“The Inner Circle Guide to AI, Chatbots & Machine Learning (2nd edition)” is based on surveys with over 400 UK & US  organisations and 2,000+ interviews with UK & US consumers. 

 

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Report summary and contents

 

Executive Summary:

 

As AI can be given access to all of the relevant data a company holds on its customers, as well as unstructured data held elsewhere (for example, forums or social media channels), it has a far wider source of data from which to draw compared to human agents.

 

In theory, an AI with sufficient sophistication could make human agents all but unnecessary, but for the foreseeable future, AI will usually work alongside its human colleagues, as well as providing self-service options through a chatbot / voicebot interface.

 

Despite a low current use of AI across industries (around 20% in the UK and US), there is widespread interest in implementing this solution, with 35% of respondents intending to implement AI within 12 months. While these figures are probably overly ambitious, it does show real interest from the contact centre industry.

 

There are numerous use cases for AI in contact centres, and these are growing all of the time. In order to structure this report, we have chosen four wide areas in which AI is actually helping customer contact now:

  1. Self-Service
  2. Assisted Service
  3. Interaction Analytics
  4. Robotic Process Automation and AI.

There can often be overlap between these areas, for example when a self-service interaction is passed to an agent, who then hands off to robotic process automation.

 

Perhaps the most popular current use of AI in the customer contact environment is in handling digital enquiries, where web chats generally take far longer than phone calls (due to agent multitasking, and typing time) and some email response rates can still be measured in days.

 

Whereas only 5% of web chats had any automation involved in 2015, this has grown to over 20%, mainly as a result of initial handling by automated chatbots which may then hand off to live agents where appropriate.

 

Our survey respondents generally do not believe that AI will replace agents: although 32% agreed to some extent that this would be the case, 68% disagreed. Respondents from large 200+ seat contact centres were more likely to feel that AI would replace human agents, with those in small and medium operations doubting that this would be the case. However, it is worth noting that the belief that AI will replace agents has strengthened over the past few years.

 

Unanimity was found when the question was asked as to whether AI would support human agents, with all respondents agreeing or strongly agreeing that this would be the case, reducing risk, speeding up responses and providing customers with higher quality resolutions.

 

It’s our view that people call people not necessarily because they want to hear a friendly voice, or that they’re Luddites who won’t countenance automation, but because they’ve found through experience that this is the most effective way of making sure their issue is resolved.

 

So while AI-enabled automation will handle much of the simple work, customers will still seek out a live channel for complex or emotional interactions: probably voice, but perhaps digital or video too, as customer confidence in these channels builds up.

 

Yet even here, AI will be playing a part, identifying the customer’s intent, gauging their sentiment, and understanding through past experience what the appropriate actions for the agent will be. Over a long period of time, AI will become thoroughly enmeshed in every element of customer interactions: the rise of the robots will be slow, but inexorable.

 

Report contents:

  • AI: Definitions and Terminology
  • Current Use and Future Plans for AI
  • Use Cases for AI in the Contact Centre
  • End-User Question #1: Does AI only really make sense for large contact centres?
  • Web Self-Service and Chatbots
  • IVR, Speech Recognition and Voicebots
  • Email Assistance and Automation
  • Digital Interaction Assistance
  • Voice Interaction Assistance
  • Sentiment Analysis
  • Predictive / Intelligent Routing
  • AI & Remote Working
  • End-User Question #2: How can AI help with remote working?
  • Robotic Process Automation (RPA) & AI
  • Interaction Analytics
  • Discovery
  • Customer Journey Analytics
  • Identity Verification and Fraud Reduction
  • Workforce Optimisation
  • Real-Time Analytics
  • Improving Routing and Outcomes
  • AI and CX Metrics
  • Implementing and Using AI
  • End-User Question #3: How can AI best be used for a quick win? Where can ROI be found?
  • Initial Actions in an AI Project
  • End-User Question #4: What are the steps we need to take to use AI in our contact centre? Where would be the best place to start?
  • Knowledge Management
  • End-User Question #5: How much initial and ongoing effort/resource will AI require? Do we need a dedicated AI professional to keep everything running?
  • Agent Replacement or Augmentation?
  • Customer Opinions of AI
  • Making AI a success and avoiding pitfalls
  • End-User Question #6: Is there anything that successful AI implementations / projects have in common? Any pitfalls to avoid?
  • The View from CX Decision-Makers
  • The Future Role of AI in the Contact Centre

 

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