Man vs machine

Botman vs. Superagent: Man vs. machine in the future of customer experience


The march of the machines

How will machine learning change the contact centre?

As machines get smarter, should we fear for our jobs? Our new whitepaper looks at how far machine-learning has come and how it can be used to make both our jobs, and customer experience, better.

With a combination of self-service technologies, chatbots and machine learning at both the customer and advisor interface, the fabric of the contact centre is changing. This means the skills we need are changing from rules based, constrained and scripted environments, to more empowered, empathetic and creative ones.

Machine learning today

We are largely still in the first generation, formative years of machine learning. Most of the applications of machine learning we are familiar with today are based on pattern recognition (algorithms), used by Google, Netflix and Amazon for example. These algorithms can reason over narrowly defined, structured problems, but have only limited learning capabilities.

A second generation of machine learning has now started to emerge. It learns from large sets of machine readable data, usually in specific areas, such as playing Go, or diagnosing cancer, and is sometimes referred to as “cognitive machine learning”. As with the first generation of machine learning, it is only as good as the data available to it.

The third generation future of machine learning is likely to be closer to artificial general intelligence (“AGI”). AGI will be able to both learn and adapt to context, but it is still unlikely to be able to do things like abstract reasoning.

How will machine learning change the contact centre?

The contact centre has been at the forefront of the march of automation for many years. Digital customer care, self-service technologies and the rise of the app have already pushed a lot of the simple, repetitive stuff out of human contact queues.

To examine the effect of machine learning on the future development of the contact centre we need to consider five critical factors:

  1. Technical feasibility
  2. Cost of development and deployment
  3. Availability of skills in the labour market
  4. The economic benefits
  5. Regulatory and social acceptance 

Download our new whitepaper to find out more about machine learning, and the impact it could have on your contact centres and customer experience.

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