The New Era of Intelligent Content Delivery How AI Is Transforming CMS and DXPs

Learn how AI revolutionizes CMS/DXP with content creation, personalization, analytics and multichannel delivery, enhancing digital experiences.

We live in a time when businesses are at a crossroads. The demand for personalized experiences has reached a fever pitch, fueled by consumers who expect seamless interactions across channels and touchpoints. If we don’t address this demand, we will be left behind. To this end, artificial intelligence has emerged as a critical tool to deliver on these huge expectations.

However, AI is not a magic wand. It requires thoughtful planning, robust data infrastructure and ethical considerations. So, the big question pops up—how can it be leveraged properly?

First, let’s consider the numbers. According to PR Newswire, 42% of IT professionals in major corporations are actively deploying AI, while another 40% are exploring and experimenting with it. These stats show just how urgent and important integrating AI into business strategies has become. But simply using AI isn’t enough—it’s about implementing it strategically. And personalization is where AI really shines.

By harnessing AI’s capabilities, businesses can analyze vast amounts of data to understand individual preferences, behaviors and context. Whether it’s recommending tailored products, predicting customer needs or automating responses, AI can create a seamless, hyper-personalized experience that keeps customers coming back for more.

For content management systems and digital experience platforms, the goal is to work smarter, not harder, when engaging customers across channels. In general, AI can help with:

• Deeper personalization at scale, tailored to each user
• Faster content creation, localization and omnichannel publishing
• Improved customer experiences based on data and insights
• Smarter recommendations and predictive capabilities
• More relevant search results and chatbot interactions
• Optimized marketing campaigns and assets for higher ROI
• Actionable analytics to guide better content decisions

Let’s take a closer look at these.

Personalization

AI powers hyper-personalization at scale by gathering data about customer interests, behaviors and preferences. This enables companies to serve up tailored content, product recommendations and experiences for each visitor. While manual personalization would be impossible for large customer bases, AI systems can crunch data to understand trends and patterns.

Examples of AI-driven personalization include:

• Customized homepage content based on past purchases and browsing history. An outdoor retailer could showcase hiking products for customers who frequently view that category.
• Product recommendations matching user profiles. A fashion retail site could suggest items in sizes that fit the customers and styles they tend to like.
• Personalized search results ranked by relevance to the individual. Searching for “tennis shoes” returns options filtered for the customer’s size, brand preferences, etc.
• Email and push notification content tailored to past responses. An electronics brand could send deals for headphones to customers who opened headphone promotions in the past.
• Chatbots providing personalized answers based on context. Customers could get individualized help from a bot that understands their account details and past service needs. Just like this Progress Sitefinity Chatbot which leverages Natural Language Processing (NLP), machine learning (ML) and more to engage in natural language conversations that feel human-like.
• Next best action recommendations to enhance the customer journey. A telecom site could offer account upgrades or equipment add-ons based on usage data.

For a tool like Sitefinity CMS, you can create customized experiences by delivering different versions of content, page assets and pages to specific audience segments. These segments are defined based on various user characteristics and data, which you can combine using rules and conditions. For instance, you can personalize entire pages, page templates and even out-of-the-box widgets like content blocks, images, news, blogs and events.

Content Creation

AI can also be an incredibly handy tool for automating content generation. All you need to do is feed data into these AI-powered tools, and they can analyze existing content, suggest topics and headlines, rewrite content for different formats and even write full articles from scratch using natural language generation (NLG).

This applies to images, videos and other media too. AI can generate creative assets based on text descriptions. AI also provides data-driven recommendations for what content to create, when to publish it and which channels make the most sense based on trends, behavior and competitors. This is especially useful for scaling content creation, and the ones that require frequent updates or localized versions.

However, when using these tools, you should still have human oversight for quality control. AI should complement your human writers, not replace them.

Content Optimization

Beyond content creation, AI can help optimize content for better performance by analyzing and providing recommendations for titles, descriptions, keywords and other elements to improve search engine rankings. This also boils down to content quality evaluation. By checking grammar, readability, logic flow and factual accuracy, AI can identify areas that need improvement before publishing.

