AI Is Fueling Smarter Collaboration

AI Is Fueling Smarter Collaboration

Artificial intelligence meets unified communications — and the result is improved data access and ability to predict events.

Artificial intelligence (AI) and machine learning (ML) are reaching into a growing number of applications, systems, and business processes. Unified communications (UC) platforms, which power much of the collaboration in enterprises today, is one of them.

While it’s still early in the real-world application of AI in unified communications and collaboration, offerings are emerging that include bots to enable natural language conversation with data, or to provide voice control of applications such as conferencing systems, said Irwin Lazar, vice president of consulting and advisory firm Nemertes Research.

Earlier this year, Microsoft demonstrated the ability of its Teams application to perform real-time language translation, enabling individuals who speak different languages to chat with one another. And in one of the latest developments, AI is being used to transcribe meetings and capture action items, Lazar said.

Combining and AI and ML with unified communications can lead to two key potential business benefits.

The first is improving the ability of individuals to access data. “Today, finding a document could be tedious [and] analyzing data may require writing a script or form,” Lazar said. With AI, a user could perform a natural language query — such as asking the customer relationship management (CRM) platform to display third quarter projections and how they compare with the second quarter — and generate a real-time report.

Then, asking the platform to share this information with the user’s team and get its feedback could launch a collaborative workspace, Lazar said.

Artificial Intelligence

The second possible benefit is predictive. “The AI engine could anticipate needs or next steps, based on learning of past activities,” Lazar said. “So if it knows that every Monday I have a staff call to review project tasks, it may have required information ready at my fingertips before the call. Perhaps it suggests things that I’ll need to focus on, such as delays or anomalies from the past week.”

Another example is improving the use of meeting tools. “Imagine walking into a conference room, having the meeting system recognize you, see that you have the room reserved for a staff call, and offer to launch the video/content sharing/audio system without requiring you to do anything,” Lazar said. “Or, if someone else enters the room, tell them that the room is in use for someone else and that they can instead head over to room 5034, which is unoccupied this hour.”

AI and ML will continue to have an impact on UC technology in the coming years, in areas such as improving access to information, enhancing the ease of use of systems and applications, and making proactive suggestions or actions based on events.

For example, Lazar said, an AI assistant might tell a user that a colleague is out sick, and as a result, the team might miss a delivery date for a crucial project step. It might then suggest a way that the team can alter the schedule or work assignments to still meet the project target.

Nemertes’ 2018 to 2019 research study on Unified Communications and Collaboration showed that about 41 percent of companies were planning to use AI technologies in the context of unified communications and collaboration.

“So, I’d expect that you see rather aggressive implementation, as companies seek to leverage AI to improve efficiencies and competitiveness,” Lazar said.

Source: ZDNet


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