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What is an AI Meeting Manager and How Does it Work

What is an AI Meeting Manager and How Does it Work

An AI Meeting Manager automates scheduling, sends reminders, transcribes discussions, and enhances productivity, reducing manual effort and optimizing resources.

Introduction to AI Meeting Managers

AI Meeting Managers are advanced digital instruments that have been developed to facilitate the process of meeting organization and conduction. They successfully exploit modern technologies such as machine learning, natural language processing, and predictive analytics, significantly relieving the organization of meetings from the administrative burden, enhancing speed of decision-making and, therefore, improving the overall meeting effectiveness.

Principles of Work

Estimating the necessity of scheduling a meeting, an AI Meeting Manager starts by scanning digital calendars for as many candidates as there are in the organization, searching for open slots available for everyone. The system also considers each given candidate’s preference: a slot, that suits the schedule of as many participants as possible, is selected first of all. For example, if a project is known to work most effectively during morning hours, an AI system will select a morning slot for the future meeting. Every aspect of scheduling, from suggesting to confirming, is performed by the mentioned AI Meeting Managers, reducing the time spent on scheduling by 50% in some cases .

The main steps of the AI Meeting Managers’ operation can be listed as follows:

  • Integration: The system is integrated with the tools and services that are currently used by an enterprise.

  • Data analysis: The system analyzes historical data to understand scheduling time patterns and determines availability.

  • Meeting initiation: Depending on whether a request or a suggestion has been made, an AI tool either suggests several meeting times available to all participants or, in case of initiatory-unsatisfactory times of meeting initiation, suggests an optimal time separately from everyone else. Each participant has between one and three time slots to choose from, and the AI ​​tool extends the number of timeslots to adjust depending on the feedback.

  • Waiting for answers: Each participant can choose times suitable for themselves and indicate their decision.

  • Finalization and reminder: At the end of the discussion, the system decides on the time of the meeting and sends a notification reminder to its members in advance.

Real-World Evidence

Cisco and IBM are among the companies, which have implemented the AI Meeting Manager, whose administrative task time has subsequently fallen by 40%. In practice, as the respective user reported, the implementation of Cisco AI cover for meetings has reduced the time required to find the appropriate time for negotiations from several hours to just ten minutes. Another example includes the AI Meeting Manager, which schedules conferences between teams from different departments in different countries or even continents. The time of the meeting is the best available option, and the format depends on the specifics: at an early stage, the considerations are mainly the role of participants, their responsibilities, and the goals to be defined. Meeting the purpose of the participants in a particular format, which can be anything from an effective decision-making session to a strict passing of information. The AI Meeting Manager not only chooses the time of the conference but can also choose consistent project plans and create them.

Role in Streamlining Meeting Processes

AI Meeting Managers are systems that revolutionize the way organizations conduct meetings by amalgamating machine learning, data analytics, and automated systems. These types of systems do not only make the meetings more efficient but also enable them to be more effective, which is why they are becoming an indispensable tool in today’s organizations.

Scheduling and planning the meeting

The most evident benefit of such AI meeting managers is that they enable better scheduling of the meeting itself. Typically, the AI solution collects data from the stakeholders involved in the meeting in order to ensure that the best time is chosen. A typical organization planning a meeting involving several stakeholders manually and discussing the time of a meeting with several options for a good half a day or several days. Meanwhile, the AI tool can conduct the same process in several minutes. First, the tool uses the data provided by the participants to ensure that all stakeholders are available at the time provided. Second, it relies on the algorithm to determine which time slots should be chosen, using the data on the history of meetings for instance. Given the data, the tool can determine if the meeting participants have a preferred time for a meeting and predict how long they might last depending on the specific type of meeting.

Another benefit of AI meeting managers is assistance in scheduling and planning the meeting itself . For instance, if a meeting’s objective is to conduct a quarterly review of the performance, several days before the meeting, the tool can prepare the agenda. It will collect the relevant data, such as performance data, notes from the previous meeting, and current statuses of the ongoing projects into one document to enable the systematic discussion of all the necessary points.

Conducting the meeting

During the meeting, AI meeting managers assist by conducting real-time data analysis, creating the agenda, and taking the minutes. For instance, if it is a strategy meeting, in which the discussion of the current market and competitors’ efforts is necessary, the tool can automatically download the relevant data before the meeting. Moreover, it might have been taught the business rules, such as if the market is growing at a specific rate, the CEO should decide to expand the sales team. If the relevant data is present, the tool can draw the appropriate conclusions and present them similarly to a PowerPoint presentation.

Utilizing Data Analytics for Meeting Optimization

Data analytics become a foundational tool for AI Meeting Managers to optimize meeting processes from their creation to the achievement of outcomes. Since these systems analyze both historical data and real-time inputs, they do not only ensure that meetings are scheduled efficiently but that the probability of success is also higher.

Predictive Scheduling

Predictive scheduling is one of the primary features of AI Meeting Managers. Since the system can analyze historical data on meeting schedules and participant feedback, the optimizer can predict the best times for a meeting to occur. As an example, if there is six months of data on meeting schedules and company divisions, the AI tool can determine which times occur with the highest attendance and engagement rates. Thus, the AI can detect, for instance, that team meetings are usually attended by all workers and are the most engaging if they occur on Tuesday mornings. In this way, the optimizer can then predict that the probability of a higher response rate and success for this type of meeting is maximized if it happens on a Tuesday morning and add this to the schedule.

