The hype is understandable. An AI that writes code, summarizes documents and drafts emails sounds ideal. But here is the nuance. Most Large Language Models are one-size-fits-all. They are not brilliant, but they are available. In many cases an LLM is not much better than a weighted dice roll. Useful? Yes. Infallible? Absolutely not.
It is important to understand that Copilot is an umbrella term. GitHub Copilot is a completely different tool than Microsoft 365 Copilot. One helps developers code faster, the other promises productivity within Office apps. Both run on LLMs, but the use cases differ significantly. Still, many organizations treat Copilot as one uniform solution, and that is where it goes wrong.
Here is the reality. There is a lot of potential, but very few proven scenarios. Many companies use Copilot simply because it exists, not because there is a clear business case. The result is disappointment. Copilot is not a magic switch. It is a run of the mill LLM for run of the mill tasks. Anyone expecting it to solve complex processes will end up disappointed.
The current version of Copilot is not the end state. It is the starting point. It is an early step toward AI driven workflows. Organizations that invest now in knowledge, governance and realistic expectations create a foundation for real innovation. The rest will keep rolling the dice.
Let us explore the right use cases and create a roadmap that works.