When companies consider integrating an autonomous AI agent into their organization, it often raises concerns.
What will be the impact on the current team? How to supervise this agent and guarantee data security? The success of this transformation relies on a paradigm shift: considering these agents as full members of the team.
Today, the introduction of agentic AI within teams raises legitimate questions about work organization and security. To move forward calmly, this involves eliminating fears. AI agents will not replace humans: they will serve as a link between employees and the technological tools of tomorrow, becoming a direct extension of the teams.
Technology that integrates all services
Unlike more traditional technologies, the arrival of AI agents in business does not only concern the IT department. It is a global project that affects all departments, from finance to human resources and general management.
AI must become part of the company culture. For this, we must not hide its use. Rather, it is essential to communicate transparently with employees about how these agents will simplify their daily work, accelerate growth and improve customer service. By entrusting repetitive tasks to AI, employees find time for more strategic and creative missions.
Start small, aim right
Before getting started, it is essential to carry out an audit of working methods in order to target needs. Once the processes have been analyzed, it is appropriate to experiment on two or three strategic activities. The choice depends on the technical response: it could be designing a tailor-made agent for a specific task or using a ready-to-use agentic AI solution already available on the market.
To make the right choice, the company must ask itself three fundamental questions. First, you should ask yourself whether this is an essential process and identify the precise outcome you want to achieve. Next, this involves determining whether the need fits into an existing category or whether it instead requires a tailor-made solution. Finally, it is essential to assess the sensitivity of the data used to define the necessary safeguards.
Open or closed models: a strategic choice
Information security is often the top concern for executives. To answer this, two main technological options exist. On the one hand, open language models learn from the information provided to them, which can then become public. On the other hand, closed models are deployed in a company-specific environment and train only on internal data.
Among closed models, recovery-augmented generation technology, often called RAG, stands out as a solution for working efficiently and at lower cost. This system allows the model to be directly fed with the company’s documents and knowledge base. But to guarantee absolute security and confidentiality, it is essential to carry out this operation within a closed model.
Welcome the AI agent as a new collaborator
Time and energy are devoted to welcoming and training a new employee. The same approach should apply to an AI agent. The more careful the preparation of its integration and the definition of clear operating rules, the more efficient the agent becomes.
Of course, the integration is different from that of a human because the AI agents must always remain under the supervision of collaborators. The best way to get started is to involve the entire team in training the agent, while training employees in this new collaboration. In this way, it becomes clear from day one that all decisions remain in the hands of humans, making technology adoption much easier.
