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Is AI Rx for CX and the Agent Experience?


AI technology
Image: Pitinan Piyavatin - Alamy Stock Photo
While it has been a long process, artificial intelligence (AI) has moved from a far-off vision of the future to becoming a mainstream staple of today's contact center. However, AI alone isn’t a panacea for solving the many problems plaguing contact centers, but it’s certainly helping to improve the customer and agent experience in many different ways.
Looking back 30 years, my first industry analyst report was on speech recognition, followed by a report on AI and neural networks. Back then, speech recognition was primarily speaker dependent, meaning the speech recognition system had to be trained for each user’s individual voice, and the speaker needed to pause in between each word. At the time, AI was primarily focused on expert systems that could answer questions or solve problems using rules-based logic for a specific domain.
Fast forward to 2022, AI is being used across industries and in many use cases. Most of us encounter AI applications and systems without even realizing it, such as when Netflix uses machine learning to provide personalized recommendations. As consumers, we’re increasingly using AI every time we get in our cars (blind-spot detection), enter high-security areas with facial recognition, ask Siri or Alexa for assistance, or reach out to a contact center for customer service.
While traditionally conservative and slow-moving, contact centers have quickly embraced AI and speech technologies to help improve operations and share insights with agents, supervisors, and business managers, helping to provide better and faster customer service.
Remedies for Both Customers and Agents
Contact center AI tools can be categorized either as agent or customer-facing. Customer-facing applications include chatbots and conversational AI for self-service or call triage and routing. Conversational AI replaces touch-tone IVR with more natural dialog interactions, enabling customers to access information without talking to an agent.
Based on primary research, as well as discussions with vendors and customers, I expect around 10-15% of customer service requests to potentially be handled through conversational AI by the end of 2022, growing to 20-25% by the end of 2023. Customers calling in to a company can talk naturally without dealing with annoying IVR prompts and pressing the keypad to enter information and can access information or conduct transactions 24/7 without having to talk to an agent.
Agent-facing AI technologies assist agents as they interact with customers, and can be used for:
  • Agent assist
  • Sentiment analysis
  • Agent coaching, suggested response, next best action
  • Workforce optimization
  • Robotic process automation (RPA)
  • Intelligent automation
With agent assist, bots can listen for key phrases in the background and assist agents by providing information from a knowledge base when they hear these phrases, saving the agent time and producing better outcomes for customers.
Businesses can assess customer attitudes and emotions using real-time or post-call sentiment analysis and leveraging several AI technologies such as natural language processing (NLP) and machine learning. This information can be used to better guide agents in real-time, improve coaching and training, and enhance the overall customer and agent experiences.
An ideal AI use case is for workforce optimization (WFO) and workforce engagement management (WEM). With insights into peak hours and channel usage, AI can help supervisors and administrators better staff their contact center based on past trends and future predictions. Agent coaching and guidance is another area ripe for AI assistance, as the technology can listen to conversations and identify agent training and coaching opportunities.
Another exciting area is RPA, where AI is used to automate and handle routine back-office tasks, such as data and form entry, generating invoices, and updating customer profiles.
An emerging AI area is intelligent automation, combining elements like NLP and sentiment detection with robotic process automation technologies and workflows to better personalize the customer journey. It can analyze both the historical customer record and real-time data and context to predict customer intent and identify if and when issues should be escalated to live agents. Intelligent automation can help reduce after-call work and wrap-up time by automatically updating the customer record instead of having the agents spend time doing this.
A Growing Market
According to Five9’s soon-to-be-released Business Decision Maker survey, the number of organizations using AI for customer service is quickly rising. While only 19% of respondents were currently using AI tools such as machine learning and chatbots in their contact center in the 2019 survey, 55% of business decision makers in the 2020 survey were using AI tools, which increased to 73% in the 2021 survey. For the organizations not currently using AI, 39% plan to use AI in the next year, with only 19% having no plans to use AI, and 43% not sure.
Though businesses are embracing AI, consumers aren’t as enthralled, especially when it comes to using virtual agents. According to the latest Five9 Customer Service Index survey that interviewed consumers in the U.S., Canada, and Europe, 38% of respondents stated they use virtual agents/chats when available. Only about 20% are keen on using virtual agents for information, and 32% just flat out don’t want to use them. Usage varies by age, with 44% of respondents ages 18-29, and 45% of those 30-49 using virtual agents, while only 33% of those 50-64 and 19% of respondents over 65 want to use virtual agents. Those 65 and over are not interested at all.
Looking Ahead
While the good news is that many organizations will be experimenting with and trying out AI technologies to enhance their contact centers, there will inevitably be many false starts and mistakes along the way, leading to customer and agent frustration. Expect to see lots of trial and error in the near future.
Most organizations today are still trying to figure out where and how to use AI – they know that it’s important, but they don’t know where to start, or where they’ll get the biggest bang for the buck. Before rushing out to deploy AI, focus on how to get started in a practical way. Identify your goals and what you are trying to accomplish – do you want to improve the customer experience by shortening hold times or enhancing self-service capabilities, or do you want to improve the agent experience with agent assist and coaching capabilities? Identify the best use cases that meet your business objectives, and then add on as appropriate.
AI technologies are great tools to help contact centers improve operations. But it’s important to start with the right use cases rather than jumping in blindfolded. AI is a solution that can help cure what ails many contact centers – but make sure you’re getting the proper advice from experts to avoid any negative side effects.

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This post is written on behalf of BCStrategies, an industry resource for enterprises, vendors, system integrators, and anyone interested in the growing business communications arena. A supplier of objective information on business communications, BCStrategies is supported by an alliance of leading communication industry advisors, analysts, and consultants who have worked in the various segments of the dynamic business communications market.