AI is reshaping the way organizations work, but the focus is shifting from adoption to impact. Meetings are becoming a key environment for that shift, as AI helps make them more efficient, productive, and valuable by capturing decisions, surfacing actions, and reducing follow-up work. But AI is only as effective as the collaboration technology behind it. When meeting-room systems capture people and conversations clearly, they become a critical enabler of AI delivering real business value.
With Microsoft research showing that meeting frequency has tripled in the past four years, and tools like Microsoft Copilot and Facilitator powering productivity in Microsoft Teams, meetings have become one of the most important environments where AI supports day-to-day work. Summaries, action items, follow-up tasks, and shared knowledge increasingly depend on what those systems can accurately capture in the moment.
That matters because meeting content is no longer disposable. As Josh Blalock Collaboration Ecosystem and Engagement Director at Shure, explains:
“As we talk in a meeting, we are creating data for the AI agents in the background to use for creating things in the back end, like documents, tasks, and all sorts of great things.”
However, the quality of those outputs still depends on the quality of what the room captures. IDC research shows that organizations are rethinking collaboration as part of a broader AI-enabled future of work, where the quality of connected tools, content, and context shapes business outcomes. In IDC’s research sponsored by Shure, 71%* of organizations say collaboration improves the ROI of technology investments, reinforcing why meeting-room quality matters more in the AI era.
For IT decision-makers, this turns collaboration technology from a meeting-room consideration into a strategic layer of AI readiness. If the collaboration experience is inconsistent, the value of the platform above it becomes harder to realize, harder to trust, and harder to scale.
Why Meeting Quality Now Shapes AI Value
Collaboration platforms promise faster summaries, automated task capture, and less administrative overhead. Yet many organizations still find users correcting transcripts, clarifying action items, and losing confidence in AI-generated outputs. The instinct is to question the platform. In many cases, the problem starts earlier, with the quality of audio and video being captured in the room.
As Blalock puts it:
“The machine wants to know exactly what was said, and it’s using that exact transcription to do the work that it needs to do.”
If a meeting takes place in a room with poor-quality AV, the problem starts with what the system is able to capture. That captured audio and video becomes the foundation for the transcript, and the transcript in turn shapes summaries, speaker attribution, action items, and every downstream workflow that depends on the system understanding what happened in the meeting. AI treats spoken input as instruction, not interpretation, so when the input is flawed, the downstream output reflects that same distortion.
As AI becomes more deeply embedded into work, that reliability gap becomes more costly. Poor capture quality can create friction for users, increase manual correction, and weaken trust in the very tools organizations expect to improve productivity.
As more workflows become automated, the consequences also grow. A flawed transcript is no longer just an inconvenience. It can lead to the wrong follow-up, the wrong task, or the wrong interpretation being carried forward.
This is why collaboration and conferencing technology now plays a more strategic role in enterprise communications. It is not simply there to support the meeting in the moment. It helps determine whether AI-enabled collaboration experiences are accurate, equitable, and usable enough to drive adoption across the organization.
What the Next Generation of Collaboration Solutions Must Deliver
Meeting rooms now need more than basic connectivity. They need collaboration solutions that deliver consistent capture quality, support AI-enabled workflows, and scale across room types without adding unnecessary deployment and management complexity. That is the new standard the next generation of collaboration solutions must meet.
In some spaces, that means advanced ceiling array coverage with solutions such as the Shure MXA925, helping ensure every participant is heard clearly, not just those closest to the camera or table microphone. In others, it means all-in-one systems such as Shure IntelliMix Bar Pro, which simplify setup while delivering the audio and video performance needed for more reliable AI-generated outputs.
For enterprise IT teams, the requirement goes beyond room performance alone. The right technology portfolio should support standardization across small, medium, and large spaces, integrate cleanly with leading collaboration platforms including Microsoft Teams and Zoom, and make it easier to deploy and manage collaboration technology at scale. Solutions such as IntelliMix Foundation System, IntelliMix Room Kits, and Microflex Wireless neXt 4 and 8 help extend that approach across different room types while supporting quality, consistency, and operational simplicity.
Signal processing also matters. Features such as echo cancellation, noise reduction, and automated gain control improve speech clarity, which can lead to more accurate transcripts, better summaries, and more dependable AI-generated outputs. This is a critical but often overlooked part of the value chain, because better in-room processing improves the quality of the data that downstream systems depend on.
IDC’s recent research sponsored by Shure, Collaboration: The ROI Amplifier, points to a broader shift here. Organizations are no longer evaluating collaboration tools only on meeting convenience. They are looking more closely at how connected collaboration environments support productivity, decision-making, and AI-enabled work. In that context, better room experiences become a business outcome issue, not just a technical specification.
Poor collaboration experiences do more than create bad notes. They widen the gap between investment and realized value. As Blalock explains:
“Selecting the right AV is less about making an extra premium investment and more about shepherding and taking care of the data you are creating.”
Getting this right is a technology, process, and adoption challenge. The right solutions capture cleaner data, support more equitable collaboration, and make AI outputs more dependable. When organizations combine that with easier deployment and scalable management, collaboration technology becomes a stronger foundation for enterprise-wide AI success.
Building the Foundation for AI-Ready Collaboration
The organizations that will get the most from AI will not simply be those that deploy more tools. They will be the ones that build the right collaboration foundation underneath them. As hybrid work continues and AI becomes more deeply embedded in meetings, the need for accurate capture, consistent room experiences, and scalable collaboration infrastructure will only grow. Get that foundation right, and everything above it performs better. Leave it as an afterthought, and even the most advanced AI is working against itself.
That is why the next generation of collaboration and conferencing solutions must do more than connect people in the room. They must support reliable AI-enabled workflows, deliver consistent experiences across spaces, and help IT teams scale with confidence.
Discover how Shure’s collaboration solutions help organizations create AI-ready meeting spaces with more reliable capture, better user experiences, and simpler deployment across room types.
IDC InfoBrief, sponsored by Shure, Collaboration: The ROI Amplifier: Delivering Immediate and Lasting ROI in a Connected Work, doc #EUR253683525, November 2025
