The explosion of cloud-based collaboration software in the enterprise means that even teams within the same organization may be using different tools. Developers in an organization, for example, might have gravitated toward Slack or Zulip, while their sales colleagues are using Microsoft Teams or Facebook Workplace. Collaboration software makers are frequently adding integrations with third-party apps to help wrangle multiple tools for file management, managing projects, tracking bugs and other features. However, artificial intelligence in the future might be required to truly tie together systems from different vendors.
According to a report from research firm Tractica, a number of application providers are exploring the use of artificial intelligence in the future--namely, chatbots--as a way to make communication more seamless. “Most of these chatbots live on conversational platforms, such as Slack, HipChat, Microsoft Teams, SAP Jam, Cisco Spark, and others,” according to the report. “Enterprise chatbots can perform a wide range of functions, such as meeting scheduling, managing and transcribing stand-up meetings, proofreading, and project management.”
Collaboration software maker Slack appears to cede the point in a blog post from its Frontiers conference this year: “According to a 2018 Forrester report, 30% of workers’ time is spent ‘interacting with dozens of internal systems, repositories and reporting apps. Bots can help surface data to the right people at the right time, and it’s not difficult to create them.”
Chris Marsh, an analyst at 451 Research, says artificial intelligence could serve as a sort of middleware to make collaboration smoother among different workplaces. “AI will be a big part of how this plays out,” Marsh said.
According to a recent report from 451 Research, the company envisions Slack’s long view as a new “work graph” that integrates communication from different systems using metadata: “Every integration point (and the data travelling through them) is a node, with metadata spanning those nodes supporting agile multi-app workflows we call WorkOps, and machine learning leveraging both of those to surface relevant context into the user's hub. More user attention will bring more data, content and workflow into the platform, across which artificial intelligence and machine learning can drive personalization. Deepening workflow lifecycle abilities should drive more engagement, ultimately leading to more sophisticated types of apps being created. Along the way, it will draw value from other discrete segments.”
Marsh said that machine learning will have a role in a central, behind-the-scenes work graph, contextually surfacing work into the work hub where users are, and helping to automate work streams through a mesh that sits between the graph and the hub.”
The report from Tractica suggests that Microsoft may be even more motivated to incorporate chatbot AI tech into its Teams collaboration software, in part because it has a wider appeal to non-tech businesses than Slack’s.
“Microsoft also has an advantage with larger enterprises, a market segment that has been difficult for Slack to penetrate,” the report says. “Microsoft makes its Bot Framework authoring tools available for free and for developers to use across various platforms, but the genius of that strategy is that Microsoft is betting developers will look closely at placing their collaboration, productivity, workflow, and project management-related chatbots on Teams. Tractica believes Microsoft Teams will quickly gain traction as an enterprise messaging platform and for chatbot use, though it will take a few years before Microsoft catches Slack as the largest enterprise messaging platform.“
Cisco’s collaboration tool, Webex, calls its use of AI in the product “cognitive collaboration.” The company points out efficiencies AI and machine learning can deliver, in part by integrating a digital assistant than can make things like setting up meetings and conference calls as simple as using a wake word.
“AI capabilities will make your meeting a zero-touch experience, so you can join a meeting, call a contact or start a recording with just your voice,” according to the company. “While available now, this is still a burgeoning technology and you’ll see functionality increase rapidly with the ability to assign action items, scheduling meetings and take notes.”
According to Cisco's whitepaper on the subject, “[i]ntelligence is a combination of data and powerful analytics to deliver greater context. Data may be obtained from many relevant sources including sensors, bots, enterprise applications such as CRM, IOT sensors, people profiles, including insights to enterprise calendars and meeting resources, even social data.”
Cisco uses AI mixed with computer vision to identify meeting participants through facial recognition, helping each participant know who’s in the virtual room. Machine-learning-based noise detection can recognize and eliminate audio distractions like someone typing on his or her keyboard, or a dog barking in a participant’s home office.
The company plans in future releases to include automatic transcription of meetings, using AI and computer vision to identify gestures used in conferences to help add context to what’s being said.
“When combined with analytics that identify patterns and relational clusters for individuals, teams, organization and customer insights we are able to present the right information, for the right team at the right time and place,” the Cisco paper suggests. “This powerful combination delivers cognitive collaboration integrated into workflows for connected, relevant and human experiences. “