Contact Centre AI: The Promise, the Reality and the Future


A picture of robots and AI

Sam Bader, on behalf of Genesys, discusses the current capabilities of contact centre artificial intelligence (AI) and its future within the industry.

Companies across all industries are experimenting with a suite of AI solutions in the contact centre to improve customer care, increase operational efficiency and enhance security. And that experimentation will continue to grow. In fact, MIT found that by the end of 2020, 97% of large companies surveyed will deploy AI.

In a recent webinar, Genesys sat down with Claire Beatty, a leading analyst from MIT, and Aarde Cosseboom from TechStyle to learn about the driving forces behind AI adoption, current AI use cases, challenges and trends. It also explores how the COVID-19 pandemic has changed the trajectory of AI in the contact centre.

Here are some of the highlights from the event.

How to Deliver Personalised Customer Experiences at Scale

In the global report, MIT surveyed over 1,000 senior executives of leading brands to identify how they’re using AI today — and how they plan to use it in the future.

Upon closer inspection, it became clear that AI is playing a variety of different roles across all business sectors. One of the top use cases is customer care efforts.

TechStyle, a leader in online retailing, implemented AI to stand apart from the competition.

With five million members, six million phone calls per year and three million chats per year, communication is core to its business. And the company leverages AI to help with that communication back and forth.

By integrating AI, TechStyle:

  • Reduced average handle time by 45 seconds
  • Saved $1.1 million in the first year in operations costs
  • Achieved a score of 92% in its member satisfaction survey

Contact centre AI can give agents the ability to go beyond efficiency and effectiveness to be more empathetic and earn loyalty through stronger connections and better results.

By leveraging insights from historical, third-party and behavioural data, AI unifies and filters this data to provide agents with the complete context of the customer. It then turns these mounds of data into real-time insights and actions.

Overcoming Contact Centre AI Issues

While AI is deployed widely across industries, MIT found that implementing and scaling the technology is difficult for many organisations.

Existing technology limitations, process and culture change, and talent shortages are all constraints to using AI.

Here’s how a good AI platform overcomes common implementation challenges.

  • Data quality or availability issues: By easy integrations with CRM systems, native AI capabilities and machine learning algorithms, as well as third-party technologies.
  • Unable to demonstrate business value with AI: Your vendor should offer proof of concepts that show business value quickly.
  • Shortage of AI developers/data scientists: Your AI platform should allow you to easily build workflows, quickly create bots and easily integrate with third-party technology and data.

This blog post has been re-published by kind permission of Genesys – View the original post

To find out more about Genesys, visit their website.

About Genesys

Genesys Genesys powers more than 25 billion of the worlds best customer experiences each year. Over 10,000 companies in more than 100 countries trust our #1 customer experience platform to drive great business outcomes and create lasting relationships. Combining the best of technology and human ingenuity, we build solutions that mirror natural communication and work the way you think.

Read other posts by Genesys

Call Centre Helper is not responsible for the content of these guest blog posts. The opinions expressed in this article are those of the author, and do not necessarily reflect those of Call Centre Helper.

Published On: 21st Aug 2020 - Last modified: 26th Aug 2020
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