NLP techniques can be used to analyze user-generated content, comments, social media discussions and feedback to understand sentiments and preferences. This enables you to better align content with audience expectations.

Enhanced Search

By implementing natural language processing and voice search, you allow customers to find information in an intuitive, conversational way.

With natural language search, users can type full sentences or questions into the search bar, instead of just keywords. The AI understands the intent behind the search query and returns the most relevant results. For example, if a user searches “Where are my orders shipped from?” the AI understands they want to know the origin location of their shipments.

Voice search takes this a step further by allowing users to speak their search queries out loud. The AI converts the audio to text, interprets the meaning and shows results. This provides a hands-free, voice-activated search option.

Both approaches create a more human-like search experience. Customers can search as if they were talking to a real person, using full sentences and conversational language. Then the AI delivers results based on meaning and context, not just matching keywords, leading to higher satisfaction and engagement.

Content Curation

Content quality assessment, as mentioned earlier, will be important for curation. This will help the content meet standards for grammar, readability, coherence and factual accuracy, while automatic content tagging via AI can suggest relevant tags, categories and taxonomies based on patterns and models in the content. Automated content moderation is another significant area where AI can identify and filter out undesirable elements like hate speech, spam and discrimination.

Content Management

AI can significantly streamline content management by automating many tasks. It can analyze materials to generate relevant metadata like titles, descriptions, keywords and categories. It can also intelligently classify content based on topics, sentiment and relevance to users.

For collaboration, AI could detect changes, highlight new content for specific team members and optimize revision workflows based on rules. It can assign tasks, route items for review/approval, and make process decisions according to defined policies. Compliance can be easier to maintain with AI analyzing content to flag potential policy violations.

Translation

Translation capabilities enable you to connect with broader audiences and drive more business growth. AI-powered translation goes beyond just word-for-word substitutions. It understands context and adapts content appropriately for each language. For example, culturally relevant examples, idioms and expressions can be localized to resonate better with international users.

Real-time translation enables your global customers to interact with your brand in their native language. Product information, support articles, marketing content and more can all be automatically translated on the fly. Readers simply select their preferred language, and the content transforms before their eyes.

Providing localized content at scale would be extremely difficult for human translators. But with AI, translations can be handled instantly to support global experiences. Visitors feel welcomed and engaged when they can consume information in their own language.

Advanced translation tools like those from Lionbridge integrate directly into your CMS and DXP platforms. This allows for AI-powered translation to be built right into your website or mobile app workflows. Content only needs to be authored once, and machine translation handles the rest.

Marketing Optimization

AI can play a major role in optimizing marketing campaigns and ad spend. By leveraging machine learning algorithms, AI can analyze past campaign performance data to determine the optimal budget allocation across channels. It can shift budgets in real time based on changing market conditions to maximize ROI.

Some ways AI optimizes marketing include:

• Automated A/B testing at scale to determine high-performing content, offers and landing pages. AI can test thousands of variant combinations simultaneously.
• AI-powered multi-touch attribution modeling to understand which campaigns and channels are driving conversions. This enables smarter budget allocation.
• Predictive analytics to forecast expected campaign performance under different budget scenarios. Marketers can adjust budgets to hit ROI goals.
• Intelligent audience segmentation powered by machine learning. AI can find lookalike audiences likely to convert based on past responders.
• Programmatic ad buying optimized by AI to bid only on impressions likely to convert based on historical data. This can reduce wasted ad spend.
• Dynamic creative optimization to serve personalized ads optimized for each user. AI tailors messaging to maximize relevance.
• Real-time budget optimization between ad networks. AI shifts budgets to better-performing platforms automatically.

Concluding Thoughts

AI has many use cases and applications that are not even covered here. As AI adoption will only increase, it’s important to carefully plan and implement AI solutions in an ethical, responsible manner.

Ultimately, AI should be viewed as a powerful tool to augment human capabilities, not replace them entirely, as we strive to create more intelligent and customer-centric digital experiences. Interested in learning more? Check out this free webinar on AI and the future of CMS.