Generative AI will soon become the differentiating factor between businesses.
What has made it the game changer today?
Generative AI (GenAI) empowers businesses to unlock new and innovative ways to boost their income, lower their expenses, enhance their efficiency, and manage their risks better.
Generative AI is a branch of artificial intelligence that can create new content such as text, images, audio, or video.
Generative AI is led by Large Language Models (LLMs). LLMs are huge deep learning models that are trained beforehand with huge data at their disposal. The transformer that they are based on is a group of neural networks that have an encoder and a decoder with the ability to pay attention to themselves.
LLMs have become essential for many domains that rely on web and visual communication, such as design, marketing, journalism, writing, consulting, customer service, and more.
However, many enterprises still struggle to deploy AI solutions at scale. There is excitement, of course, but there is also confusion and lack of knowledge about GenAI.
Adobe is one of the front-runners that has quickly embraced AI as a key component of its products like Adobe Experience Manager and demonstrated its potential at the Adobe Summit 2023.
Let’s examine AEM and Generative AI to help you adopt a more balanced perspective on this topic.
Generative AI Use Cases with AEM
Generative AI has many potential use cases in Adobe Experience Manager content management system that helps businesses deliver personalized digital experiences.
Some of the use cases are:
- Content generation: Generative AI helps AEM users create engaging and relevant content for their websites, apps, or campaigns. It can write product descriptions, blog posts, headlines, captions, or summaries based on the user’s input or preferences.
- Content optimization: GenAI enables to improve the quality and performance of your content by suggesting edits, enhancements, or variations. It can rewrite content to match a specific tone, style, or audience, or to optimize it for SEO or conversion.
- Content personalization: It guides you to tailor the content to different segments, personas, or contexts. It generates personalized recommendations, offers, or messages based on the user’s behavior, preferences, or location.
- Content moderation: The tool empowers AEM users filter out inappropriate or harmful content from their platforms. It detects and removes spam, profanity, hate speech, or fake news from user-generated content or comments.
How Generative AI in AEM Helps SEO?
In Adobe Experience Manager, Generative AI can help SEO by producing high-quality, relevant and engaging content for web pages, blogs, social media posts and more.
Some of the benefits of using GenAI in AEM for SEO are:
- It saves time and resources by automating the content creation process and reducing the need for manual editing and review.
- It improves the content quality and consistency by following the best practices and guidelines for SEO, such as keyword density, readability, structure, metadata and more.
- It increases the content variety and diversity by generating different versions of the same content or creating new content based on user feedback, preferences and behaviour.
- It enhances the user experience and satisfaction by providing personalized, relevant and engaging content that matches the user intent and context.
Generative AI in AEM is powered by Adobe Sensei, a framework that leverages machine learning, natural language processing and computer vision to deliver intelligent and creative solutions. Adobe Sensei can analyse large amounts of data, learn from it, and generate content that meets the specific needs and goals of the users and the businesses.
When is the Right Time to Combine AEM and Generative AI in Your Project?
Before integrating AEM with GenAI, here are some factors you should consider:
- The scope and complexity of your project. If your project involves a large amount of content, multiple languages, or diverse formats, generative AI can help you automate and streamline the content creation and delivery process. However, if your project is simple or small-scale, you may not need generative AI, or it may not be worth the investment.
- The quality and reliability of your data. Generative AI relies on data to learn and generate content. Therefore, you need to ensure that your data is accurate, relevant, and consistent. AEM can help you manage and organize your data sources, but you also need to verify and validate the data quality before feeding it to Generative AI models.
- The goals and expectations of your project. Generative AI can produce impressive and novel content, but it is not a magic solution that can solve all your problems. You need to have clear and realistic goals and expectations for what Generative AI can do for your project, and how it aligns with your business objectives and user needs. You also need to monitor and evaluate the performance and impact of Generative AI on your project outcomes.
Generative AI will require constant technological innovation at every level, as the underlying technology is expected to change rapidly. To leverage new capabilities and meet the high computing demands of Generative AI, a modern, cloud-based infrastructure and a data platform and architecture that span the enterprise will be crucial.
We at Embitel are equipped with an expert team who handle AEM services and Cloud solutions for our customers globally and bring 17 years of experience to the table. We offer end-to-end support for our customers with 24/7 support. For more information and a free demo, reach out to our team at sales@embitel.com
