Before you read another word about artificial intelligence, answer this honestly. When someone brings up AI at work, do you feel a quiet sense of panic? Like everyone else has moved ahead and you have somehow missed the moment to catch up? If the answer is yes, you are in very good company. But that feeling usually comes from a simple misunderstanding. The belief that being “good at AI” requires technical skills you do not have. Coding, data science, something complex and sli

I recently delivered a M365 Copilot course for a business who really needed in person meeting notes and transcription. They were looking at Otter AI and Fireflies as possible tools to help them with this but this would have meant an increased cost of around £10 per user per month. They were also very strict in terms of what they could use for data security and GDPR reasons. However Microsoft has quietly introduced a way to record and transcribe in-person meetings using M365 C

As an AI Trainer I often get to see how the same prompt and information can generate different results. Often students will comment: “I used the same prompt, with the same data but the answers are different.” Sometimes the response is broadly the same but phrased differently. Sometimes the emphasis changes. And occasionally if doing data analysis, the data itself is wrong. This is despite very clear and detailed prompts and the exact same data. Over time, this leads to a bigg

Artificial Intelligence is advancing at an incredible rate, but does it truly understand what it produces? The short answer is no. While AI can generate coherent, often insightful responses, it does so by predicting patterns, not by grasping meaning in the way humans do. Understanding, in the human sense, requires real-world experience, emotions, and consequences—things AI simply does not have. AI is Pattern Recognition, Not Understanding At its core, AI operates by identifyi