Why AI Will Make Collaboration Experts of Us All
By Kelly Bousman
Sr. Vice President, Marketing, AVI-SPL
Editor’s note: Seventeen unified communications (UC), video and collaboration leaders from Fortune 500 and large enterprises met at AVI-SPL’s 2018 Customer Advisory Board (CAB) meeting and a subset of six CAB members met over three months in 2019, to envision AI’s role in improving collaboration and meetings.
AI Will Change the Way We Work and Collaborate
Digital tools have changed the way we work, meet, collaborate and innovate. The physical constructs we once knew — hallways, office machines and water-cooler conversations — transformed into virtual spaces, mobile devices= and video calls. Connecting people digitally in a video everywhere environment fueled by cloud applications has literally torn down barriers, opened teamwork to remote participants and made collaboration fluid and seamless. We realize these benefits now and we’re on the brink of exponential gain with the arrival of artificial ontelligence (AI) in the workplace.
Today, artificial intelligence, or AI, is growing quickly. Thanks to larger, more structured data sets and increased computer processing power, machines are quickly learning how to perceive, comprehend and translate complex inputs, then make data-driven decisions. Smart machines are bringing new intelligent automation to the workplace as well as our personal devices.
For our exploration into how AI will enhance collaboration, we focus on recent advances in natural language processing (NLP) and machine learning. We see significant potential as these AI applications enter the modern workplace, enterprise workflows, and even the workforce as fellow collaborators to improve the efficiency and efficacy of meetings.
AI works best in tandem with human intelligence. A new collective intelligence will make collaboration experts of us all. Whether launching the next presentation, teaching a class or starting a deep-dive collaboration session, AI will be working to eliminate the typical friction points in meetings and teamwork while reducing technology start-up time.
End users and IT, HR, facilities and real estate teams alike will reap significant, measurable benefits in increased engagement and productivity, improved talent acquisition and retainment and optimized use of real estate and technology investments. Throughout this paper, we review the use cases for AI that will have the most dramatic impact on the digital workplace.
AI for Pre-Meeting Efficiency
AI has the power to improve meetings before they start with smart scheduling, auto-composition of messages, intelligent risk management and self-healing. Removing these tasks from human meeting operators and applying contextual logic to them will jump start teamwork and focus efforts on collaboration rather than coordination.
Sometimes coordinating the meeting time, attendees, and agenda can take as long as the meeting itself. Enter AI to optimize this process. Applying NLP, AI responds to commands by voice or text and connects to calendar applications to set appointments, invite participants, locate the best meeting room location and track responses. Imagine using your voice to quickly and easily launch automation processes that book your next project meeting and invite the core team to it, knowing this ability is part of your AI-enabled task library.
Combined with machine learning algorithms, AI will learn who should be part of a meeting, the best time and locations for the meeting and even predict preferences of attendees. For example, AI will know the meeting organizer prefers afternoon working sessions, but not immediately following budget meetings. AI’s handling the tedium of scheduling tasks in the background, lets organizations capture countless hours of productive time.
Auto-composition, something already seen in email applications like Gmail and Outlook, is an essential addition to smart scheduling. AI bots compose calendar invitations and write email messages to attendees with the meeting agenda, attaching notes from the last session if available. Today, auto-composition completes sentences and recommends relevant replies for email messages. When integrated into meeting workflows, this language automation takes on the task of meeting messenger and streamlines communication. Email volume will drop while team efficiency grows.
Identifying and managing quality and security risks
Delivering successful meetings goes beyond coordinating people to orchestrating the technology that supports the team. System and network variability can affect meeting quality by dropping packets in a video call, hindering content sharing or delaying audio streams. Security vulnerabilities could expose intellectual property to viewers outside the trusted, authenticated team.
AI can identify and resolve these common faults. Machine learning will respond to network and system anomalies, intelligently changing configurations or throttling bandwidth to support demand without disrupting the meeting, interrupting a participant or alerting the help desk.
For meeting content flagged as proprietary and protected, machine learning is in the background watching for and researching security holes or intrusion attempts. For example, packet loss detected at 9:05 a.m. kicks off an AI-enabled investigation to find the task using the bandwidth. Violators will be shut down more quickly with AI onboard, while the meeting host and IT operations team is instantly alerted about the potential security threat. This pre-meeting monitoring with self-healing protocol removes meeting-start challenges. With this, AI-enriched automation saves IT and facilities teams hours of time otherwise spent tracking and resolving routine service tickets and frees up time for more strategic support tasks.
AI for In-Meeting Productivity
Once AI takes care of meeting preparation — coordinating people and technology for collaboration — it will join the meeting. Now the real fun and productivity hacks begin. AI will take on several collaboration roles, from virtual digital assistant, to self-service help desk, to real-time, self-healing, system agent — helping us all collaborate more effortlessly and meaningfully. Eventually, AI may also take on the role of integrator — connecting multiple AI agents or bots to coordinate the best, most efficient outcomes for teams.
