Introduction
In a world where companies are increasingly adopting artificial intelligence (AI), the use of so‑called agentic AI is taking on a whole new meaning. Agentic AI – autonomous, purpose‑driven software agents combined with copilot capabilities and human ambition – opens the door to truly AI‑first business models, according to Microsoft. This article explores what agentic AI means, how it is already having an impact and what opportunities it offers for businesses.
What is agentic AI?
Agentic AI describes intelligent systems that not only respond to inputs but actively pursue goals and act autonomously in business processes. According to Microsoft, three components are key:
- Agents: autonomous software units that execute tasks with a defined objective.
- Copilot: interactive AI assistants that support people and facilitate processes.
- Human ambition: combining technology with ambitious business goals makes the difference.
This combination allows companies not only to use AI but to think ahead and redesign business models.
Concrete use cases: examples of successful implementation
Microsoft cites several customer projects that already show impressively how agentic AI is being used:
- Atomicwork used the Azure AI Foundry to deploy the agent “Atom” in the digital workplace. The result was increased service quality and significant cost savings.
- BDO Colombia built “BeTic 2.0” using Copilot Studio and Power Platform – an agent solution for payroll and finance that dramatically reduced workload.
- Dow automated the analysis of over 100 000 freight invoices per year with an agent and a dialog agent (“Freight Agent”), providing rapid insights – analyses that previously took weeks now take minutes.
- Eneco, an energy provider with more than 1.5 million customers, implemented a multilingual chat agent that processes 24 000 chats per month – 140 % more than before – and reduces escalations.
- Additional examples include The Estée Lauder Companies Inc. with “ConsumerIQ,” Fujitsu with a sales‑automation agent, Grupo Bimbo with 650 agents and KPMG in ESG/compliance.
These cases show: agentic AI is not science fiction – it is being used today and is already contributing to productivity, cost reductions and better customer experiences.
Why act now?
There are several reasons why companies should not postpone the use of agentic AI:
- Scale and speed: Agents can automate repetitive tasks so that employees can focus on more strategic work.
- Differentiation: Those who not only use AI but shape it with agents stand out from the competition.
- Economic pressure: In times of rising costs and complex processes, autonomous agents help achieve efficiency and customer benefits.
- Democratisation of AI: Platforms such as Copilot Studio enable citizen developers (not just IT professionals) to create agents – widening adoption.
Tips for implementation in your company
If you plan to introduce agentic AI in your organisation, you should follow these steps:
- Define your goal: Which business or process objectives do you want to achieve with agents? (e.g. service efficiency, data analysis, customer experience)
- Ensure a technological foundation: A robust AI platform, scalable data architecture and appropriate tools such as Copilot Studio are prerequisites.
- Start with a pilot: Begin with a clearly defined use case – e.g. invoice checking or chatbot automation.
- Design human‑machine collaboration: Agents do not replace all employees. Rather, they complement human work and create freedom for higher‑value tasks.
- Measure and scale: Define metrics (e.g. processing time, escalation rate, cost savings) and scale successful agent projects across the company.
Conclusion
Agentic AI marks a milestone in the evolution toward AI‑first organisations. By combining autonomous agents with interactive copilots and ambitious business strategies, new opportunities open up to fundamentally transform processes, increase efficiency and build competitive advantage. The examples mentioned show that this is already a reality. If your company wants to harness the potential of agents, now is the right time to start. Your next question might be: “Which process is the right one – and how do we start?”
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