Since the end of 2022, the debate around artificial intelligence has been dominated by the prospect of an act, a general intelligence capable of reasoning independently. But on a more business horizon, it is not the act that redraws the uses but the AI agents. Specialized systems, capable of orchestrating actions in specific environments, and which are performing more and more in edgedirectly on a local terminal or cloud.
The real switch
Generative models showed their value as an interface, but their impact remained limited as long as they could only produce text or code. The agents cross this limit when they trigger concrete actions in a CRM, in a production chain or in a customer service. Where the AG remains hypothetical, the agent already stands out as Automation actor.
Dirty ops: invisible automation
In the sales teams, IA agents connect to tools like Salesforce or HubSpot. They automatically enrich the prospect sheets, qualify the leads according to pre -established criteria and program monitoring sequences. The interest is not to replace the salesperson, but to remove the repetitive load. The gain is measured in conversion rate and treatment speedtwo metrics immediately visible.
Customer support: from Ticket to resolution
In the support, the AI agents exceed the simple chatbot and will categorize a ticket, look for good procedure in the documentary database, then perform simple actions such as reset a password, trigger a refund, or plan a technical intervention. The issue is not limited to cost reduction, and is more in the Average resolution timea strategic KPI of customer loyalty teams.
Production and industry: AI closest to machines
In industry, agents will find their place at the heart of production lines. Executed in Edge to reduce latency, they can monitor sensors, anticipate anomalies and launch parameter adjustments without delay the intervention of an operator. Here, the value can be read in the Reduction of machine stops And in energy optimization, critical issues in a context of tense costs.
Why the Edge is decisive
The ability to execute an agent locally changes the situation significantly. Of course a compact model, turning on mobile or on an internal server, limits the dependence on the hyperscaler cloud and reduces latency and data transfer costs but for CTOs, the equation is above all less external dependence, more operational control, and the question of security is pre -aged, As we can see in the rest of our article tomorrow devoted to the integration of agents.
The upcoming battle
You will have understood that the next 24 months will not be those of the act but those of Specialized agentsable to integrate into existing workflows and deliver measurable value. Companies that will deploy these agents on a scale will take a step ahead.
European solutions to follow
- Dust (France) : Develop secure conversational agents for companies, capable of connecting to their internal tools while respecting confidentiality constraints.
- Giskard (France) : Provides test and explanability tools to make the models used by agents reliable, a key asset to avoid inconsistencies and biases.
- Cosmian And Zama (France) : work on homomorphic encryption and applied cryptography, essential to deploy agents on sensitive data without loss of security.
- Enzai (United Kingdom) And Aspi (Germany) : support companies in the regulatory compliance of AI systems, a compulsory passage to deploy large -scale agents in Europe.
