Categories
Copilot

Microsoft Copilot vs ChatGPT: Which Is Better?

If you have been exploring AI tools at work, you have almost certainly come across both Microsoft Copilot and ChatGPT. They look similar on the surface: you type a prompt, the AI generates a response, and both are powered by technology from OpenAI. But underneath, they are designed for very different purposes, and choosing the wrong one for a task will leave you frustrated.

Categories
Copilot

Work IQ Isn’t an Intelligence Upgrade. It’s a Control Plane.

When Work IQ was introduced, most people focused on one idea: Copilot was becoming smarter because it could understand more about how an organisation works. But if you look past the keynote and read the architecture details, the bigger story is not just intelligence. It is control. Microsoft designed Work IQ to manage who can use that intelligence, what they are allowed to do with it, and how every action is recorded and checked. In simple terms, Work IQ makes governance something organisations need to actively manage, not something that stays hidden in the background.

Categories
Copilot

How to Build Custom Copilot Agents?

A Practical Walkthrough Using Microsoft Copilot Studio

1. Introduction

Custom Copilot agents are task-specific AI assistants you build for your organization’s unique needs. Unlike the general Microsoft 365 Copilot chat, these agents are tailored to specific business workflows and grounded in your own data.

Categories
Copilot

5 Copilot Prompts Every Manager Should Know


Copy-paste prompts that deliver results from day one

Most managers who try Microsoft 365 Copilot for the first time come away with the same reaction: ‘It seemed useful, but I wasn’t sure what to ask it.’ That is not a Copilot problem, it is a prompting problem. And it is entirely fixable.

Categories
Copilot

Microsoft Copilot in Excel for Finance Teams

Six high-value workflows for analysts and finance professionals

Finance professionals spend a disproportionate amount of their working day doing things that are important but not particularly analytical: cleaning and formatting data, writing formulas they half-remember, building the same charts for the same reports every month, and translating numbers into written commentary for stakeholders.