Artificial Intelligence – Coming Soon to a Meeting Room near You

Nov 08, 2017

After years of anticipation, Artificial Intelligence (AI) is finally starting to fulfill the promise of smarter collaboration. The first phase is primarily centered on conversational AI that addresses routine functions for meetings, such as joining and ending conference calls. The real potential of AI lies in deeper contextual and predictive applications that will follow over the next several years. Expect to see some exciting developments as AI becomes the uber technology that will transform meetings to make them more efficient and better aligned with people, processes and business goals.

We all have our pet peeves when it comes to conference calls. Complex dial-ins, long pass codes, figuring out the complexities of sharing content both locally and remotely, not knowing who’s joined, who’s speaking, loud typing, heavy breathing, dogs barking, the list goes on and on. The misery doesn’t end after the call wraps up when the action items lead to lengthy email follow ups or worse yet don’t get addressed at all. AI could soon come to the rescue and make meetings not only less painful, but also smarter, faster, more engaging, more productive, more strategic and hopefully more enjoyable.

Over the past few years, AI has made impressive forays into our daily lives. Digital Assistants and smart bots have become common place. The impact is all around us with autonomous vehicles (drones and self-driving cars), AI-assisted medical diagnosis, intelligent search engines, voice assistants (Siri, Alexa, OK Google), image recognition, robots in manufacturing, fraud detection in banking, and highly-targeted online ads. Many of these experiences are setting expectations for what we want in our daily communication experiences at work.

Machine Learning has already brought many innovations leading to better meeting experiences such as intelligent view or intelligent framing in a video call, background noise suppression, and rich in-room analytics for better meeting diagnostics. Voice interaction is the next low hanging fruit that vendors are focusing on. While voice assistants that perform basic functions like starting and ending meetings will grab headlines, it should be noted that many conference rooms today are already equipped with touch screen interfaces to perform basic functions with a single tap or click. The true impact of AI will be in embedding cognitive technology within meeting devices and services.

Data, the fuel that powers AI, is now abundant. Thanks to the rapid migration to software-based and cloud meeting technologies, we’re moving to the next step of AI that will infuse cognitive capabilities into meeting applications. Using a combination of face and speech recognition, deep learning, and predictive analytics; meetings in the future will do way more than just bring people together. The application of AI for smarter meetings is centered on several areas -

  • Automating repetitive manual tasks - A bulk of the meeting tasks performed today are manual and dependent on choices/inputs made by users pre-, in-, and post-meetings. The end result is it sucks up significant time and creates friction in user experiences. The most basic level of AI is focused on automating functions such as scheduling, starting and ending meetings, enabling recordings, taking meeting minutes and notes (who joined, who spoke, for how long) and receiving follow ups after the meeting has concluded. An area of complexity for many meeting participants has been seamless sharing of content. Voice commands will automate this process by allowing users to leverage all the content bought into the meeting, control what’s on the screen, and even advance the slides for presentations. Many vendors have already enabled smart pairing that recognizes users, their identity, and their devices when they enter the room to configure the meetings for them. Bots that keep the meetings focused on the agenda and send notifications on elapsed time along with a host of rich diagnostics will make the outcomes more actionable.  Lastly, through a combination of meeting notes and facial and voice recognition, an AI-powered bot will automatically assign tasks to the right people.
  • Tapping critical visual information - The widespread availability of cameras and advancements in sensors is opening up a world of relevant data which is the foundation to building great AI. Video has a distinct advantage over other forms of communication in its ability to capture the full spectrum of information – verbal, written, data, as well as non-verbal/facial cues. Thanks to cameras using facial-tracking to focus on active speakers, we have already seen the elimination of “bowling alley views” in video meetings. In the future expect to see even smarter framing with optimal field of view that will adjust on the fly depending on meeting room size and participants. With a combination of voice and face recognition, AI will enable intelligent notes and recordings (for example, eliminating all small talk from meeting transcripts). Cameras functioning as super sensors will enable a host of new capabilities such as capturing side discussions; tracking participants head movements and gaze to capture non-verbal visual cues that indicate user engagement or interest level (possibly opening up a Pandora’s Box of privacy issues). It would be interesting to see how the context and relevancy of all such information will be accurately applied which could be a challenge for the developers.
  • Connecting people and workflows - The true potential of AI is not in replicating tasks being done by humans or by doing them faster but rather in creating value by adding functions that address inefficiencies in workflows. Given the rapidly increasing output from sensors, machines and social networks, AI can add significant value in making meetings more strategic and actionable. By letting the machine crunch the full spectrum of raw content for insights and patterns combined with its relevance for the business, AI can eventually help lead to better decision making in and outside of meetings. Bots will be able to understand and analyze the discussions in a meeting and suggest ways to connect people and workflows such as recommendations on who to invite, key stakeholders for follow up, and making introductions between people and subject matter experts based on the org chart, skill sets etc.
  • Predictive AI – This is by far the most exciting promise of AI, but also the furthest from being realized. AI-guided analysis customized by job roles can lead to accelerated business decisions. As intelligent devices gain greater knowledge from analyzing large volumes of data, they will accurately predict user needs and meet them before the users themselves realize. Predictive analytics will also anticipate users’ next steps based on their interactions and behaviors. The goal would be to create that magical meeting experience where machines will push at users everything they need in a way that accommodates individual user preferences and behaviors. Imagine an AI bot leveraging your entire content library and automatically choosing the most appropriate meeting content for you, based on the topic or purpose of the meeting, profiles of participants, past content sharing patterns, and target audience, among other things. Predictive analytics will also enable better quality meetings for IT by proactively monitoring the network and endpoints, scanning for performance anomalies, and taking corrective actions before users are affected.

