AI + UCaaS + CCaaS: The Future is Now

AI + UCaaS + CCaaS: The Future is Now

This article was originally published by Telecom Reseller.

Artificial Intelligence (AI) is reshaping communications as we know it. With machine learning, speech technologies, collaboration tools, data analytics, and integration capabilities joining together in a powerful new digital mesh, both the workplace and the contact center are proving to be among the biggest beneficiaries. Enterprise productivity and the customer experience are the subjects of many AI-based innovations, representing the next evolution of automation.

And you don’t have to wait to cash in on the benefits. The future is now.

Here’s how the latest communication innovations are impacting UCaaS and CCaaS and how to apply “what’s next” today.

AI in Communications: What We Can and Cannot Do

First, let’s define artificial intelligence (AI). Most people think of AI as machines that mimic human cognitive functions such as learning and problem solving. AI is also used to describe any device (usually a computer and software) that perceives its environment and takes actions to maximize the identified goal, for instance, speech and text analysis and response. While AI technologies perform speech and text processing very well, these advances are not yet equal to the powers of the human brain.

Nonetheless, current AI capabilities are helping enterprises automate responses to contact center customers and UC users. Complex tasks still have to be supported by humans. In other words, AI is not ready to replace all the contact center agents, but it’s ready to assist both agents and UC users, improving employee productivity and accelerating the customer service process.

Conversational AI: Benefits with Contact Center as a Service

In the age of personal digital assistants like Amazon’s Alexa, customers are demanding a higher level of service. AI is changing interactive voice response (IVR) technology, which has historically produced relatively static menus to callers and hasn’t responded well to erroneous or mistaken inputs. With advanced innovation, AI systems now have the ability to train themselves based on the businesses they are supporting and generate natural language responses derived from the library of customer service answers. At a minimum, virtual agents can greet customers, answer questions, and fulfill requests on their own without participation from contact center agents.

But even better, AI systems can also actively assist agents, supporting their live customer conversations as they happen in real time. Data analytics engines integrate with real-time voice recognition technologies to predict what the customer wants and supplement live service by proactively providing relevant information to the agent’s desktop.

This point was made clear in a conversation with Dean Manzoori, Vice President of Cloud Communications at Masergy, who explained that enterprises are already capitalizing on cloud contact centers, integrating data analytics with real-time voice recognition technologies to enhance the customer experience.

These intelligent service interactions reduce costs, improve customer satisfaction, and allow the real, live agents to focus on complex customer queries. AI technology also offers the ability to:

  • Transfer customers from virtual to live agents when the AI cannot support the caller’s request
  • Analyze the chatbot text conversation and provide references to a live agent when necessary
  • Produce outbound calls to customers using a virtual agent
  • Provide relevant information to the agent, giving them the caller’s question or topic as well as a history of the conversation with the virtual agent--whether it occurred via phone (audio) or chat/email (text)
  • Provide a human-like experience using Natural Language Generation (NLG)
  • Track dialogue, storing, and cataloguing the conversation as well as allowing two different responses to two different customer questions
  • Determine the topic in which the live agent should assist, using Natural Language Understanding (NLU)
  • Automate system configuration for the supervisor and agent profiles and permissions

Conversational AI: Benefits with Unified Communications as a Service

Combining unified communications technologies with AI is also a big benefit. Today, AI for UC is focused on improving system usability, problem-solving, and data analysis. The combination of UC and AI helps people do their jobs better by allowing machines to guide them, interpret data, and analyze information faster. The goal of unified communications mixed with AI is to work smarter, not harder, and therefore be more productive.

Simple examples include keeping meeting participants informed with regards to:

  • Meeting attendee lists
  • How to join a meeting
  • How to share documents or content
  • How to access features and make them work as desired

The biggest UC challenges have traditionally been problem-solving, and AI is effectively assisting UC users with:

  • Intuitive call recording
  • Easy call transcription
  • Automated participant identification
  • Intelligent speaker tracking
  • Advanced voice assistants
  • Automated user profiles and permissions

Five Steps to Success with Conversational AI

Ready to infuse your communications and contact center with machine learning and AI-focused technologies? While AI seems like a future capability, there are many technologies that exist today. To get ahead of your competition, you’ll want to be a leader, not a follower. To start applying advanced AI-based technologies, you need to unite new tools, creating interoperability via one cohesive environment. These five steps are critical in creating the future today:

  1. Move the contact center and communications systems to the cloud in order to:
    1. Support advanced features and functions, accessing capabilities that cannot be implemented in your old system. Remember that legacy communications technologies are static. Versatility and flexibility are limited. Making major changes requires attachments because the old technologies were not designed for the new communications missions that exist today.
    2. Make AI and emerging technologies more affordable by shifting from CAPEX to OPEX business models. Cloud-based technologies allow enterprises of every size to gain access to features and functions that were previously reserved for enterprises because they were costly and required IT staff.
    3. Enable the workforce of the future. Businesses need to embrace the remote communications capabilities and social networks that are so common today. When combined with machine learning, CCaaS and UCaaS can enable a mobile workforce and deliver services that mimic the easy-to-use features of Twitter and Facebook.
  2. Support communications with a network service that can ensure global business continuity, delivering the same service level agreements (communications quality) across every location in your enterprise footprint.
  3. Use software-defined networks to support communications so you can take advantage of the IT agility, performance optimization, and management efficiencies they deliver.
  4. Consider an investment in Integration Platform as a Service (iPaaS), which removes the complexity of integrating multiple cloud applications, making complex business process automation easier. iPaaS is a key element in making that “speak and it will be done” Alexa-style approach now applicable for the enterprise. Learn more about cloud communications and iPaaS.
  5. Start experimenting with emerging technologies and building the voice-centric enterprise and then build on your successes. But start slowly, one technology and application at a time, to help reduce any unrecognized risk.

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About Gary Audin

Independent Communications Consultant, Delphi Inc.
With more than 40+ years of computer, communications, and security consulting and implementation experience, Gary Audin is a celebrated author and IT thought leader with regular articles published by Telecom Reseller, No Jitter, TechTarget, and Webtorials. Gary has operated and managed data, LAN, and telephone networks including local area, national and international networks as well as VoIP and IP convergent networks both in the U.S. and across the globe. As a trusted consultant, he has advised domestic and international venture capital and investment bankers in communications, VoIP, and microprocessor technologies.