Let me start with a deceptively simple question: how can we improve the way humans communicate with each other?
It might sound straightforward, but when you take a closer look, communication is at the heart of almost everything we do at work. Research shows that more than 80% of a typical workweek is spent on communication – whether that’s in chat, email, documentation, or meetings.
So when we step back and think about it, businesses don’t just run on strategy, products, or processes. They run on communication.
At Grammarly, our mission is simple but ambitious: to improve lives by improving communication. For the past 15 years, we’ve built AI-powered tools that help individuals and organizations express themselves more clearly and effectively.
Today, Grammarly is used by more than 40 million individuals and over 50,000 organizations, across half a million web and desktop applications.
So in this article, I’ll share some of the ways we’re advancing AI-powered communication, how we’re using AI to improve writing accuracy and speed, why personalization and context matter so much, and where AI agents are taking us next.
Let’s get started.
Why AI is transforming communication
What does good communication actually look like? To me, it means getting the right information to the right audience to drive the desired outcome. And ideally, it should happen efficiently – we all know how valuable time is.
Writing plays a central role in this process. Whether it’s an email to a client, a technical specification, or a quick Slack update, writing is the backbone of modern communication. But writing isn’t a one-step activity – it’s a process. I like to think of it as three interconnected stages: pre-writing, writing, and post-writing.
Each stage has its own unique challenges and goals. Sometimes writers move linearly through the process, while other times they jump back and forth or skip stages altogether. That complexity is exactly why AI can play such a valuable role.
At Grammarly, we believe AI can help across the entire writing pipeline, from drafting to revising to final delivery. But let me focus on three areas where I see the most exciting progress:
- Improving writing accuracy and speed
- Enhancing personalization and contextualization
- Building the future with AI agents
Improving writing accuracy and speed with AI
The most impactful use case for AI in writing is text revision. Anyone who’s tried to rewrite a sentence, adjust tone, or correct grammar knows how much time this can take.
Traditionally, you’d rely on your own editing skills or a colleague’s review. But with large language models (LLMs), we can automate much of this revision process. We’ve also fine-tuned smaller LLMs on a large collection of high-quality writing tasks. These include grammar correction, text simplification, improving coherence, and even tone adjustments.
