The best AI becomes invisible infrastructure, according to Grammarly’s CEO

Grammarly CEO Shishir Mehrotra argues that artificial intelligence becomes invisible infrastructure once it works effectively, with AI agents already embedded throughout digital systems without being recognized as such. This perspective reframes the AI conversation from futuristic speculation to present-day reality, suggesting that successful AI integration happens when technology seamlessly blends into existing workflows rather than announcing itself as revolutionary innovation.

What you should know: AI agents are already operating across countless systems, but we’ve stopped calling them AI once they become reliable infrastructure.

• Traffic systems that adjust timing based on car detection, Grammarly’s real-time writing assistance, and spam filters all function as agents with specific knowledge, capabilities, and assignments.
• At YouTube, Mehrotra discovered hundreds of AI-powered systems handling content moderation, thumbnail generation, and recommendations—none labeled as “agents” despite meeting the criteria.
• The shift mirrors how transformative technologies like electricity or Wi-Fi fade into the background once they become dependable.

How agents actually work: Effective agents operate on three core principles: knowing something, being able to do something autonomously, and having a specific assigned task.

• Grammarly exemplifies this framework by knowing grammar rules, analyzing writing across applications in real-time, and executing the specific assignment of marking errors in red and improvements in blue.
• Virtual meeting assistants, customer support bots, and recommendation engines all qualify as agents under this definition, despite not resembling science fiction portrayals.
• Most agents currently operate within isolated applications, but the future lies in agents that can move across workflows and tools.

The design challenge: Progress comes from better assignments and context rather than more intelligent models.

• “Great outcomes don’t stem from intelligence alone. They come from great direction,” Mehrotra explains, emphasizing that specificity trumps generality in practical AI applications.
• Future breakthroughs will emerge from agents with targeted jobs and better context—like a language learning agent that could suggest email edits, translate web content, or provide real-time conversation coaching.
• Success requires defining what “done well” looks like before tasks begin, similar to managing human employees.

What leaders should do: Business leaders need to act intentionally rather than passively adopt AI tools.

• Invest in purposeful design by assigning clear roles to agents that solve real workflow problems rather than just adopting AI for its own sake.
• Prioritize context and quality of input to ensure agents access the right data, goals, and signals for intelligent action.
• Champion interoperability to break down silos so agents can move across workflows instead of operating in isolated applications.

The bigger picture: The most transformative businesses won’t showcase flashy AI models but will thoughtfully integrate AI into existing work processes.

• “We won’t say, ‘AI helped me do that.’ We’ll say, ‘That’s how I work,'” Mehrotra predicts, describing a future where AI assistance becomes as natural as using any other tool.
• Current AI tools like language models and transcription assistants will soon feel as ordinary as Wi-Fi or electricity.
• The ultimate measure of AI success is invisibility—when technology works so seamlessly that users forget it was ever called artificial.