Given the buzz around AI, leading collaboration vendors have shown a deep commitment to incorporating AI into their products and services. IBM Watson Workspace Collaboration leverages the deep cognitive computing and AI capabilities of IBM Watson, one of the most advanced AI platforms in the industry. A feature called Moments creates a summary of the posts taking place in Workspace allowing users to view their conversation history and break down the massive amount of information that is shared. Google has announced itself as an “AI first” company. Its chatbot called @meet (not to be confused with its video conferencing service Hangouts Meet) is a built-in integration for Hangouts Chat and uses natural language processing to automatically schedule meetings and make other suggestions based on the conversation. Slack has an AI and machine-learning division called Search, Learning & Intelligence (SLI) that is focused on reducing the information overload for team collaboration users. Slack has incorporated AI-powered search that helps users find subject matter experts and a feature called Highlights to helps users focus on what’s important first.

Cisco recently launched Spark Assistant, leveraging the deep-domain conversational AI technology from its acquisition of MindMeld. Spark Assistant will allow users to join and end meetings and start and stop recordings with voice activated commands. Earlier in the year, WebEx introduced a feature that detects background noise and prompts meeting participants to mute their microphone. Microsoft is also promising better meetings with Microsoft Teams by integrating machine learning, cognitive services, and speech recognition to improve the experience. Zoom, a cloud-based video conferencing provider that has been growing at a fast pace, announced its first brush with AI in the form of an automated meeting transcript function that creates a searchable transcript and identifies each speaker.

As more and more providers get on an active AI roadmap, the key to success will be turning AI capabilities into a platform that becomes the foundation for internal development as well as exposing APIs to third-parties to create new AI-enabled applications. Smart innovation will be focused on AI-related enhancements that are truly contextual, relevant, and highly personal. An area where AI innovators can differentiate will be easing concerns around security, privacy and compliance. AI will need oversight, but it is not yet clear how that should be done.

While the full impact of AI is out by many years, it is clear that it will touch all aspects of business. Making meetings smarter and intuitive and eventually predictive, AI will change how we view meetings forever. If you are a collaboration vendor, the time to invest in AI is now or else you will get disrupted. If you are a user of collaborative technologies, keep an eye out for new AI services from vendors and start thinking about how they can be used to improve business workflows and processes and the customer experience.  

Category : Big Data, Cloud, Enterprise

Roopam Jain


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