AI for business: how to implement Copilot, AI agents and governance

Almost every organisation is experimenting with AI today. Management is asking about Copilot and AI agents, and meanwhile employees are already using all kinds of tools on their own. Then the question becomes how to use AI safely, so that it also delivers measurable results.

In this guide, we set out how to give AI a place in your organisation step by step, based on the projects we run with our clients.

Implementing AI means giving AI applications such as Microsoft Copilot or AI agents a permanent place in the daily operations of your organisation. That comes with agreements on which data AI may use, how you secure that data and who is responsible.

Activating a licence is quickly done. The result depends on what surrounds it: a reliable data foundation, a secure infrastructure, processes you can automate and people who know what they can do with AI.

Many organisations recognise the pattern. Two dashboards show two different figures, while management is already asking about AI agents. A few pilots are running, but they rarely make it to production. Who owns which data remains vague, while the AI Act raises the bar. And in the meantime, employees use AI tools on their own, without agreements on what is allowed.

The bottleneck is then usually in the foundation beneath the AI. The five steps below tackle that.

Start with an honest maturity scan of your data environment and your ambition. Where is your data, who owns it, can you trust it and is your infrastructure ready for AI? If your data foundation is already in place, you go straight to the use cases.

Look at your people too. With Xylos Insights, our digital baseline assessment, an AI agent has a short conversation with each employee. You get a DigiScore per employee, a heatmap per team and an overview of the AI applications already in use on the work floor. That overview is also a good source of use cases.

AI is only as reliable as the data beneath it. Bring your data together on a modern data platform, so that reporting and AI draw from the same source. That also ends the discussions about whose figure is right.

Also define who owns which data, with data owners and stewards, and draw up an AI policy: which tools are allowed, which data may go into them and who decides on new applications.

Think about security as well. Microsoft Copilot works with the access rights your employees have today. If a folder with payroll data is too widely accessible, Copilot can summarise that information for colleagues who should not see it. So clean up the permissions first and label sensitive documents.

With the foundation in order, you select the applications that deliver the most. Generative AI such as Copilot helps employees write, search and summarise faster in Microsoft 365. Dashboards give the right people the right insight at the right time. With automation and low-code, for example in Power Platform or Mendix, you turn those insights into faster processes.

With agentic AI, AI goes one step further. An AI agent carries out tasks independently and drives systems based on your data. An engineering SME uses such an agent today: it reads along with project communication and alerts the project manager weeks before a client escalates. A manufacturing SME uses computer vision to pull defective bags off the line before they go into the container.

You choose the model based on the question at hand. That can be Copilot, Azure OpenAI or Claude by Anthropic, always within an architecture that fits your environment.

AI applications only pay off when people use them. Since February 2025, the AI Act also requires organisations to ensure sufficient AI literacy among the employees who work with AI.

The results of Xylos Insights show where the learning needs are, which learning formats your people prefer, who is ready to start and who needs extra support. We link those insights to our offering, and that gives you a personalised learning path. You decide how far you take it, up to a path tailored to each employee. Think of the AI literacy programme, short learning moments in OASE or a game on PlayForward. After the path, you measure again so you can see the progress.

A pilot only becomes valuable when it goes into production. Test every application against your security and the AI Act, and build in human oversight where AI prepares decisions.

Look at the infrastructure too. Your data and models live in the cloud, on-premises or in a combination of both, and that environment must be secure and scalable.

After go-live, AI still needs work. Models and processes change, so plan right away who monitors, manages and adjusts the environment.

• Does the partner look at your data, your infrastructure and your people before any tool is rolled out?

• Can the partner help work out your data foundation and governance, in line with the AI Act?

• Does the partner choose the model based on your question, or does it work with a fixed technology?

• Does the partner take use cases all the way to production, and does it keep managing and securing them?

• How does the partner measure the results, in your processes and among your people?

Xylos is a Belgian family-owned tech company headquartered in Antwerp. Xylos supports organisations at every step of their AI implementation, with six building blocks you combine depending on your situation: data strategy and governance, modern data platforms, dashboarding and insights, AI readiness, AI transformation and agentic AI, and data and AI literacy. Xylos is a Microsoft Solutions Partner for AI Business Solutions, Cloud & AI Platforms, Security and Microsoft Cloud, including the Adoption and Change Management specialisation. Xylos is also an Anthropic partner and ISO 27001 certified.

AI never stands apart from the rest of your environment. Hybrid Cloud provides the infrastructure your data and models run on, and Modern Workplace feeds your data through Microsoft 365. Automation and low-code turn insights into faster processes, Cybersecurity and Managed Services keep everything secure and up to date, and through Learning Services your people get the learning path they need. Xylos brings those layers together.

You see results after every step, so you decide yourself how far you go.

In an exploratory conversation, our experts map your data environment and sketch the first outlines of your path to AI.