The old metaphor that “a camel is a horse designed by a committee” does a disservice to both the camel and the committee. If a committee met to design a horse for the desert, a camel would be the best outcome, given that a camel is the ideal solution for the desert.
At the risk of torturing that metaphor, let’s imagine how artificial intelligence (AI) would actually assist in the meeting room where the “Let’s Design a Horse for the Sahara Desert” Committee convenes each week. Their job is to overcome design challenges and launch a better “ship of the desert.”
AI sets up and helps schedule and run the meeting.
With the help of AI, meeting chairperson can automate the routine functions of meeting logistics. Using a voice-activated smartphone app, and the voice command, “Alexa, show the free time available for all committee members for next Wednesday, and show the conference room schedule”; followed by, “Alexa, set up a special meeting of the Design-a-Horse Committee for next Wednesday.”
AI accesses each committee member’s calendar and suggests the optimum meeting time. If necessary, the software could provide alternatives to resolve scheduling conflicts or instruct the conference room scheduler to free up time for the meeting.
So, the meeting is under way. As attendees enter the meeting room, their devices are paired with the AI meeting software. Everyone knows how much time has elapsed, what progress has been made towards previous action items, and who is responsible for the agreed tasking.
AI accesses information and resources.
This week’s meeting agenda involves overcoming the challenge of lack of water in the Sahara. How many desert miles can the camel walk before heat and dehydration become impediments to the desired outcome?
One of the most exciting promises of AI is its ability to access a large volume of data and analyze it to support the best decisions. For example, the answer to the question on a camel’s endurance would involve multiple variables involving terrain, distance, climate, distance between oases, along with a knowledge of camel physiology.
AI could leverage the committee’s content library to consider those variables. One outcome could be assigning research to each committee member based on qualifications and experience. Or, perhaps the AI could locate subject matter experts, who could brief the committee via conferencing software.
AI synthesizes meeting minutes
Along with automating scheduling and starting and ending meetings, AI technology can record meeting minutes, identify and summarize speakers’ comments, and assign follow-up tasks for the next meeting agenda. Intelligent note taking will edit out the small talk and produce minutes that go far beyond dry text transcripts—i.e., with images and informative presentations.
It is not “if,” but when…
Our tongue-in-cheek example of the camel committee was, of course, a level or two beyond hypothetical. However, the AI implications are real. Machine learning is already impacting our work experience and will continue to be fueled by data, which is growing exponentially.
As business approaches evolve from the hierarchical to management by consensus, meetings will remain at the forefront of brainstorming, creativity, and productive outcomes. AI, now abundant, will continue to make deeper inroads and help keep meetings on track and productive.
