI, closely related to natural language processing (NLP) or natural language understanding, is a branch of artificial intelligence focused on how computers understand and process human language. It involves analyzing and interpreting the meaning of words and sentences to perform tasks or provide information to users.

For example, a semantic AI system can automatically summarize a news article, answer questions, or translate text from one language to another. These systems often rely on machine learning algorithms to improve their accuracy and performance over time.

Benefits of Semantic AI

Integrating semantic AI into Tridion offers several benefits:

Improved Data Quality Semantic AI enhances data quality by improving predictions and classification, making data more organized and streamlined.

Enhanced Search and Findability A more robust taxonomy makes finding the right content assets easier for both content authors and the end consumer. By understanding search intent and using faceted search, the most relevant results can be displayed, reducing the time spent wading through excess information.

Increased Productivity Content editors and authors can quickly and accurately tag content without manual effort. This allows them to focus on creating content that drives desired results rather than organizing and classifying it.

Better Insights Semantic AI provides better insights to marketers and content creators by extracting relevant information from unstructured data. It offers improved semantic analysis, allowing faster conclusions from customer feedback than manual methods.

Enhanced Customer Experience Semantic AI can implement chatbots that draw on knowledge databases and existing content assets. These chatbots answer customer queries faster than in-person support and offer more personalization, thus delivering a better customer experience.

How Tridion Uses Semantic AI

Semantic AI connects Tridion to the knowledge databases throughout an organization, integrating content with data to provide all users with the information they require. Key features of Tridion leveraging semantic AI include:

Conceptual Search Semantic AI adds context and matches user intent to content using machine learning. When a customer searches for a term, semantic AI provides relevant suggestions and recommendations, and users can apply faceted search to narrow down results.

Taxonomy Spaces Tridion uses Taxonomy Spaces to improve data sharing and governance with the help of semantic AI. It manages important concepts within an organization, various ways to describe them, and their interrelations.

Smart Tagging Tridion offers automated tagging suggestions that provide relevant tags while editing content. For example, a blog article about “Best Insurance Companies in the Southern US” could generate labels like insurance, insurance claims, Florida, Georgia, and more. This saves time for content authors, who can accept or update tags as necessary.

Leveraging Semantic AI and Tridion

Machine learning algorithms and artificial intelligence are valuable tools for increasing employee productivity and delivering better customer experiences. With the latest semantic AI capabilities, Tridion users can leverage features like Conceptual Search, Taxonomy Spaces, and Smart Tagging.

At Content Bloom, we have deep expertise in Tridion’s various capabilities and can help you maximize the benefits of CCMS and semantic AI. We assist in avoiding content silos and gaining control of the content lifecycle with improved findability and reusability.

Learn more about structured content and the benefits of having a solid structured content strategy by reading: Best Practices for Implementing a Structured Content Strategy.

FAQ

What is Machine Learning?

Machine learning is a field of artificial intelligence that focuses on using and developing computers that can imitate how humans learn. Essentially, it can interpret and adapt as it gathers more information. For example, Netflix’s recommendation engine provides more accurate recommendations after it begins understanding your viewing preferences.

What is Machine Learning vs. AI?

Machine learning is a subset of artificial intelligence. AI encompasses a wide range of techniques and technologies for creating intelligent systems, while machine learning is a specific method used within AI to enable machines to learn from data and make predictions or decisions.

What are semantics in Artificial Intelligence and Machine Learning?

Semantics is the historical study of meaning. In artificial intelligence and machine learning, semantics refers to the interpretation of language or data by computers.

What does Tridion Semantic AI do?

Tridion semantic AI matches user intent and context to content to improve search performance, automatically tags relevant content assets, and enhances the organization and classification of content assets throughout the business.