In this guide to AI agents, you'll discover how these autonomous applications go beyond the traditional capabilities of generative AI models, combining logic, reasoning, and access to external information to achieve specific goals.
In simple terms, an AI agent is an application designed to achieve a goal by observing the world and acting on it through tools at its disposal. AI agents are autonomous and can act independently of human intervention, especially when they have clear objectives to pursue. Furthermore, they can be proactive: even without explicit instructions, they can reason about what the next step is to take to achieve their final goal.
Table of Contents
- How to Create AI Agents
- Practical Applications of AI Agents
- Benefits for Companies
- The Challenges to Face
- Conclusions
- FAQs
How to Create AI Agents {#how-to-create}
AI agent technology has made great strides in recent years, meaning that creating your own AI agent is now accessible to anyone with a computer.
Anyone can access the OpenAI playground to create their own AI Agent. However, the process is not straightforward. This is why platforms like Crafter.ai simplify the development process and management of AI agents, combining tools and features within a hybrid platform that allows you to benefit from the latest innovations made available by the Big Players (ChatGPT, Gemini, Claude, Mistral, Llama), without the complexity of having to know each of these models.
To start creating your own agent you need to clarify its task: what will it need to be able to do?
For example:
- To create an AI agent tasked with answering a large number of questions, drawing on a set of documents, it is advisable to use supervised LLMs with RAG technology.
- When it is crucial to ensure precise and predictable behavior (management of prices, discounts, reservations), it will be preferable to use the Conversation Designer which allows you to design bots that perform specific tasks with absolute certainty.
Practical Applications of AI Agents {#applications}
AI agents are revolutionizing numerous industries, from pharmaceutical research to customer service, improving efficiency and reducing costs. Here are some concrete examples:
Chemical Synthesis in Drug Discovery
Pharmaceutical giant Johnson & Johnson uses AI agents to optimize the chemical synthesis process in drug discovery. These agents determine the best time to perform the "solvent switch", a critical phase for the crystallization of molecules. The process, which previously required many manual iterations, is now faster and more precise.
Financial Analysis
Financial analysis firm Moody's has developed a multi-agent system to carry out tasks such as comparing sectors and analyzing company documents. These agents work synergistically and can arrive at different conclusions on complex topics, offering a more nuanced view of information.
Code and Marketing Automation
eBay has created an AI agent framework that uses different language models for tasks like translating and writing code. Agents also learn user preferences, becoming increasingly sophisticated and autonomous over time.
Internal HR Support
With the "askT" agent, Deutsche Telekom offers its employees a tool to get answers about company policies, benefits and products. This agent is able to perform tasks such as managing vacation requests directly in HR systems.
Customer Service Support
Spanish company Cosentino uses a "digital workforce" of AI agents to fill customer service gaps. These agents replaced the jobs of 3-4 people, allowing human employees to focus on higher value-added tasks.
Benefits for Companies {#benefits}
AI agents promise a remarkable return on investment, allowing companies to:
- Reduce the number of working hours for repetitive tasks
- Optimize the use of human resources, moving them towards more strategic activities
- Automate complex processes, improving operational efficiency
- Scale operations without proportionally increasing headcount
The Challenges to Face {#challenges}
Despite the benefits, AI agents present some challenges:
- Risk of bias: they may generate biased information or rely on inaccurate data
- Human supervision needed: it is essential to implement adequate oversight and quality controls
- Technical integration: connecting agents to existing enterprise systems requires expertise
The Crafter.ai platform integrates RAG – Retrieval Augmented Generation technology for greater precision and accuracy of responses, reducing the risk of hallucination.
Conclusions {#conclusions}
AI agents represent a turning point in the use of artificial intelligence, allowing companies to go beyond simple automations and tackle complex tasks autonomously. With responsible use and appropriate oversight, these tools can transform the way businesses operate, opening new frontiers of efficiency and innovation.
Source: WSJ
FAQs {#faqs}
What are AI agents? AI agents are autonomous applications designed to achieve specific goals by observing the context in which they operate and acting through available tools, without the need for constant human intervention.
What is the difference between a chatbot and an AI agent? A traditional chatbot follows predefined rules and responds to specific questions. An AI agent is much more sophisticated: it can plan actions, use external tools, make contextual decisions, and autonomously complete complex objectives.
How do you create an AI agent? You can start with platforms like Crafter.ai that simplify the development process. The first step is to clearly define the agent's task, then choose the most suitable technology (LLM with RAG for document-based answers, Conversation Designer for predefined flows), configure the knowledge base, and test the behavior.
Are AI agents suitable for SMEs? Absolutely. Platforms like Crafter.ai make AI agent creation accessible to small and medium-sized businesses as well, with no-code or low-code solutions that don't require advanced technical expertise.
Which sectors benefit most from AI agents? Customer service, retail, banking, insurance, healthcare, logistics and HR are among the sectors obtaining the greatest benefits from AI agent adoption, thanks to the automation of repetitive processes and personalization of customer experience.
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