Networking analyst Zeus Kerravala told the London-based show earlier this month that a general set of problems persists in UC, mostly relating to system usability. These include uncertainty over who is in a meeting and who should have been invited, not knowing how to join a meeting, share documents or content, or how to make video features work properly.
Future AI-enhanced UC systems could improve meetings with features such as: more intuitive call recording or transcription, perhaps based on keywords; facial recognition and automated identification to aid meeting set-up; or features such as intelligent speaker tracking. Looking further ahead, more advanced AI features could offer users recommendations on who should join a team meeting, proactively finding and loading useful content, or generating minutes.
However Kerravala warned that mass-market voice assistants, such as Alexa and Siri, are not good enough for enterprise applications. “Voice assistants are becoming incredibly popular but not all are created equal, and this is something to think about,” he said.
Most consumer-grade voice assistants are integrated with what Kerravala referred to as “shallow AI”, which is good at providing broad information such as football scores or weather forecasts, but falls down when asked to do anything complex.
“In most business settings, or in a hospital, for example, you don’t care about the weather, you care about patient status and terminology, and that’s hard for Alexa to understand,” he said. “More narrow, deep AI systems with vertical expertise is the solution, but it is a hard problem to solve.”
Kerravala’s keynote speech was welcomed by industry publication Computer Weekly which wrote that “the concept of unified communications is now so wide-ranging that it is ripe for disruption – or improvement – by artificial intelligence”.
The meaning of the term UC has widened to include more than just voice over IP, video conferencing and instant messaging. Technology such as interactive whiteboards, team spaces and document management are all taken in by the term now. But, said Kerravala, when one considers the rising number of UC tools and the data and content they produce, people’s ability to interpret that data becomes very limited.
“Workers today are getting crushed under the weight of the data and UC tools they have, and are sometimes less effective because of this,” he said. “There are many more ways to communicate and we are using all of them. The intersection of UC and AI is all about helping people do their jobs better by letting machines interpret data and analyse information faster.”