Agentic AI:
The Rise of Digital Colleagues

Jerrold Stolk

17 Jul, 2025

A payment comes in, but without an invoice number. Someone has to figure out which invoice it belongs to. This may sound like a small task, but it takes a lot of time. Imagine if such a puzzle could be solved automatically. An AI agent scans the payment, recognizes the customer, finds the correct invoice, and updates the accounting records immediately. No more manual searching. No noise, no errors.

These kinds of applications mark a new phase in artificial intelligence. While generative AI mainly generates answers to questions, AI agents independently perform actions. They don't just respond; they act. They make decisions, switch between systems, and perform tasks as if they are thinking along with the organization.

What makes an AI agent different?

Behind the scenes, such an agent works based on a language model supplemented with tools, memory, and a clear goal. This transforms AI from a passive assistant into an active force. A digital colleague who reads emails, handles inquiries, processes data, and even makes decisions based on current information. And all of this quickly, accurately, and without breaks.

However, the rise of AI agents is not about replacement, but about shifting. Much work consists of repetitive actions. These are the tasks that agents can take over, giving people space for more complex questions, personal attention, and creative thinking. Not everyone is immediately enthusiastic about this kind of technology. Understandable. But practice shows: when employees understand the benefits, acceptance grows quickly.

Step-by-step implementation

The implementation usually proceeds step by step. Not with a big bang, but with a targeted application in a recognizable process. One clear goal, one smart agent, one visible improvement. What works, expands. This way, agentic AI grows with the organization, not over it.

There is a clear condition: the agent must know what is going on. And that means: data that is accurate. Not scattered across departments, but centralized, complete, and understandable – even for machines. If an agent has to process an order, it must be able to see what has been ordered, what the stock status is, and whether the payment has been received. Only when all this information comes together can it really do something. This requires a solid data platform. A digital infrastructure where data is logically connected and immediately available.

Agentic AI is therefore not about the future of AI, but about the future of work. Those who organize it well will notice the difference. Not suddenly, but fundamentally. Less switching, less searching, more space to really add value. It may still seem like a step forward now. In a few years, it will feel natural.

Examples

These Agents Are Ready to Use Today

What if you never had to handle payment inquiries manually again?

Every day: vendor inquiries from suppliers. Your finance team checks if payment has been made, links it to the correct invoice, and emails back. Time-consuming and error-prone – and above all: no longer necessary.

Now there is: the 'PayFlow Agent'. It does this work automatically. As soon as a supplier emails with a question like "When will my invoice be paid?", the agent scans the content, looks up the correct information in Dynamics 365 Finance, and formulates an automatic, correct response. Within seconds. The PayFlow Agent is built with Copilot Studio and Model Context Protocol (MCP), fully integrated with Dynamics 365.

PayFlow Agent

What if incoming orders were immediately converted into orders?

In many organizations, a large part of the orders still comes in via email. Sometimes neatly as a PDF, sometimes as a scan or even as a photo of a handwritten note. Processing them takes time, leads to errors, and keeps employees away from more important work.

The 'Mail-to-order Agent' changes that. It automatically reads incoming emails, recognizes customer information, item codes, quantities, and delivery dates, and immediately converts that information into a correct order in Dynamics 365 Finance & Operations.

The agent recognizes patterns, fills in missing data, or asks for targeted validation if something is unclear. No copy-paste work, no back-and-forth emails with sales.

Mail-to-Order Agent

Are you already working with an AI agent – without knowing it?

In many organizations, a digital colleague is already lurking in the background. Those who work with Microsoft Dynamics 365, SharePoint, or the Power Platform often already have access to AI functionality that automates processes.

Take the Sales Qualification Agent. This smart application scans customer data, recognizes buying signals, and makes suggestions for the next steps. What used to depend on intuition is now supported by pattern recognition based on historical data.

Sales Qualification Agent

Are you already working with an AI agent – without knowing it?

Take the Case Management Agent, which answers questions via email or chat, retrieves relevant information, and performs actions if necessary. Not as a standard chatbot, but as part of a broader workflow.

Case Management Agent

Three people reviewing a financial chart

Are you already working with an AI agent – without knowing it?

And in the financial sector, there is the Account Reconciliation Agent. This agent helps with reconciling transactions – a task that can normally take hours. By automatically matching sub-ledgers and the general ledger, the system speeds up financial closing and reduces the error margin.

Account Reconciliation Agent

Want to learn more?

Ask our AI expert

I believe AI only makes an impact when it’s actually used. My passion is bridging the gap between what’s technologically possible and what organizations truly apply.

Data is the foundation. With a strong background in data engineering and hands-on experience with tools like Microsoft Fabric, Azure Data Factory, Databricks, Copilot Studio, and AI Foundry, I build scalable, data-driven AI solutions that deliver real value.

Curious how AI and data can accelerate your organization? Let’s connect!

Jerrold Stolk
AI Lead

What makes an AI agent different?

Step-by-step implementation

These Agents Are Ready to Use Today

What if you never had to handle payment inquiries manually again?

What if incoming orders were immediately converted into orders?

Are you already working with an AI agent – without knowing it?

Are you already working with an AI agent – without knowing it?

Are you already working with an AI agent – without knowing it?

Ask our AI expert

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