Why is 'AI as a collaborator' the need of the hour?

Our workdays are packed; switching between tools, juggling tasks, and trying to keep pace with shifting priorities. In such an environment, relying solely on traditional tools can hinder our progress.

That’s where AI as a collaborator becomes essential. Instead of adding more layers, it fits into the flow to speed up the flow & bring the focus back on thinking, creating, and deciding.

The real value shows up when responses are accurate enough that we don’t need to double-check; it saves time and mental effort.

The goal is simple: help us work smarter and faster, with less friction.

Let’s dive into how this kind of teamwork plays out.

Examples

Granola helps with meeting notes in a way that feels natural. It fits into the workflow and builds on what users add, not just basic transcription. Users stay focused during the conversation, while Granola handles structure and formatting. The result is useful, high-quality notes without the usual post-meeting cleanup.

A small message like “enhancing notes…” shows when it’s working. Smart templates based on meeting type help give the notes a clear starting point.

Dovetail brings AI as a collaborator in making research faster and more manageable. It automatically highlights key points from user notes, saving time and cutting through the clutter to show what matters most.

Users stay in control; they can create a new highlight and also can can accept, edit, or remove suggestion. This makes the final output still feel like their own work.

Caption is another great example of smart collaboration. It's a smart video editor. Once users upload their footage, it takes care of syncing, styling, and editing, making polished videos with minimum effort.

All edits appear directly in the timeline, so users always know what changed. If the tone feels off, they can easily switch styles using built-in presets.

This lets users focus on their creative message while AI manages the technical details.

We still have a lot to discover about how AI can truly become a collaborator. Right now, it mostly waits for instructions; users tell it when to work.

One who starts by asking what needs to be done, learns quickly, and then grows into someone who can take initiative. Over time, this colleague began suggesting better, faster ways to do things. And when users say yes, it just gets done smoothly, while keeping them in the loop.

That’s the future we’re excited about!