AI agents are no longer a promise for the future. They are now used in production and in companies of all sizes and in all sectors. The question is no longer whether the technology is mature enough. The question is: which use cases suit us and where do we start?
According to a Gartner forecast, around 40 percent of all enterprise applications will contain task-specific AI agents by the end of 2026 - a significant leap compared to the previous year.
If you look for specific examples, you will find them across all industries and business areas.
AI agents analyse incoming tickets, assign priorities, initiate standardized responses and escalate if necessary. Simple troubleshooting can be fully automated through integration with monitoring tools.
What this means in practice: an agent receives a support request, classifies it according to urgency and topic, forwards it to the appropriate team or resolves it directly if it is a known error case. Human intervention is reserved for complex or critical cases.
AI agents in customer support automatically evaluate incoming inquiries according to priority, content and tone and transfer them directly to the appropriate team. Long support correspondence is compressed, agents receive real-time tips for the next steps in the middle of customer contact.
The result: shorter response times, relieved teams and a customer experience that is consistent around the clock, regardless of shift work or vacation season.
Procurement processes are a classic field of application for AI agents. An agent checks incoming purchase requisitions, compares them with supplier data and budget pots, creates an order proposal and forwards it for approval. If approval is granted, it triggers the order directly in the ERP without any manual intermediate step.
Procurement, invoice processing, IT support, contract review and customer communication are the processes in which AI agents add particular value. They encompass several steps directly, access various systems and thus minimize the amount of manual coordination by an employee.
Incoming invoice processing, fraud and risk monitoring as well as compliance monitoring can be automated on the basis of structured data.
A concrete example from practice: An audit agent receives the order to collect all evidence of the implementation of a specific guideline from the past year. He combs through document management systems, e-mail archives and contract management and creates complete, auditable documentation including exact references. This also reduces the preparation time for the audit from three weeks to two days.
In manufacturing, AI agents monitor production lines in real time, detect anomalies and autonomously optimize processes. Maintenance agents in Industry 4.0 predict potential failures and order spare parts in good time - before the plant comes to a standstill.
This not only saves repair costs, but also protects against the significantly more expensive unplanned downtime.
Logistics agents forecast fluctuations in demand, optimize stock levels and manage supply chains fluidly. An AI agent recognizes delays and automatically initiates route detour without waiting for human intervention.
At a time when supply chain disruptions are the norm, this is no longer a convenience, but a competitive advantage.
AI agents support HR in the pre-qualification of applications, answer standardized employee inquiries about benefits and guidelines, coordinate onboarding processes and automatically remind employees of outstanding tasks. Nine out of ten managers report that AI agents change the way their teams work. Employees spend more time on strategic activities and less on routine work.
All successful deployment scenarios share three characteristics: They are process-bound, data-driven and measurable. AI agents are particularly productive in highly structured, recurring tasks with clear performance measurement.
Those who start with such a use case achieve quick results and create the basis for further scaling.
At prodot, we help companies do just that: from consulting and designing individual AI agents to integrating them into SAP, ERP, CRM and Microsoft 365 and orchestrating complex multi-agent workflows - with clearly defined responsibilities and the human-in-the-loop principle.
Find out more about AI agents for companies
Would you like to know which processes in your company are suitable for the introduction of AI agents? Talk to us - we'll take a look together.