Generative AI

What is Generative AI?

Generative AI is a category of artificial intelligence that creates new content (text, images, code, audio, or video) rather than analyzing or classifying existing data. Where earlier AI systems were designed to recognize patterns, predict outcomes, or retrieve information, generative AI produces original outputs based on patterns learned from large training datasets. Common examples include large language models that write text, image generation models, and AI coding assistants.

The term is widely used across technology, marketing, and content industries to describe systems capable of producing human-quality output at scale. In Xperience by Kentico, generative AI capabilities are embedded through AIRA, enabling content teams to generate drafts, refine existing text, produce metadata, and run autonomous marketing workflows without leaving the platform.

What are the key benefits of Generative AI for marketing and content teams?

Content production at scale: Generate first drafts, summaries, metadata, and content variants faster than any manual process, reducing the time between brief and published content.
Consistent quality at volume: When guided by a content strategy and reviewed editorially, AI-generated content maintains consistent tone and style across high volumes of output.
Personalization at volume: Generate audience-specific content variants without multiplying manual effort, supporting more targeted digital experiences across segments and channels.
Reduced time on repetitive tasks: Automate structured, high-volume tasks (product descriptions, metadata, email variants) freeing teams for higher-judgment work.
Accessible to non-technical users: Modern generative AI tools operate through natural language prompts, requiring no coding or technical training to use effectively.

Industry Insight

ChatGPT, released by OpenAI in November 2022, reached 100 million users within two months of launch, making it the fastest-growing consumer application at the time. The release brought generative AI from a research context into mainstream use across marketing, content, and product teams worldwide.

How does Generative AI work, and why does it matter for digital experiences?

Generative AI models are trained on large data sets of existing text, images, or other content. Through that training, they learn statistical patterns that allow them to produce new content following those patterns. For text, this means generating the most contextually appropriate word, sentence, or paragraph given a prompt and prior context. The output reads as if created by a person because the model learned from human-created content at scale.

For digital experience teams, this changes what is operationally possible. Volume has historically been a constraint on content quality: producing more meant either hiring more people or accepting lower standards. Generative AI removes that constraint for first drafts, metadata, and structured content variants. Editorial effort can then focus on accuracy, judgment, and brand alignment.

How does Xperience by Kentico support Generative AI?

Xperience by Kentico embeds generative AI capabilities through AIRA, making them directly available within the platform's content and marketing workflows:

Text Generation: Generate content drafts across any text field in the platform using the AIRA chat interface, from page body copy to metadata descriptions.
Text Refinement: Rewrite, shorten, expand, or adjust the tone of existing content directly within the editing interface, without switching tools.
Metadata Generation: Automatically generate image alt text, tags, and descriptions using AI, reducing manual metadata work across large content libraries.
Agentic Marketing Suite: Four specialized AI agents (Content Strategist, Customer Journey Optimization Specialist, SEO and GEO Specialist, and Campaign Manager) use generative AI to analyze performance, produce structured reports, and generate recommendations autonomously.

Generative AI in Xperience by Kentico is embedded within existing editorial workflows. AI-produced content goes through the same review and approval processes as any other content before it is published.

How do organizations benefit from Generative AI in their content strategy?

Organizations that have integrated generative AI into their content workflows report measurable reductions in time-to-publish and increases in content output without proportional growth in team size. The gains are most significant in high-volume, structured tasks: product descriptions, metadata, email variants, social content, and first drafts of longer-form pieces.

The strategic benefit extends beyond speed. Generative AI makes personalization at scale operationally viable. Teams that previously published one version of a page or asset for all audiences can use AI to produce targeted variants efficiently, supporting more relevant digital experiences without expanding headcount.

How does Generative AI fit into a responsible content strategy?

Generative AI introduces both opportunity and risk. AI-produced content reflects the quality of the prompts it receives and the patterns in its training data. Without editorial review, it can be generic, inaccurate, or misaligned with brand voice. Organizations that see the best results treat AI as a first-draft tool: AI generates, humans review, refine, and approve.

In Xperience by Kentico, AIRA is designed to work within existing governance structures. Content generated by AIRA enters the same review and approval workflows as any other content, ensuring speed does not come at the cost of accuracy or brand consistency.

What is the difference between Generative AI and Artificial Intelligence?

Artificial Intelligence is the broader field covering any system that performs tasks normally requiring human intelligence; classification, prediction, image recognition, language understanding, and decision-making. Generative AI is a specific subset focused on creating new content rather than analyzing or categorizing what already exists.

Earlier AI applications in marketing operated primarily in the analytical space: lead scoring, segmentation, recommendation engines, and predictive analytics. Generative AI adds a creation dimension. In a DXP context, this means AI can now participate in producing content, not just evaluating or targeting it.

What's the difference between generative AI and agentic AI?

Generative AI and agentic AI are related but distinct. Generative AI refers to the capability of producing new content (text, images, code) in response to a prompt. Agentic AI refers to the ability to pursue a goal autonomously across multiple steps, making decisions and taking actions without requiring a human to direct each one. The key difference is scope: generative AI produces an output in response to a single request; agentic AI executes a sequence of actions (which may include generating content, retrieving data, evaluating results, and adapting behavior) in pursuit of a defined objective.

Frequently Asked Questions.

No. ChatGPT is one application built on generative AI technology, a large language model developed by OpenAI. Generative AI is the broader category that includes many different tools and models for producing text, images, code, audio, and video. Other well-known examples include Claude (Anthropic), Gemini (Google), GitHub Copilot, Midjourney, and DALL-E.

Not as a direct replacement, but it changes how content work gets done. Generative AI handles first drafts, structured content production, and repetitive tasks well. It performs less reliably on nuanced brand storytelling, strategic judgment, and accuracy verification. Most organizations use it to increase output and reduce time on low-judgment tasks, with writers and marketers focusing on editorial direction, fact-checking, and brand alignment.

Consistency comes from the quality of the prompt and the editorial review process. In Xperience by Kentico, the Content Strategist agent evaluates content against a Content Strategy document capturing brand voice, tone, and terminology guidelines, providing structured feedback when content deviates from those standards.

Generative AI performs well on structured, high-volume tasks: product descriptions, metadata, email variants, first drafts, summaries, and page copy. It is less suited to content requiring specialized expertise, verified facts, or deep brand storytelling, those require human authorship with AI assistance rather than AI generation with human review.

Major search engines, including Google, evaluate content based on quality, relevance, and usefulness, not on whether it was written by a human or AI. Well-edited, accurate AI-generated content performs the same as well-written human content. The risk is in publishing unreviewed AI output that is generic, inaccurate, or thin in substance.

In practice, agentic AI systems often use generative AI as one of their tools. In Xperience by Kentico, AIRA's text generation and text refinement features are generative AI. The AIRA Agentic Marketing Suite: the Content Strategist, Customer Journey Optimization Specialist, SEO and GEO Specialist, and Campaign Manager, represents agentic AI that uses generative AI capabilities as part of broader, goal-directed workflows.