One of the latest products of artificial intelligence technology, generative AI is effective in easing the workload of both daily and professional users and automating their tasks. Agentic AIs powered by generative AI models are ideal for easing the workload of businesses and organizations and automating repetitive complex tasks. Both types of AI have advantages, disadvantages, areas of use, and limits.
In this article, we will explore the differences between generative AI and agentic AI.
If you are ready, let's get started!
TL; DR
- Agentic AI refers to autonomous systems designed to achieve objectives independently and autonomously.
- Agentic AIs work by autonomously acting AI models and processing results to complete specific objectives given by users.
- Agentic AIs can integrate into complex workflows of businesses and organizations and automate most tasks.
- Generative AIs are technologies focused on content generation that work with human guidance.
- While Agentic AI can work completely autonomously and make independent decisions, generative AI needs human guidance.
- Agentic AIs are goal-oriented, and generative AIs are output-focused.
- Agentic AI adapts to the environment of the organization and business it is integrated with, while generative AI cannot.
- If you are looking for an AI assistant that will lighten your workload and integrate into your complex workflow, TextCortex is the way to go.
What is Agentic AI?
Agentic AI refers to autonomous systems designed to achieve objectives independently. These AI agents can make decisions, plans, and road maps and act without human interactions. Agentic AIs assign tasks to different AI models to achieve user-given objectives and use all results to perform the tasks in the best possible way.
How Does Agentic AI Work?
AI agents use complex communication methods between AI models to work completely autonomously. An AI agent can communicate between its AI models to achieve the perfect output and can generate multiple iterations until the desired output is obtained. Agentic AIs can adapt to the knowledge base and environment provided by the user and create and independently act on the most effective method to achieve the given objectives. Moreover, AI agents start to work more usefully and effectively by improving themselves with each output.
Key Capabilities of Agentic AI
Agentic AIs offer features such as task automation and output generation to increase the efficiency of enterprises and organizations.

They possess the capability to perceive, analyze, learn, adapt, and act independently and autonomously to achieve their goals. Some of the key capabilities of agentic AI include:
- Autonomy
- Reasoning
- Workflow Optimization
- Independent Decision Making
- Environment Adaptation
- Self-Learning
What is Generative AI?
The concept of Generative AI is a type of AI that has become popular with OpenAI’s ChatGPT and can generate new and unique data using existing data patterns. Generative AI is a technology that works with the prompting method and can understand user inputs and produce related outputs. Generative AI can generate human-like, concise, and clear outputs in seconds.
How Does Generative AI Work?
Generative AI analyzes input data using technologies such as natural language processing, machine learning, and neural networks, and then generates new and unique output data using its parameters and trained data. Generative AI is a technology that works with human interaction to shorten and simplify users' repetitive and longer tasks.
Key Capabilities of Generative AI
Generative AI models can generate content in a variety of types, including text, code, images, video, audio, and music. Generative AI models can learn various writing, drawing, and sound patterns by analyzing large amounts of data and mimicking them while generating content. This capability is ideal for reducing workload in professional fields such as marketing, entertainment, design, content generation, human resources, customer service, and finance.

Some GenAI models allow users to customize the outputs to be generated. Thus, users can generate outputs that use their tone of voice through Generative AI models. This capability is especially effective in areas that require professional brand voice use, such as marketing and customer support.
Agentic AI vs. Generative AI: What is the Difference?
Agentic AI and generative AI are artificial intelligence technologies with similar features but different capabilities. There are sharp differences, areas of use, working methods, and target audiences that separate agentic AI from generative AI. If you are wondering about the differences between agentic AI and generative AI, we’ve got you covered.
Automation Capabilities
What makes Agentic AI stand out is its completely autonomous operation and independent decision-making capabilities. Agentic AIs can make real-time decisions, change outputs according to the environment, and achieve given objectives by assigning tasks to AI models.

On the other hand, the automation offered by generative AI models is limited to content generation only. Generative AI offers creative content generation to its users and requires input and prompts for triggers.
Goal-Oriented & Output-Oriented
Agentic AIs are goal-oriented AI tools designed to achieve the specific objectives of organizations. Agentic AIs can navigate complex systems, make decisions to reach defined objectives, and optimize resources such as AI models and knowledge.
On the other hand, generative AI models focus entirely on output-oriented generation. It focuses on producing creative outputs based on given inputs, without making independent decisions. The power of Generative AI models lies in quick, creative, human-like, and high-quality content generation.
Adaptation
Agentic AI actively engages with its environment, allowing real-time adaptation and decision-making to achieve given goals. If you are looking for an AI tool that constantly monitors your organization's resources and makes decisions based on the current situation, Agentic AIs will be the ideal choice for you.
On the other hand, when using generative AIs, the user needs to observe the environment and resources and prompt accordingly. Generative AI lacks dynamic interaction with its surroundings and cannot adapt to new information or feedback.
Tool Use
Agentic AIs are tools that automate APIs to plan and assign tasks to various tools. To use Agentic AIs, you simply assign an objective to it. Then, Agentic AI will assign tasks to the AI tools it owns and combine their outputs to complete the final task.

On the other hand, generative AIs have a single function and can complete a single task assigned. Agentic AIs do the heavy lifting by triggering different generative AI models and presenting the final output to the user.
TextCortex
If you are looking for an AI assistant that will automate your complex workflow and has state-of-the-art AI models such as GPT-4o, Claude 3.5 Sonnet, DALL-E 3, TextCortex is designed for you. TextCortex can activate different AI models autonomously and independently to achieve the given objectives by integrating them into the complex workflow of enterprises and organizations and generating final output for users.

Some of the capabilities of TextCortex include:
- Multiple LLMs such as GPT-4o and Claude 3.5 Sonnet
- Multiple AI Image Generators such as DALL-E 3 and Stable Diffusion
- Web Search with Citations
- Organizable Knowledge Bases
- ZenoChat, the Conversational AI Assistant
- Powerful RAG
- Complex Task Automation
- Writing Assistance
- Natural Language Capabilities
- Image Generation
Frequently Asked Questions
What is the difference between generative AI and agentic AI?
Generative AI technology is a technology that produces outputs based on user inputs and requires human input or guidance to act. On the other hand, agentic AI is an AI system that automates all processes of an objective from output generation to task completion. If you need to complete a single task, generative AI is sufficient for you, while you can use agentic AI to achieve complex and multi-step objectives.
What is the difference between agentic and non-agentic AI?
Agentic AI is capable of adjusting its actions independently and autonomously to achieve specific goals, and it can adapt to its environment and changing conditions. In contrast, non-agentic AI requires user guidance to generate output and cannot make autonomous decisions. By integrating AI assistants like TextCortex into your organization, you can automate complex tasks that lead to increased efficiency and improved profitability.
How does agentic AI differ from traditional AI?
Traditional AI is the basic AI technology that completes simple tasks such as translation and auto-response through interaction. Agentic AI is a tool that can adapt to the environment of organizations to complete complex objectives, analyze their knowledge sources, and automate objectives by assigning tasks to the generative AI models it hosts.