Grammarly and the future of workplace AI: Removing friction, not replacing people

Enterprise AI discussions tend to get caught up in two polar extremes: one side is convinced it’s going to make all the difference overnight, and the other is wringing its hands over all the jobs that will supposedly get lost to automation. Neither stance does a whole lot of good to help real business leaders actually make AI a useful, safe, and trackable part of their organization.

But in a recent conversation with Superhuman’s Lana Malikova and Kseniia Shalyhina, led by Twain Taylor, we saw a much more productive way to think about things. This time, it was about how teams are actually using AI every single day to work together and the responsible way to adopt it by keeping an eye on security, workflow, and whether it’s actually paying off.

In this article, we look at how business leaders can get past the AI hype, make it easier for modern cloud and serverless teams to communicate, and use AI in the workplace in a safe and measurable way.

Hype versus reality is often an adoption problem

Before policy is decided, employees start using AI to write, summarize, or organize work. That creates a predictable gap:

• AI is already in use, sometimes in unsanctioned ways.
• Security and governance teams are still trying to define guardrails.
• Leaders struggle to measure value because usage is fragmented.

For business leaders, the real question is whether they will lead adoption in a responsible way. When companies say AI is optional, they often get the worst of both worlds: AI is used without limits and doesn’t always help.

Working with AI in the workplace

When it comes to using AI in knowledge work, there’s one guiding principle that should always be at the forefront: humans retain the final say in decision-making.

It’s crucial not only for quality control but also to mitigate brand risk, compliance issues, and keep organizations accountable for their actions. People still have to make the call on what’s true, what’s right for their audience, and what aligns with their organisation’s goals.

This comes down to the difference between AI working as an assistant versus trying to substitute for human input. Companies have more success with the first approach because it mirrors how accountability actually works within an organization.

Why Grammarly is a responsible AI in action

Grammarly’s story isn’t about some sudden pivot into generative AI. Instead, it’s built on years of helping with language and writing, and only gradually improving to include more AI-driven tools as people’s expectations evolved. And that history is important as it helps shape how Grammarly operates in the workflow.

Grammarly is way more than just an autocorrect tool. It’s an AI-powered communication assistant that helps people get their point across more clearly and consistently, without forcing them to rewrite or give up control.

For enterprise leaders, this makes adoption a whole lot easier. Employees don’t need to change their workflow, and they don’t have to give up control either. The tool helps take the friction out of communication while keeping accountability where it belongs.

Bottom-up adoption

The only time bottom-up adoption becomes a problem is when the organization takes a back seat and lets things unfold without any direction. But if leaders are on top of it, it can actually be an opportunity.

A practical approach includes:

• Choosing tools that are actually used in the workplace
• Being super clear about when AI should be used (and how)
• Training teams on how to use AI without losing their judgment
• Giving IT and security teams a say in where AI runs and what it can access

Moving from a tool to a platform approach

Another important theme in the discussion was that communication does not happen in isolation. Writing is connected to execution: tasks, decisions, approvals, and workflows.

That is part of why Grammarly has expanded into a broader ecosystem that includes Coda and Superhuman Mail. The positioning is straightforward:

• Grammarly supports communication where people write.
• Coda supports structured collaboration and workflow execution.
• Superhuman Mail supports teams that spend a large part of the day in email, with features like thread summaries and faster drafting.

The platform direction discussed was a connected experience that can travel across tools, using connectors to reduce information silos and context switching. For enterprise leaders, the strategic appeal is not novelty. It is reduced friction across the surfaces that employees already live in.

Security and governance are what separate pilots from enterprise scale

Many AI efforts stall because governance is treated as an afterthought. In enterprise environments, security questions come first, especially for teams like HR, legal, and operations.

The discussion emphasized several themes that leaders should expect from any workplace AI vendor:

1. Controlled activation in sensitive contexts: Tools should avoid operating in fields where sensitive personal data is entered.
2. Clear data handling and storage behavior: Enterprises need to understand what is processed, what is retained, and under what conditions.
3. No training on enterprise customer data in managed configurations: This is a common enterprise expectation and should be contractually clear.

A practical starting point for responsible adoption

Usually, the places where teams have the most trouble every day are where a good AI strategy starts. This includes writing, getting approvals, handing things off, and always making sure that communication is clear between functions.

Grammarly gives business leaders a realistic example of AI that cuts down on repetitive communication tasks, promotes consistency, and leaves human judgment in charge. Implementing in places where people already write, tracking real adoption, and expanding with risk-appropriate governance are the fastest ways to get value.

To get the full context and hear how these ideas connect across collaboration workflows, readers should watch this interview.