AI Agents: from Chatbots to Autonomous Co-workers

Imagine a company that replenishes stock levels before they all go - items like printer paper and toner in office, lubricants and cleaning material in manufacturing plant, mineral water and snacks at large event venue. An AI agent can monitor inventory levels, trigger automatic reorders, and even negotiate the best deals with suppliers – all thanks to large language models (LLMs) that understand complex communication.

But that's just the beginning. Imagine AI agents on both sides of a business transaction, one generating leads contacting potential buyers, negotiating the prices, and another one finding the best supplier for the goods providing best prices and delivery terms. There may be hundreds or even thousands of such specialized AI agents working together in swarms, handling many aspect of a company's operations, automating processes, and reaching new levels of efficiency. Is there still a place for human?

From Conversation to Intelligent Action

AI agents have come a long way from their early days as basic chatbots. Today, they're not just about mimicking human conversation leveraging LLMs, they can automate tasks, make decisions, and even learn from experience and autonomously improve.

Unlike traditional automation tools and Robotic Process Automation (RPA), the AI agents are leveraging LLMs and techniques like Retrieval-Augmented Generation (RAG) to ingest company-unique data in their decision process and execution. They can add value in several ways:

• Understanding Context: They can analyze user intent and respond accordingly, making them ideal for customer service or virtual assistant roles.
• Adapting to Change: Whether navigating a factory floor or analyzing financial markets or finding best supplier, AI agents can adjust to dynamic situations, making real-time decisions.
• Continuous Learning: By interacting with data and users, AI agents become more proficient over time, constantly improving their performance and time to completing the task.

The AI Landscape: Your Toolkit for Success

Several big-tech companies offer sophisticated platforms for building AI agents, each with its own strengths, unique features and maturity in enterpris environment. Regardless what names are used - AI Agents (Google, Nvidia), AI Assistants (IBM, AWS), Bots (OpenAI) or Copilots (Microsoft, Salesforce), their objectives are similar - moving from conversations to actions and improving enterprise productivity.?? Here are a few examples:

• IBM watsonx platform , with watsonx Assistant and watsonx Orchestrate : Renowned for its versatility, watsonx allows you to build AI apps and assistants using wide range of LLMs for multiple tasks and applications.

• Google Vertex AI Agent Builder (Preview): This platform helps to create conversational AI agents using natural language.
• Microsoft Azure OpenAI with Semantic Kernel SDK: can use LLMs to build bots/agents with own Copilot experience assisting developers by suggesting code and automating repetitive tasks.
• Salesforce Einstein 1 with Copilot builder: Tailored for the CRM realm, Einstein helps automate tasks and gain insights from customer data.
• Amazon Q (newly announced): This newcomer from AWS helps application developers, data scientists, and IT professionals develop AI-powered assistants.

Getting Started with AI Agents

The key to unlocking the potential of AI agents lies in understanding your specific needs. Here are some key questions to consider:

• What tasks are currently the most repetitive and time-consuming?
• What level of user interaction is necessary for these tasks?
• Do you have existing data that can be used to train your AI agent?

The Future of Work: A Human-AI Duet

Is there still place for human? Absolutely, yes! AI agents aren't here to replace humans; they're here to empower them. Humans will continue to define goals, KPIs, set guardrails, and maintain control over processes. Inference in production requires also regular testing of trustworthiness and ethics of deployed AI agents.

By automating tedious tasks like for example re-ordering items to replenish stocks, AI agents free up human time and energy for more creative activities. Code generations deserves separate article. This human-AI collaboration is the key to unlocking the true potential of artificial intelligence. As this technology continues to evolve, we can expect even more innovative applications of AI agents, further transforming the digital landscape.

?Conclusion

The rise of AI agents marks a new era in artificial intelligence. With tech giants leading the way, the future of AI agents is brimming with promise. As these intelligent agents continue to develop, they will undoubtedly play a crucial role in shaping the future of technology and business.

Are you already using AI agents in your business processes? What's your exeperience? Share it in comments?