AI Insights

The landscape of Generative AI is changing at a breathtaking pace. Today, the term “AI agents” is on everyone’s lips, and these technologies are rapidly permeating many areas of our lives. To understand how these changes will affect society and the labor market, it is useful to look at the levels of artificial intelligence development proposed by Sam Altman. He distinguishes five stages:

1. Chatbots – The basic level where AI is capable of simple conversations and performing standard tasks.

2. Reasoners (conversational chatbots with reasoning abilities) – Systems that can analyze information and make decisions based on logic. Following the release of OpenAI o1 models family, we are already at this stage.

3. Agents – Autonomous systems that not only interact with users but also coordinate their actions with other agents to solve more complex problems.

4. Innovators – AI capable of generating new ideas and making scientific discoveries.

5. Organizations Composed of AI Agents – Structures where key processes are managed by interacting agents, potentially transforming traditional models of organizational work.

Agents are considered to be a cutting-edge paradigm of the AI world now. Having this in mind, let’s take a closer look at their impact on our lives and labor market.

The Benefits of AI Agents Today and Their Impact on the Market

AI agents are already being actively implemented across various sectors, delivering tangible benefits by automating routine operations. Examples of their use include:

• Customer Support:
  Agents often serve as the first line of interaction. They handle incoming calls, respond to standard queries, and escalate issues to human operators when problems become too complex. Such solutions are widely used in banks, telecommunications companies, and service centers, reducing the load on staff and speeding up query resolution.
• Virtual Assistants and Online Chat Services:
  Many companies integrate agents for online ordering, consultations, and appointment scheduling. Operating around the clock, they provide continuous support and efficiently execute standard tasks.
• Logistics and Retail:
  Agents help automate order processing, track deliveries, and manage inventory, thereby enhancing efficiency and reducing costs.

In addition, AI agents offer several key advantages:

• Multilingual Communication:
  They are capable of adapting to the language most comfortable for the user, eliminating language barriers and improving communication quality.
• Consistent Courtesy and Friendliness:
  Regardless of the client’s emotional state, an agent maintains a polite and friendly tone, which helps reduce conflicts and increases customer satisfaction.
• 24/7 Operation:
  Agents can function without breaks, which is especially important for supporting global services and responding quickly to requests at any time of the day.
• Rapid Skill Acquisition:
  Unlike training a large group of employees, adding new functions and knowledge to AI systems occurs swiftly. This enables companies to adapt more quickly to market changes and technological innovations while reducing the costs associated with continuous employee training.

This automation of routine operations is transforming the professional landscape: as jobs requiring repetitive tasks are phased out, the labor market is gradually shifting towards fields that value creative thinking, strategic planning, and interdisciplinary analysis.

Approaches to Creating AI Agents

Today, developing AI agents has become accessible through several approaches:

Low-code / No-code Platforms

These solutions allow you to create and host agents without deep programming knowledge. They are ideal for implementing simple tasks when the necessary functionality is already integrated into the platform. Advantages include:

• Rapid Development and Testing: Quickly creating a prototype to test with a target audience.
• Low Costs: Eliminating the need to engage a team of developers for the initial implementation.

However, the obvious drawback is limited flexibility: if a complex or non-standard functionality is required, the platform may not be able to handle it. One more issue to consider is vendor lock in. There might be no easy way to move to another provider and preserve all data and workflows you’ve produced.

Programming Using Specialised Frameworks

Numerous tools such as LangGraph, LLamaIndex, SemanticKernel, and AutoGen enable the development of agents with complete freedom. Key benefits include:

• Full Customisation: The ability to develop a solution that precisely meets business needs.
• Scalability and Integration: Easier implementation of new functions and integration with other systems.

The downside of this approach is the necessity for skilled developers, which leads to higher costs and longer development times.

Hybrid Approach

In practice, a combination of both methods proves effective. Initially, low-code / no-code platforms can be used to quickly create prototypes and test the idea with the target audience. Once the concept’s value is confirmed, development can transition to a full-fledged solution using specialized frameworks, ensuring optimization for specific business needs.

Conclusion

AI is rapidly permeating every aspect of our lives, and new examples of its application emerge daily. Organizations have moved from experimental projects to the full-scale implementation and use of AI agents, allowing them to automate routine processes, enhance efficiency, and create conditions for fostering innovation. To maintain a competitive edge, those organizations that have not yet invested in these technologies need to consider starting sooner rather than later. In the rapidly evolving landscape of Generative AI, adapting to and integrating AI agents is becoming a critical factor for future success.