How Microsoft Teams plans to use AI for its noise suppression feature to filter out some non-stationary noises like dog barks while keeping others like laughter
Last month, Microsoft announced that Teams, its competitor to Slack, Facebook's Workplace, and Google's Hangouts Chat, had passed 44 million daily active users.
Context & Ripple Effects
This piece unpacks the real-time noise suppression Microsoft unveiled when Teams blew past 44 million daily active users — moving from the announcement to how the model actually classifies non-stationary sounds, keeping human cues like laughter while cutting dog barks and other interruptions.
It lands mid-race: two months later Google published a deep dive on Meet's own AI noise cancellation, and Microsoft kept compounding the audio stack with an echo- and interruption-reduction update in 2022 and voice isolation and generative backgrounds in 2023.
First-order effects
- Remote workers on Teams calls get machine-filtered audio by default — barking dogs and similar background bursts suppressed while conversational sounds like laughter survive, changing what a 'clean' home-office call means.
Second-order effects
- Google Meet answered with its own AI-powered noise cancellation rollout, turning call-audio cleanup from a differentiator into a parity feature both platforms must ship and maintain.
Third-order effects
- If the pattern holds, real-time audio and video correction becomes embedded infrastructure in every major meeting product — the on-ramp to the paid AI tiers Microsoft later built with Teams Premium features like recaps and live translation.
The trend: Collaboration platforms are baking machine learning directly into real-time call infrastructure, starting with noise suppression and expanding into paid AI meeting layers.