Getty Images


Generative AI's effect on content management systems

Generative AI's ability to create content can enhance workflow automation within a CMS. Yet, organizations must implement guardrails to ensure data privacy and content quality.

The relentless pace of technological innovation is changing the content management landscape.

Generative AI (GenAI) sits at the forefront of this revolution, reshaping the way content management systems (CMSes) function. It sets new benchmarks for efficiency, personalization and innovation as it automates tasks that were traditionally the domain of human creativity, like writing and graphic design.

However, organizations that integrate GenAI into their content management (CM) workflows face challenges with ethical considerations, quality control and the need to balance automation with human oversight. These challenges make the exploration of GenAI's role in CM a strategic imperative as much as a technical assessment.

Explore key capabilities and limitations of GenAI in CM and learn how to transform its challenges into opportunities.

What is generative AI?

Generative AI creates new content based on large training data sets. It interprets training data and uses it as a springboard to create its own content, like articles and images, that mirrors human output. GenAI is a leap from conventional AI's analytical capabilities to a more creative and generative function that can mimic human thought processes and creativity.

5 ways generative AI fits into a CMS

The integration of GenAI into CMS platforms enhances traditional workflows because it can automate content creation. This automation boosts employee efficiency, as it lets content creators focus on higher-level tasks, like content planning and strategy. Additionally, it analyzes customer data to let organizations create highly personalized digital experiences.

Explore the five main use cases of GenAI in a CMS to optimize content processes.

1. Generates product descriptions

CMSes can use GenAI to automatically create detailed product descriptions to captivate potential customers. This capability can streamline content creation for employees like marketers and help each product stand out from its competitors.

2. Enhances SEO

GenAI's ability to analyze content can help creative teams improve search engine optimization (SEO) efforts. For instance, a CMS vendor might offer a GenAI tool that scans marketing copy, like blog posts, and suggests revisions to keywords, titles, headers and formatting, to improve a website's search engine rankings. It might also offer tools to create SEO-optimized meta tags.

These automations can improve readability, optimize content for search engine algorithms and increase organic traffic and visibility.

3. Improves content personalization

GenAI in a CMS can analyze customer data, like purchase history and web behavior, and use it to personalize content for each online visitor. This makes every online visit unique, with highly relevant promotions, product recommendations and advertisements for individual users.

A personalized digital experience shows users the offers and products they want to see, which can improve customer engagement, satisfaction, retention rates and conversion.

4. Generates long-form content

To engage audiences, content teams must keep content fresh and relevant. GenAI helps with this, as it can autonomously generate long-form content like articles and blog posts. This automated content creation can make sure an organization's website remains engaging and informative without requiring constant manual updates.

5. Improves chatbots

Organizations can incorporate AI-powered chatbots within CMSes to improve user interactions. These chatbots offer real-time communication, so they can relay requested information to customers, resolve queries or engage users in a way that feels more personal and immediate than traditional chatbots.

3 challenges of generative AI for content management

Despite the benefits of GenAI, it presents ethical and quality challenges that may concern organizations.

1. Privacy concerns

The use of GenAI raises privacy concerns regarding how organizations use customer data to train their tools and generate content. To navigate these concerns, organizations should identify broad ethics principles, like transparency and respect for privacy, and use them to set data management policies and procedures.

For example, organizations that use customer data to train their GenAI tools should inform customers for transparency. Additionally, they should implement strong privacy policies to protect user information and achieve compliance with data protection regulations.

2. Lack of creativity

Although AI can generate content, it doesn't possess the innate creativity and nuance of a human creator. Therefore, GenAI content requires human oversight and editing to ensure it aligns with quality standards and brand voice, and that it doesn't plagiarize existing content.

3. AI hallucinations

The potential for GenAI to create misleading, inaccurate or completely false content, known as AI hallucinations, can damage a brand's reputation. For example, if an organization uses GenAI to write factually inaccurate blog articles, audiences will eventually associate the brand with misinformation and poor-quality content. To uphold content integrity, organizations must implement guidelines and oversight to ensure the accuracy of GenAI output.

Key takeaways

The integration of GenAI into CMSes represents a technological leap forward. It can automate creative tasks and offer innovative digital experiences, yet this journey brings challenges that require careful navigation. CM professionals must address key issues, like privacy, quality and AI hallucination, to protect customer data and establish content quality.

In the near future, the fusion of human creativity and GenAI could be the cornerstone of successful CM strategies.

Robert Peledie is the director of CRM consultancy 365Knowledge Ltd., with years of consulting experience in global organizations.

Dig Deeper on Content management software and services

Business Analytics
Data Management