However, the AI does not rely solely on density but also takes into consideration the type of meeting, the length of the average meeting, and potential preferences of the time for all participants. Furthermore, if there are major holidays, public events, or company-wide meetings that could interfere, they can be excluded from scheduling.

Dynamic Agenda Setting

Agenda setting is also significantly improved by the power of data analytics in AI Meeting Managers. The systems can analyze the goal of the meeting and use inferred information to collect a dynamic and focused agenda. For example, if a meeting on the review of the current project is scheduled, the AI will collect the latest data on project metrics, detect the general issues concerning the project based on the current setback or improvement, and create an agenda tailored to the needs of the meeting.

In this way, every schedule will be tied up directly to the exact requirements of the meeting, and no useless and unnecessary points will be added. This means that such types of algorithms can learn to optimize time to complete the necessary discussions on each occasion.

Real-Time Decision Support

AI tools also provide data analytics in real-time to assist in the discussion. For example, if a marketing strategy is discussed, the AI optimizer can instantly provide information on all pertinent data, such as trends or statistics in the specific area.

Integration with Calendar and Scheduling Tools

AI Meeting Managers are unique solutions, considering that they need to smoothly integrate with already existing calendar and scheduling tools. This detailed insight aims to showcase how exactly AI meets such a need, as well as specify the tools with which AI should be integrated for effective scheduling. As a result, the discussion reveals that the integration process plays a significant role and that AI tools commonly rely on application programming interfaces to complete the task. The two common tools mentioned are enterprise solutions – Google Calendar and Outlook .

Calendar Inclusion

A specific example of such a situation may include the presence of a synchronized event or appointment in individual calendars. All participants of the meeting use Google Calendar, and the meeting organizer decided to establish the event. As a result, the first step of the process should be scheduling the AI Meeting Manager to Google’s Calendar API.

The appointment is now established and is synchronized via the API. The manager uses the data to scan through each of the participants’ calendars, finding any overlaps. Consequently, the system determines that the original date may not be suitable. When providing an alternative, the AI Manager – based on the number of instances in the calendar, may suggest a day and time frequently used for such events in the past.

Synchronization Process

Furthermore, becoming synchronized with the local calendar API through the use of Outlook follows a similar process. The only key difference is the very interface of the API, as other characteristics are almost identical. As such, the original meeting date does not have suitable conditions and is not favorable for most participants. Alternatively, the system offers an identical date and hour, as was the result when synchronizing with Google Calendar.


The emerging AI System efficiently runs the data of all of the World Company’s team members. Generally, as the members are situated on different continents, the manager must establish that each individual works around from 8 am to 4 pm. Regardless of the hours, the algorithm consequently avoids the event establishment during the known off-hours.

As such, a strong feature of AI Meeting Managers revolves around their integration with existing calendar systems. For instance, the discussed tool synchronizes with family Google Calendar or any other enterprise tool effectively.

Enhancing Communication and Collaboration

AI Meeting Managers make meetings more than an item scheduled within teams by automating and enhancing its lifecycle. Thus, they play a significant role in improving the communication and collaboration within teams. Specifically, these systems streamline information sharing, facilitate real-time collaboration, and improve post-meeting follow-up and team connectivity.

Streamlining information sharing

AI Meeting Managers feature a streamlined approach to information sharing. In particular, they automatically generate and share agendas and pre-meeting materials, ensuring that all team members arrive at the meeting prepared. For instance, a team works on a project, and its members are located across several regions. Then, the system captures the project updates shared by the project manager and the discussion on key items included in the agenda if the meeting has been scheduled. It also includes background materials that can be used during the meeting and automatically shares this content a week or at least several days before the meeting . Therefore, team members come prepared to participate, and the need to catch up with everyone is eliminated.

Facilitating real-time collaboration

AI Meeting Managers facilitate live or real-time collaboration during the meeting. Notably, they include such tools as live note-taking, real-time data presentation, and discussion board. For example, if a team arranges a brainstorming session and meetings AI records all ideas shared during the meeting, categorizes them, and builds a word cloud or similar representation . At the end of the meeting, participants can see the detailed list of all ideas.

Improving post-meeting follow-up

AI Meeting Managers feature automation of post-meeting follow-up. In particular, they can send meeting minutes and are capable of keeping track of who promised to do what . For example, a strategic planning meeting took place, and the AI system emailed everyone the minutes of the meeting and assigned tasks in the following days. A month later, when the assigned team missed the task’s deadline, everyone got reminders from these tasks received updates in these tasks . At the same time, minutes were sent directly to the software system, which manages the relevant project.

Improving team connectivity

Another important aspect of AI Meeting Managers is that they enhance team connectivity. In other words, they can communicate with such tools as email, Slack, Microsoft Teams, or Zoom. Members are also capable of either preparing or pulling up information instantaneously. For instance, a project is facing an unexpected challenge, and the team must meet to address it, and all data created in Team Slack during the week is analyzed. Then, the project manager calls for a critical meeting, and the AI program schedules it, sending all the necessary information to Zoom . Scheduled kept in Teams, which are used by the organization.

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