Voice tech makes inroads in the enterprise

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Some good news, bad news for voice technology partisans in the workplace: The bad news is that the dream of a voice assistant in every conference room and on every desk hasn’t come to pass. The good news is that voice technology is still having an impact in business, just outside of white-collar workplaces.

Voice assistants have never taken hold in the office. In 2017, Amazon announced Alexa for Business. In the official announcement, the company outlined use cases like starting meetings in conference rooms or asking for information around the office. While Amazon hasn’t released detailed stats on Alexa for Business adoption, even Amazon partners haven’t all jumped in. WeWork paused its partnership, and Ajoy Krishnamoorthy of Acumatica said they have seen concerns around security. And this was all before offices became a place that sat empty while workers stayed home.

Voice technology has seen adoption in verticals such as farming, where companies like AgVoice, founded by farm owner and technologist Bruce Rasa, uses voice technology to improve data management. It claims to have a 50% improvement in performance.

Voice assistants are making warehouse work more efficient, as well. While voice picking has been around for decades, improvements in speech recognition and NLU (natural-language understanding) technology have increased the effectiveness and the uptake of voice.

In retail, you can’t get any bigger adoption than Wal-Mart, and it is likewise bringing a voice assistant into its stores via the Ask Sam voice app. The app is a voice-driven tool for employees that brings together information like employee schedules, stock information, and even recipes. Wal-Mart says that this keeps employees on the floor, instead of needing to go find a computer to look up information.

We see, then, that there are fields where voice technology is making an impact, and we haven’t even touched on hospitality or the medical field. But what about back in the enterprise? In many ways, voice assistants didn’t revolutionize the enterprise because there was a solution but not a problem. The dream of asking Alexa for sales numbers isn’t that useful when you have your CRM open in the browser on your laptop all day.

Yet voice technology is still having a major impact on the enterprise, just not packaged as an assistant. Companies like Chorus.ai and Gong are using speech recognition and natural language understanding to give sales teams insights into their performance, with significant traction, including a $2.2 billion valuation for Gong.

Customer support is another domain in which voice technology is having an impact on the enterprise bottom line. Google continues to invest in contact center voice technology via Dialogflow and its Contact Center AI. Its virtual agent technology is indeed an assistant of sorts, just one narrowly scoped for customer support, with an eye towards helping customers self-serve their problems and leave humans to handle the thornier requests.

While NLU and speech recognition technology became good enough to enable smart assistants, these smart assistants and the competition between companies like Google, Amazon, Microsoft, and Apple, in turn improved NLU, speech recognition, and semantic understanding technologies.

Tech that a few years ago was only available to companies with millions upon millions of dollars to funnel into machine learning efforts is now available to everyone to integrate directly or via SaaS. While we aren’t seeing voice assistants in conference rooms, we are seeing the impact that they have had when new products that leverage NLU or voice recognition reduce customer support costs, make farm work easier, or provide coaching for revenue teams.

For most, integrating voice and NLU is an iterative process. Customer support is often the best place to start as companies are likely to see an immediate reduction in costs when customers find their own answers to their questions without reaching out to a human. Another solid starting point is implementing sales tools like Chorus.ai or Gong, which will bring in more revenue. Successful projects focus on the areas where voice and NLU can make improvements to processes that are already in place, parlaying early wins to further investments and expansion down the line.

Dustin Coates is Product and GTM Manager at Algolia, co-host of the VUX World podcast, and author of Voice Applications for Alexa and Google Assistant.


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