The AI Revolution in Customer Care

The TransPerfect DataForce team launched their first-ever DataForce Live event, the AI Revolution in Customer Care, hosted by our own Alex Poulis. Joined by IBM’s Senior Product Manager Rachel Liddell, we discussed the ongoing technological transformation taking place in the customer service industry. Here are some key takeaways from the event.

Artificial intelligence (AI) has led to many recent improvements in speech-search technologies.

More specifically, conversational AI has helped create customer service processes that customers actually don’t hate using.

Customer service is a big focus for IBM and their AI portfolio. Watson Assistant, which is part of IBM Watson, started off as a digital chat tool. It has since evolved into a powerful method for creating automatic ways to answer customer questions.

Customer care technology is something every company needs to streamline the customer care process at scale. Companies can no longer rely on FAQ pages to answer customer requests. Today’s customers want direct responses, and they want them quickly.

Technology Improvements Enabling the AI Revolution

1) Computers

The gaming industry has pushed computer technology to progress quickly, and is specifically responsible for graphical processing unit improvements.

Machines are getting increasingly more powerful, processing more data faster, and creating more accurate predictive models. This progress leads to greater strides in AI.

2) Proliferation of Data

Humans are generating much more data than they did just five or ten years ago. In fact, 90% of all data has been generated in the last five years alone and, according to some reports, 2.5 quintillion bytes of data are produced by humans every day.

When a search is entered in Google, it’s not just IBM or similar companies benefiting from that data. All companies want to do cool stuff with that information—such as attract new customers or analyze which market to expand to next.

We’re developing new ways to process and collect data. We’re establishing new types of machine learning algorithms. Computers are progressing, and new machines are being developed based on AI-created models and predictions. Business is changing, and it’s time to adapt.

3) Speech-to-Text Improvements

As more data is collected, systems get smarter and invent better ways to process. This is a result of humans applying their ingenuity to data to find interesting insights and make better predictions.

With speech-to-text, there is more opportunity to train algorithms. As more of this data is collected and processed, companies will have more and more reasons to use it.

Diversity in AI

There are some arguments against using AI because of claims that it lacks diversity. More specifically, speech-to-text’s conversational AI technology is under scrutiny. For example, just like our skin ages, our voices age, too.

Some fear voice assistant data under-represents people over a certain age, which could lead to the user experience not being consistent across demographic groups. Even more so, this becomes critical in cybersecurity (e.g. voice authentication) and healthcare (e.g. voice-based diagnostics).

To overcome these types of challenges, companies like IBM have committed to identifying these inherent biases and finding solutions for them. Companies can ensure data sets are robust and serve all people by including data samples that represent different backgrounds within broad populations.

Customer care is ever evolving thanks to updates in AI. As we’ve said, what we are seeing today is different from what we saw five to ten years ago and will continue to adapt as the technology evolves and improves. As our customers continue to change over time, so will our technology as we seek to stay on par with them and continue to provide the high-level experience they want and deserve.

For more information on TransPerfect’s DataForce and how we can help you improve your customer support, email dataforce@transperfect.com.