Some of the most enticing AI skills for meetings are triggered by voice-activated controls which use conversational AI or NLP to comprehend requests, identify the speaker and transcribe commands from speech to text. The human voice replaces other user interfaces, like touchscreen panels, occupancy sensors, keyboard strokes and mouse clicks. UC and meeting solution vendors are beginning to implement voice recognition into their own audio processing systems so that voice control can be handled at the core of the meeting, not from competing devices. Soon, new skills libraries will use voice control to start a meeting, launch a video call, control devices in the meeting room and schedule meeting follow-up actions.
A welcome productivity hack will be the use of voice enabled search queries during meetings. We may ask our AI-enabled, voice-activated assistant, “In what year did x company patent y product?” or, “Who volunteered to do this task?” AI will translate the query, know its context, conduct the search, and return results in a non-intrusive format by displaying possible answers on the shared meeting screen for local and remote attendees. We envision voice commands initiating the search but the search results returned as text or visuals on a screen, almost like an augmented reality layer. As teams use and collect query results, machine learning will improve search responses for future meetings. Think IBM Watson and its capacity for deep learning that has led to tremendous leaps in medical diagnostics.
When AI eliminates connectivity challenges that delay meeting starts and enhances teamwork with simple, voice-activated search queries, it will capture untold hours of collaboration and improve project outcomes.
Virtual digital assistant
Having a virtual digital assistant as a project team member allows the human participants to focus on creative problem solving while AI manages meeting workflows. An AI assistant may take meeting minutes and distribute them. It also may suggest supplementary research, such as related product development or customer insights, and resources, including subject matter experts or past results from trials. AI-powered discovery will shorten research time and inspire ideation. Integrated with a team project management application, like Asana or Slack, the virtual digital assistant will assign tasks with deadlines, track task completion and report project progress.
Working efficiently with virtual digital assistants like Google Assistant and IBM Watson in meetings will not only save project discovery and management time but will create a new level of collective intelligence which will greatly accelerate team output, innovation and time to market.
Self-service help desk
AI chatbots are already at the front lines of customer service. Zendesk is a leader in AI-enabled customer experience, using natural language processing and deep learning to continually improve service levels.
Having an AI-powered support app dedicated to meetings — real and virtual — will resolve common meeting friction points before they disrupt teamwork. With conversational AI, end users will ask for help during a meeting, either via voice or text. Using semantic algorithms, AI will extract the technology issue and transcribe the request. Issues will be quickly triaged by the chatbot who either responds from the service knowledge base with the most likely resolution or routes a new service ticket to the most qualified help desk technician.
AI speeds technical support to keep the meeting on track and the ideas flowing. It also steps in as virtual agent, removing routine issues from the help desk queue and saving IT operations teams time and resources. IT will be able to offer a more personal, higher level of support to users. AI can also take on the role of compliance officer for customer service level agreements by comparing new trouble tickets to current SLAs and triggering escalations to ensure timely resolution.
Even better than AI-powered self-service is AI-powered self-healing. By connecting machine learning to IT system health monitoring tools, IoT-enabled devices and hardware APIs, AI will detect and initiate automated protocols to mitigate device failure, application error, network connectivity issues or operating system errors. Self-healing happens without human intervention. Moreover, AI will work in the background to proactively adjust system or device settings to improve the user experience. Meeting room audio will suddenly become more audible and clearer. Other environmental factors sensed via IoT in the meeting space, such as ambient light, will trigger changes in a display. AI will silently but perceptibly optimize video call quality to account for network bandwidth or other performance factors.
AI tools for self-healing employ predictive analytics and automation to dramatically reduce technology downtime, avoiding productivity loss and lowering maintenance costs. User experience and satisfaction is enhanced, encouraging adoption of powerful team collaboration technologies. IT and facilities teams are relieved of routine manual checks as well as complicated error resolution when AI is a technology teammate ensuring access to collaboration tools.
AI tools and AI enhanced meetings will grant new access to collaboration for those otherwise left out without accommodations for a disability, such hearing or vision impairment. It will create more inclusive meeting experiences for all participants and break down barriers, including language barriers. With NLP and machine learning, meetings will be automatically transcribed and translated to any language in real time to allow all team members to fully participate in meetings with ease.
AI for Post-Meeting Action
Collaboration extends well beyond meetings. AI will improve the meeting experience and the teamwork that follows by measuring engagement, tagging and indexing content, managing project workflows and predicting optimal technology and spaces.
