How does AI for meetings improve collaboration?
Reaping the collaboration benefits of AI may take some time. Learn how AI for meetings can improve the collaboration experience through automation and predictive insight.
Collaboration vendors continually try to improve meeting experiences with new technology. AI is the latest wave of new technology, and while applications are still formative, they could potentially benefit the meeting experience. Today, AI benefits for collaboration are limited, but AI is iterative and will improve as data sets grow.
The benefits of AI for meetings will take time to manifest, so the bar for a quick ROI should be set low. IT decision-makers should consider two distinct types of AI benefits for collaboration meetings. First, AI for meetings provides efficiency through automation. Second, AI can improve the quality of a meeting's outcomes.
Automation improves employee efficiency
Vendors are interested in improving meetings by providing AI-driven automation, which can boost employee efficiency. Manual tasks create a wide range of pain points before, during and after meetings. AI is now automating many of these meeting-related tasks, such as invites to meetings and readying a room for a video call.
One way AI for meetings automates tasks is with speech applications that interface with PCs or other endpoints, such as Amazon Echo. As AI-driven speech applications in the workplace become more common, voice commands can streamline processes. Participants can use voice commands to start a meeting, invite a new participant, start the presentation, lower the lights and send calendar invites for the next meeting. Alone, each task may seem basic, but the cumulative impact across many tasks can improve the overall experience.
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Ultimate guide on enterprise unified communications strategy
Improved quality of outcomes
AI-enhanced analytics can quickly process large amounts of information that can be used during the meeting. For example, AI-enhanced analytics can collect data from a wide range of sources -- both inside and outside the organization -- and use keywords to extract relevant content for a meeting. Applying analytics to that content can identify patterns and relationships that would otherwise require time and effort to produce manually. The net result is better quality inputs that help produce better decisions and outcomes from meetings.
For recurring meetings, AI provides predictive and proactive insights to make collaboration more productive. AI for meetings can transcribe conversations -- often more accurately than workers taking notes. The transcriptions keep precise tabs on action items, such as how well team members are following up on items from meeting to meeting. The impact over one or two meetings may be nominal, but as AI applications learn more about team members and how they interact, this workflow should lead to better collaboration outcomes.
