The sun is cresting over the horizon of an age where smart computer programs, known as agentic systems, can do tasks all by themselves, learning and making decisions just like humans. This work has been accelerated by the development of scalable generative AI large language models. These new generative AI-powered systems are and will be transforming how businesses work. This article will explain what agentic systems are, how they help in business, and how they’re different from other methods like custom software or doing things by hand.

Understanding Agentic Systems Agentic systems are advanced computer programs that can think, learn, and make decisions on their own. They are like very smart robots inside a computer. These systems use artificial intelligence to get better at what they do, making them more helpful than regular computer programs.

Agentic Systems in Business Agentic systems are super useful in businesses. They can do jobs that are boring or hard for people, like organizing lots of information, fixing mistakes in data, or even writing complicated computer code. This means people can spend time working on top of licenses and being human-centric while the agentic systems handle the routine stuff.

Business Use Cases of Agentic Systems

1. Data Cleanup: Agentic systems are great at cleaning up data. They can review a lot of information, find mistakes, and fix them. This is helpful for businesses because clean data means better decisions.
2. Coding and Software Development: These systems can write and test computer code by themselves. This is helpful for companies that make software because it means they can create new things faster and don’t always need super-specialized programmers.
3. Document Processing: Imagine having a system that can sort through hundreds of documents, file them correctly, and pull out important information. Agentic systems can do this quickly and accurately, saving lots of time.

Comparing Methods

• Custom Software: Custom software is like having a special tool for one job. But it can’t learn new things or change if the job changes.
• Robotic Process Automation (RPA): RPA is like a robot that does exactly what it’s told, but it doesn’t have the ability to think or learn anything new. It’s great for repetitive tasks that don’t change much. However, for adaptability, like dealing with unique customer requests, RPA is less effective than agentic systems, which can handle such unpredictable scenarios more effectively.
• Manual Work: Manual work involves people doing tasks by hand. It can be time-consuming and prone to errors. Humans are adaptable and can handle unexpected situations, but they can’t match the speed and efficiency of agentic systems for routine tasks. Agentic systems excel in performing tasks independently, with minimal need for human supervision.

Agentic Solutions: Several organizations are working on tooling to help build Generative AI agentic systems, including OpenAI, Microsoft, Google, and other open-source platforms.

• AutoGen
• AutoGPT
• CrewAI
• LangChain Agents
• Huggingface Transformers Agent
• Google Vertex Agent
• OpenAI Assistants
• Microsoft Co-Pilot Studio

In summary, agentic systems offer a level of adaptability, learning capability, and independent execution that is not found in custom software, RPA, or manual work. This makes them a game-changer in business. They can handle complex tasks efficiently and adapt to new challenges, ultimately transforming how businesses operate and allowing people to do more human centric work.