The way humans interact and collaborate with AI is changing and developing every day. The latest of these developments is Agentic AIs developed for enterprises and organizations. Agentic AIs are software programs that have their decision-making mechanism and do not need a command to take action. Agentic AIs prepare task and sub-task lists to complete the given objectives by integrating them with your enterprise data and taking actions that will reach the objectives step by step. If agentic AIs are new to you and you are looking for information about them, we've got you covered!

In this article, we will discover what Agentic AIs are and examine their best applications.

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TL; DR

  • Agentic AIs are software programs that offer a combination of different AI models and techniques and aim to automate the workload of companies.
  • While generative AI requires human input and guidance to generate output, agentic AIs can independently complete the assigned task, including decision-making and taking action.
  • Agentic AI follows four basic steps to work: information gathering, reasoning, action, and self-training.
  • Agentic AIs provide organizations with benefits such as time-saving, automation, improved productivity, enhanced customer support, and increased efficiency.
  • The most common areas where agentic AIs are used are customer support, content generation, software engineering, and documentation.
  • If you are looking for an AI assistant that will automate all your company tasks and save you time, TextCortex is designed for you with its multiple LLMs, knowledge bases, web search, and seamless integrations.

What is an Agentic AI?

Agentic AIs are a combination of different AI techniques, models, and approaches to empower organizations by analyzing data, setting goals, taking actions, and automating complex tasks with minimal human workforce. Agentic AIs are problem-solving machines that provide near-human automation in many areas of a company and improve with every interaction by adapting to their environment.

What is the Difference Between Agentic AI and Generative AI?

Generative AI models are technologies that focus on generating output in different formats such as text, code, image, and video, and are kickstarted with a command. You can leverage Generative AI models for tasks such as brainstorming, data analysis, and text generation. Generative AI primarily focuses on content creation based on human input and guidance.

What is the Difference Between Agentic AI and Generative AI?

On the other hand, agentic AIs are action-oriented technologies that provide independent decision-making capabilities and generate insight by integrating with company data. Agentic AIs can analyze situations, formulate strategies, create tasks and sub-task, and execute actions to achieve specific goals with minimal human input.

How Does Agentic AI Work?

Although each agentic AI tool has different working principles and forms according to its purpose and features, they all have a common four-step process:

  • Information Gathering: The AI ​​agent collects data that it can use by observing the environment and company data it is in.
  • Reason: After completing the observation part, agentic AI creates the necessary tasks to achieve the objectives and assigns generative AI models such as LLM and image generator to the tasks.
  • Act: After completing the planning phase and task assignment, agentic AI executes the strategy it has established to achieve the objectives.
  • Learn: After completing the entire process, agentic AI trains itself with feedback and output and continues to adapt to your enterprise by developing.
How Does Agentic AI Work?

The Benefits of Agentic AI

Integrating AI agents into your company comes with lots of advantages. You can shape agentic AIs according to your organization’s needs, give them objectives, and automate repetitive complex tasks. Some of the benefits of Agentic AIs include:

  • Increased Efficiency
  • Improved Productivity
  • Enhanced Customer Support
  • Greater Specialization
  • Innovation

Agentic AI Landscapes

Agentic AIs are multi-functional AI assistants that can take on different roles depending on the needs of the organization. Agentic AIs bring together all the AI ​​models you need on your behalf and use them to achieve the given objectives. Let’s take a look at a few agentic AI landscapes.

Customer Support

Agentic AIs offer features such as enhanced self-service capabilities and automated routine communications such as email writing to improve customer support. For example, instead of outputting phrases from FAQs or customer support documentation, you can use agentic AIs to have your customer support AI chatbot analyze this data and customer input to produce personalized responses. This way, you can provide customers with concise, clear, and personalized responses, which can boost customer loyalty.

Agentic AIs, unlike humans, do not need to sleep, eat, or take breaks, so they can provide 24/7 service to customers. This feature is an effective solution, especially for online and multinational companies. Regardless of the time zone, your customers can always reach active customer support.

Content Generation

Agentic AIs can understand the needs of your organization and quickly generate high-quality and concise content. Since Agentic AIs develop themselves by analyzing the environment they are integrated with, they can understand the needs of your company and generate documents such as personalized marketing content and project proposals. Thus, you can automate a wide range of your company's content generation tasks from marketing to sales and save time.

Software Engineering

AI agents can increase developer productivity by automating repetitive coding and fixing errors in code. According to McKinsey research, AI could automate 30% of work hours, including engineering, by 2030.

Documentation

Agentic AIs can integrate with enterprise data, complete assigned objectives, and enhance the company documentation process with AI model capabilities. Agentic AIs can both handle assigned documentation writing tasks and create new and unique company documentation to complete their objectives.

TextCortex – Enterprise AI Agent

If you are looking for an AI assistant that you can integrate into your workflow and support your enterprise with features such as multiple LLMs, image generators, web search, knowledge bases, brand personas, and content automation, TextCortex is designed for you. TextCortex offers its users advanced AI features with 30,000+ integrations. So you can continue to use TextCortex without interruption in every corner of the internet!

You can train TextCortex with your internal data using knowledge bases and use ZenoChat to autonomously generate a wide range of documents from project proposals to progress reports. What's more, ZenoChat's web search feature also lets you automate tasks that require up-to-date Internet data, such as market research.

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Frequently Asked Questions

What is an agentic AI?

Agentic AI refers to an advanced AI system that autonomously takes actions, makes decisions, solves problems, and creates tasks and sub-tasks to achieve given objectives. By integrating Agentic AI into your organization, you can automate most tasks that require human input.

What is the difference between GenAI and agentic AI?

Generative AI requires human input and guidance to take action or generate output and complete tasks under specific conditions. Agentic AI are AI systems that also include generative AI and can independently take action to generate output or complete objectives.

Is ChatGPT an agentic AI?

ChatGPT is a Large Language Model (LLM) and does not offer agentic AI features. However, ChatGPT is a high-performance LLM that is used to power most agentic AI. Most agentic AIs offer ChatGPT’s LLM capabilities to their users in reasoning, coding, and text generation tasks. For example, TextCortex offers both GPT-4 and GPT-4o models to its users, promising to complete given tasks with maximum efficiency.

What is the difference between LLM and agentic AI?

You can think of Agentic AI as a method that combines a wide range of AI technologies, including LLMs. LLMs are programs that generate the desired outputs as long as a command is given. Agentic AIs are decision-making mechanisms that understand the needs of companies and activate LLMs to generate outputs.