Introduction to AI-powered Agents and how they can benefit your workforce.
What are Agents?
AI agents can be described as a system with reasoning capabilities, memory, and the necessary tools to execute end-to-end task completion. Consider AI agents as your new AI team members that can work alone, or as part of a team of other agents and real people.
Agents have clearly defined roles and responsibilities, and they can choose how best to get their work done using the knowledge they access, and the tools you equip them with.
To learn more about AI agents, see AI agents and agentic workflows.
Get started with agents
There are a few ways you can get started with building your own agents:
Access pre-trained and expert AI agents
You can use one of our existing expert AI agents, which have been created by domain experts to perform specific tasks in your industry. For more, see Pre-trained and expert AI agents.
Create your AI agents
You can build an agent entirely from scratch. Our agent quick-start guide will get you familiar with all the building blocks that make up building out your agents.
Your AI agent workforce
1. Performs endless tasks
You can scale agents to meet all your needs. Run the necessary agents to perform the tasks you need to be down, without recruiting new employees or increasing the workload of existing ones.
2. Increases productivity
You can use agents to automate repetitive time-consuming tasks, so that your human employees can be freed up to do more engaging work.
3. Can work autonomously
Agents can complete work end-to-end without you needing to be involved at all.
When you run AI agent, the task is performed in the back without needing human input at all.
4. Adaptive and non-deterministic
Agents do not have to respond to tasks in the exact same way ever time like traditional software solutions. They have the ability to choose the most appropriate way to respond on a case-by-case basis.
FAQs
When should you use an agent?
AI Agents are especially well-suited for repetitive tasks, no matter how complex the task is. For example, many financial analysts spend a huge amount of time searching for insights on new markets, including recurring type of data, when they could instead focus on more interesting work further down the funnel, like analyzing the insights and take decision.
When should you NOT use an agent?
Building a highly-skilled agent might take some time. If you can’t be sure that the agent you want to build will become a valued part of your team on an ongoing basis, it’s better to direct your energy and resources elsewhere.
Who should build agents?
Domain experts or team members who are currently doing the work you want to delegate to your agent should be the one creating the AI agent. Consider adding AI enthusiasm in the process to improve the instructions and prompts to give to the agent.