How Generative AI is changing the world of contact centres – interview with Bora Wiemann

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Bora Wiemann is Head of Digital CX at Team Global Express and Industry Lecturer in AI Strategy at RMIT University. We interviewed Bora about how Generative AI (“GenAI”) is changing the world of contact centres.

What would you say are the top ways GenAI is making contact centre agents’ jobs better/easier?

The biggest core benefits for agents are that Generative AI can:

  • instantly summarise calls, significantly reducing the dreaded post call documentation
  • provide pre-crafted responses in a tone which matches the agent and the context, and
  • suggest next best actions.

Over time we’ll see GenAI play more of a role in enriching the training experience with interactive conversation simulations. It will be able to assess agent performance in real-time and suggest micro-trainings to upskill in the moment.

Think of it as having an experienced agent sitting next to you, helping not only during a call or chat, but even afterwards, providing helpful coaching tips and stress management techniques.

How is GenAI enhancing the role of the QA department?

GenAI provides the ability to analyse and report across massive amounts of data. The two areas I’d highlight are:

  • QA teams can create, review and edit visually appealing insights in under an hour, replacing reports that are currently only compiled on a weekly or monthly basis due to manual effort.
  • GenAI has deep forecasting and anomaly detection capabilities. This can enable quick testing of scenarios for potential impacts, such as changes in team structure, adding new products or technologies. Planning is therefore faster and more precise. GenAI can also spot anomalies and monitor them in real-time – examples are collection of unusual customer data by an agent; attempted data breaches disguised across multiple calls; or a spike in uncommon inquiry types or terminology used by callers, which might lead to a review of scripts.

How do you see organisational structures in contact centres changing as a result of GenAI?

Contact centres are struggling to leverage new technology. Vendors tell me that the majority of their clients use barely 40% of available capabilities and that is before GenAI comes into play. Those that embrace the breadth of the latest AI capabilities will soon start to outperform competitors by a significant margin, as it really is such a powerful tool.

Hence, I see the need for Technical Director and Advisor roles as critical in bridging the gap between available technology and legacy operations. 

It’s just unrealistic to expect a Head of Contact Centre to know and be able to manage the constantly shifting technology landscape on their own, while IT managers are commonly not contact centre specialists.

A new role to watch, specific to the GenAI space, is the “Prompt Engineer” – effectively a translator between the business and GenAI tech to elicit the best answers. If you don’t know how to “talk” to GenAI, you might get a correct sounding answer which is in fact not right for what you wanted.

All the existing AI-related roles will become more in demand, from engineers to data scientists and QA analysts.

Moving beyond the tech roles, the implications for your agents and the supporting structure are immense. With AI eliminating simple inquiries, collecting key information and even preparing potential answers and next steps, agents are left to handle the challenging and potentially more emotional or stressful inquiries. Additionally, GenAI doesn’t always get it right so agents need to be always alert to potentially erroneous outputs. In this environment, managers have to be aware that agents are dealing with a higher cognitive load and less downtime – all up, a much more demanding job.

This means agents will require more training, resilience, and support and likely more breaks or slower paced activities to avoid burn out. On the other hand, these “super agents” can be leveraged to help design better customer experiences, more than is currently the practice in many contact centres.

In short, the new contact centre is a high-performance team, which comes with a requisite investment in high quality “members & components” and better maintenance.

If a WFM manager was making a business case to trial GenAI, what are some of the benefits or use cases that could be highlighted?

There are a range of opportunities for a WFM manager to trial GenAI. I’d suggest starting with something as simple as creating faster and better communications, training and standard operating procedures for agents. GenAI can have the same impact as adding an FTE in the internal comms or training team.

Investing in forecasting and behaviour anomaly detection is interesting but harder to do. One example referenced in Simon Kriss’s best-seller, The AI empowered Customer Experience – imagine the WFM function could predict employee turnover, so you could intervene with strategies to keep high performers or implement backups. These are very new ideas so perhaps for tech trailblazers only for now!

How can a contact centre operations leader “partner” with GenAI to uplift performance?

As the operational leader, I’d start partnering with GenAI to improve comms, then move on to use cases such as summarising insights, creating scenarios e.g. for crisis management, and then work on strategy options and planning. I believe most managers are blissfully unaware how much GenAI can accelerate this part of their work. GenAI is amazing to start with insights, dig deeper, create scenarios, solutions and then even help to create the strategy decks and budget requests. With the help of GenAI, a 1-day workshop on strategy could create fully fledged plans & slides/documents instead of just a bunch of ideas to explore. And if you need someone to help facilitate a workshop, I believe Matchboard has some recommendations!

What level of adoption of GenAI are you seeing in the Australian contact centre industry?

This space is still very fresh and even overseas it’s only the minority of organisations that have GenAI in production. The one use case everyone talks about is After Call Work summarisation and I recommend everyone gives it a try.

Overall, my concern for the Australian contact centre industry is the under-investment in tech resources to explore this new AI space. Many centres are focused on running lean and are “technology conservative”, with little appetite to experiment and automate. Contact centres traditionally have a fear of getting things wrong and GenAI requires experimentation, iterations and tuning.

Last updated on: August 29, 2023