AI has made strides in estimating human sentiment, most recently by modeling speech prosody, or rhythms, to coach call center agents while handling customer inquiries. AI reads voice modulations to detect the underlying expression, which may not be conveyed by the words alone. Similarly, facial recognition can detect basic emotions. With these tools, AI may perceive the sentiment of meeting participants, their level of engagement in the meeting and their satisfaction with the technology and space supporting it. Alternatively, AI may add a smart routine to poll all meeting participants, not just the host. Assessing the broad sentiment of an audience with a presenter — a class and a lecturer — also could be a coaching mechanism for the presenter to hone content or delivery.
Measuring sentiment through observation rather than user input may trigger serious privacy concerns which must be evaluated. Consider the potential for AI to more deeply measure satisfaction or discord than the standard, end-of-meeting, star-rating, pop-up survey. We see applications of AI-powered sentiment analysis to broadly advise IT, HR and facilities managers about which meeting rooms are preferred and which technology causes excessive frustration, or benefit, for users.
We already see AI productivity applications on the market that monitor phone conversations, email, and other communications channels to measure, track, and predict sales employee performance. These applications bring the same risk of bias and error as automated resume screening systems have demonstrated. So, it’s important to maintain a human feedback loop for such AI uses.
Today, simple NLP can transcribe the spoken word to a text file. Taking this further, AI will use voice recognition to identify the speaker and attribute their contributions in meeting minutes. AI will also discover patterns in the transcription, tag common keyword phrases, like the name of a product, person, project or company, and then index those important terms for future search. AI will easily do this with text, audio and video. From there, AI will build a structured knowledge base of meeting proceedings that include not only the spoken word but also a record of the content and research shared.
This knowledge base of meetings will organize the work of various teams on a variety of projects, enabling host organizations to notice opportunities for cross-functional approaches to teamwork, invention, problem solving and business management. Having tagged and indexed meeting minutes, making them easily accessible and searchable also will aid collaboration and accelerate project outcomes.
AI virtual digital assistants will supplement and potentially become our project managers. Using voice control, team members can receive a list by email or text of new project tasks assigned to them. AI will also remind task owners of their due dates and task dependencies. AI will learn team member roles and skills, appropriately assigning new tasks to people based on fit. Behind the scenes, AI assistants will track all project milestones and report progress to the team lead. AI will be a workflow optimizer, creating, assigning and tracking tasks for harmonious collaboration.
When AI manages projects, people are freed to focus on their ideas and contributions rather than reporting the status of their tasks. Project management tools help streamline team communication, but AI will take workplace collaboration to new heights.
IT, facilities, real estate, and HR teams all seek to optimize their resources for the most positive user experience, and to base their decisions on objective data. With AI-fueled analytics for meeting scheduling, space utilization, system health, project workflows, and user satisfaction, it will be able to predict the optimal allocation of meeting space, technology and support personnel. These AI-powered recommendations will eliminate budget waste. They’ll also identify possible savings for current facility configurations.
Space, technology and people are the most essential resources of any organization. AI will propose the ideal ratio of workspaces to meeting rooms plus the most useful technology to empower users so workplace strategy teams can consider and maximize all resources. These actionable analytics will provide business intelligence that dramatically reduces operating costs, increases productivity and enhances the bottom line.
AI Improves Collaboration and Workplace Experience
We see a future where AI is the most valuable player on a team. When AI eliminates the most common operational pain points — meeting scheduling, technology availability, knowledge access and project management — people can truly collaborate. Teamwork will flourish when people focus on creative problem solving and innovation. Projects will have stronger business outcomes with AI working in the background to facilitate productive meetings and provide contextually relevant information that speeds decision making and improves results.
While AI augments team collaboration, it also unburdens IT and facilities departments from continual monitoring, maintenance, and management of meeting spaces and technology. This enables help desk technicians and local operations personnel to focus on more complex issues, like security. With this enhanced teamwork, efficiency and creativity, the overall workplace experience elevates.
AI benefits for workplace experience will extend beyond real and virtual meetings to other workplace environments like smart buildings, IoT ecosystems, research laboratories and training rooms. It will also improve organizational communication by indexing enterprise video assets, recommending training tracks, predicting market shifts with social media listening, and automating administrative tasks so employees can more meaningfully collaborate.
Organizations and vendors alike will be critically tasked with creating parameters, data sets and appropriate business goals for AI. Similarly, organizations will be charged with ensuring privacy, eliminating bias and managing permissions when deploying AI-powered solutions.
AI will bring a new humanity to the workplace as long as workplace strategy leaders focus on AI applications that aid rather than invade human creativity. We see human factor design coupled with AI development as the next critical step for technology adoption and workplace experience success. With a well-informed, collective but human-centered approach, AI will make collaboration experts of us all.
Is your organization using AI to improve collaboration, enhance meetings, or better manage the digital workplace? Please comment and share your experience.