Copilot & agent readiness: bring AI safely into your Microsoft 365 processes

ICT 365 introduces AI where your processes already run: in Microsoft 365, SharePoint and the Power Platform. We make data and permissions Copilot-ready, prioritise use cases by benefit, and build agents for clearly scoped tasks – with checkpoints instead of blind flight. And because we develop with AI ourselves every day, we advise from practice, not from the brochure.

Illustration: AI features with a sparkle symbol in application windows, protected by a shield and connected to data sources

When AI is on the agenda but nobody knows where to start

AI projects rarely fail on technology – they fail on foundations and scope. Typical situations:

Copilot is licensed or in trial – but the results disappoint because structure and data quality are missing.
Before the rollout stands the fear of oversharing: Copilot finds everything users can access – including the wrong things.
There are plenty of AI ideas, but no prioritisation by benefit and feasibility.
First agent experiments run without rules, owners or checkpoints.

What our AI consulting covers

From the first reality check to daily operation:

Copilot readiness: data quality, permissions and oversharing analysis
Use-case prioritisation by benefit, feasibility and risk
Introducing Microsoft 365 Copilot: pilot groups, adoption, measurement
Agents with Copilot Studio for clearly scoped tasks – with human checkpoints
AI in business applications and processes: Power Platform, SharePoint, Azure AI
Guard rails for operation: owners, logging, user training

What works today: Copilot, agents and AI in the platform

The state of AI in Microsoft 365 changes quarterly – as of August 2026, much of it has become routine.

Microsoft 365 Copilot has been a built-in part of model-driven apps since April 2026, AI record summaries and form assistance included; Dataverse has offered AI prompt columns since May 2026, and through Copilot Studio agents can be embedded directly into applications. We assess what of this is mature for your processes – generally available, preview or merely announced – and build in what measurably helps. The foundation is always the same: clean data and correct permissions. Without them, every AI tool delivers convincingly formatted wrong answers.

Diagram: path from data sources through permission checks to AI features in applications

Not just using AI – mastering it

Introducing AI takes more than licences: your teams must be able to work with it – the EU AI Act demands as much.

Since February 2025 the EU AI Act obliges companies to ensure sufficient AI literacy among their staff; since August 2026 additional transparency obligations apply. We train users and developers on their own processes instead of slides – and pass on our own way of working: AI-assisted development with Claude Code and Google Gemini, agentic knowledge work with Claude Cowork and Claude Teams. We do not replace legal advice – we make your teams capable.

How we introduce AI in your company

Initial conversation and target picture

Where AI genuinely saves you work – and where it does not. We sort ideas by benefit, feasibility and risk.
Readiness analysis

Data quality, permissions and oversharing risks are assessed – you receive an action plan with an effort estimate.
Pilot with a clear use case

One scoped scenario goes live with a pilot group – with measurable criteria instead of gut feeling.
Rollout and adoption

Extension to further groups, training on your own processes and clear rules for daily use.
Operation and further development

New AI features are assessed continuously and adopted where they are mature and useful.

Frequently asked questions about introducing AI

How much does introducing Copilot and AI cost?

Beyond the Microsoft licences, readiness drives the effort: how much needs doing on data and permissions is what the analysis shows – after it you receive a reliable estimate. Licence prices change regularly; we calculate with current Microsoft prices instead of promising figures.

How long until productive use?

A pilot with a clear use case stands much sooner than a company-wide rollout – how soon depends on the state of your data and permissions. The readiness analysis makes it plannable; pilot groups then work productively while the rest is prepared.

What is the Copilot oversharing problem?

Copilot finds everything a user can access – including content never meant for them whose sharing is simply too broad. That is why permission analysis and clean-up belong before the rollout; it is the single most important step of Copilot readiness.

Do we need our own AI models?

In the vast majority of cases, no: Copilot, Copilot Studio and Azure AI cover the typical enterprise scenarios; custom models only pay off for very specific requirements. We recommend the path that delivers benefit – not the one that sells the most infrastructure.

How do we stay in control of AI agents?

With us, agents get clearly scoped tasks, defined data access and human checkpoints for decisions. Add logging and an owner per agent – governance is part of the build, not an afterthought.

Do we have to train our employees?

Yes – professionally and legally: the EU AI Act has required sufficient AI literacy among staff since February 2025. We train on your own processes instead of slides – from prompt basics to safe agent use; the details sit with our personalised training service.