What is Generative AI? - Explanation & Meaning
Learn what generative AI is, how it creates new content, and why GenAI is a game-changer for businesses in 2026. Discover LLMs, diffusion models, and more.
Definition
Generative AI (GenAI) is a category of artificial intelligence capable of creating new content — including text, images, code, audio, and video — based on patterns learned from training data.
Technical explanation
Generative AI employs different architectures depending on the type of content being generated. Large language models (LLMs) such as GPT-5 and Claude 4 are based on the transformer architecture and generate text by predicting the next token in a sequence. Diffusion models like Stable Diffusion and DALL-E 3 generate images by gradually removing noise from a random starting point, guided by a text prompt. Variational autoencoders (VAEs) and generative adversarial networks (GANs) are alternative architectures for image generation. In 2026, enterprise adoption of GenAI has grown explosively: over 72% of large enterprises have integrated GenAI into at least one business process. Multimodal models that can simultaneously process and generate text, images, and audio have become the standard. Retrieval-Augmented Generation (RAG) is widely deployed to reduce hallucinations and ground outputs in business-specific data. The rise of AI agents that combine GenAI with tool use marks the next phase in generative AI evolution.
How MG Software applies this
MG Software leverages generative AI to build powerful solutions for clients. We develop AI assistants that can summarize business documents, answer customer queries, and generate reports. Using RAG architectures, we ensure generated content is always grounded in up-to-date business data.
Practical examples
- A law firm using GenAI to analyze contracts, extract relevant clauses, and generate first drafts of legal summaries, reducing document review time by 60% for attorneys.
- A marketing agency deploying generative AI to create personalized campaign copy in multiple languages, reducing campaign production time from two weeks to two days.
- A software company using AI-powered code assistants to generate boilerplate code, write unit tests, and accelerate code reviews, boosting developer productivity by 35%.
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