UC environments with something extra
Let’s examine the practical use cases for artificial intelligence in unified communications.
It’s hard to ignore the buzz around AI these days. Artificial intelligence is one of my favourite talking points when discussing the evolving nature of UC. As we move quickly towards accepting handy bots and virtual assistants in our personal lives, UC vendors are rapidly developing enhanced ways for us to communicate in the workplace.
The sheer flexibility and scope of AI in UC means that it’s almost impossible to imagine the full extent of this technology’s potential. There are just too many use cases and options to consider. However, I have noticed a few trends in the way that AI is being used within the world of business communications of late. I’d love to hear your thoughts in the comments too.
Here are some of the areas I’ve been looking at:
10 years ago, the concept of artificial intelligence powering day to day communication was out there with hoverboards and travel to Mars. Today AI is one of the most exciting technologies to hit the business communications space. Customer engagement is the most significant use case for AI, according to research.
However, it’s not just CX that stands to benefit from AI.
If we put CX related AI tech aside for a moment to consider how AI is changing the UC landscape (I’ll write a blog about AI in the contact centre separately very soon), we see a range of new opportunities. After speaking to countless experts throughout this year, I thought it would be worth sharing my insights on some of the exciting things being developed right now. These are the tools that are helping us to communicate more intelligently in the workplace.
Here are six ways to utilise AI in your UC stack:
We’ve all got an Alexa or a Google Assistant at home these days, so this one is an easy one to get your head around. Talking to technology via voice AI and virtual assistants is the simplest use case to help us get more done at work. According to the web, by 2020, half of all searches will be initiated from voice rather than typed search. Telling your Alexa-enabled desk phone to add something to your schedule is becoming a natural part of the modern workflow.
Soon you’ll be able to ask your device to schedule a meeting, set up reminders, and more. Companies like Zoom.ai are already training Bots to schedule Microsoft Teams meetings from text commands. I don’t know about you but ridding myself of tasks like this and having a virtual companion take care of the communication between parties, sounds good to me.
Some would say the days of the SMDR call logger are long gone. Nowadays UC and contact centre platforms are expected to output live call stats on-demand and record all calls in and out of the system. Using AI, call analytics vendors can offer new insights into your ‘dark data’ (the call recordings that you don’t ever get time to listen to). We’re shining a light on a whole new world of information.
Using cloud-based machine learning platforms, you can now transcribe your calls and almost instantly and discover things about your conversations that you would never have imagined. It doesn’t matter whether you have a customer service team, sales team, or have a room full of contact centre agents; you can extract fantastic value from knowing more about what was said. Sentiment analysis helps you to even ascertain the mood of the user and the customer on live calls, prepare to be enlightened!
If you’ve used Google Photos recently, then you’ll know how good technology has got at recognising faces. These tools are so effective that businesses like ‘Accompany’ (recently acquired by Cisco) uses public data to automatically match faces in video meetings to names. Cisco calls this People Insights and has wrapped it up in their latest ‘Cognitive Collaboration’ based portfolio.
Here’s another example:
Imagine how many times you sit down at your desk each week. What if AI could identify your face and log you back into your PC? What if your UC tool could identify the voice at the other end of the phone and bring up valuable information about the caller like their last conversation to your company, their account details, their personal preferences and even the last time they were mentioned in the public domain.
Companies are seeking more contextually rich experiences; therefore by using AI to identify people, it can not only augment useful information and improve the overall experience, but also help with things like privacy and fraud prevention.
Connecting systems, people, and objects is the holy grail when it comes to increasing efficiencies and driving staff productivity. It’s not just people that we need to communicate with anymore.
Using AI platforms such as IBM Watson, vendors are now able to convert speech to text faster than ever before. What’s more, they can initiate machine-based tasks to reduce complex workflows based on the information found in data. Also, tools like IBM Watson Workspace can help you draw insights from conversations from existing tools and solutions like Slack and Salesforce.
Using UC technology such as CPaaS, there are also many more AI platforms you can integrate your workflows with. CPaaS provides the APIs your developers need to initiate calls, messages, and video sessions. Pioneers such as Twilio even offer a ready to go contact centre toolkit called Flex, that you can customise to your heart’s content. If you’re seeking differentiation by tightly integrating your communications with your day to day tasks, then consider hiring a developer to make the magic happen.
One of my personal favourites features of the AI revolution, after living and working in Japan for a couple of years in 2003 is the potential for real-time translation. I find the concept of translation via AI incredible – particularly for companies that cross multiple geographical borders. I only wish I had been able to access something like this when I was younger.
UC vendors can now connect their UC apps and endpoints to AI-powered translation engines to translate and transcribe conversations in real-time. Imagine this; you’re speaking to your German colleague in English, and they are replying in German. The platforms can now translate and transcribe the conversation in real-time, enabling you both to talk in your native language.
Have you ever used Alexa’s music recommendations? Why not take advantage of the same intelligence for your daily task? Imagine sat at your desk, performing your routine duties, and a Bot pops up and offers you a helpful hand in completing the task at hand.
For example, if the Bot hears you talking on the phone and you say, “sure, let’s meet up next week for lunch,” the Bot could offer to schedule the meeting or add a reminder to your list of tasks for the following week.
What if, based on an incoming message to Slack a voice-controlled AI could recommend predefined responses, thus cutting down the time to respond – pretty useful right?
I’m personally very excited about having a virtual assistant at my desk, in my workflows, on my calls, and in my meetings. I’m sure the technology will have its challenges and won’t always get it right, but I’m one of those who will give it a chance and hopes that it will get better. In most cases, it does in time.