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Zen office expands the use of artificial intelligence (AI) across its entire customer experience (CX) platform with the release today of a series of new features that the company is branding as Zendesk AI.
New features in Zendesk AI include advanced bots to handle customer inquiries across multiple industries. Customer service agents will now also have AI-powered assistance in responding to inquiries. Additionally, the system incorporates intelligent triage capabilities that use sentiment analysis and intent detection to help route requests correctly.
While many features of Zendesk AI have been developed by the company’s own teams, new services have also benefited from a healthy dose of Generative AI through a partnership with Open AI. The generative AI component will integrate into the Zendesk AI suite, helping to generate responses and summarize content.
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“We believe we need to make AI easy to understand and use and accessible to everyone,” Cristina Fonseca, head of AI at Zendesk, told VentureBeat.
What generative AI adds to Zendesk
Zendesk was no stranger to AI before its partnership with OpenAI.
Zendesk took a big step into AI in 2021 with the acquisition of a Portugal-based startup Cleverly AI, where Fonseca was previously CEO. In September 2022, Zendesk announced a major update integrating Cleverly AI technology to help speed up customer service responses. Fonseca said today’s Zendesk AI release is an evolution of what the company announced in September 2022, which was specifically aimed at the retail industry. She noted that the new version is available for a wider group of customers.
Zendesk has offered bot capabilities for a while, but Fonseca said OpenAI’s generative AI foundation has greatly expanded those capabilities.
“We believe software should be smart and plug-and-play, and for most bots to work, you need to spend a lot of time training them,” she said. “This is one of the main features we’re launching now – with pre-trained bots that already understand customers.”
Generative AI will also help power a revamped feature set for increased customer service agent productivity. Zendesk AI uses technology from OpenAI to support summation and sentiment analysis for requests which, in turn, helps agents respond efficiently. The ability to help agents create responses is also part of the new update.
Why Generative AI Alone Isn’t Enough for CX
Fonseca pointed out that while Zendesk AI uses OpenAI’s generative AI, it doesn’t abandon its Cleverly AI roots.
Intelligent triage, for example, is a fundamental element that the product uses and was developed by Cleverly AI to understand customer intent, sentiment, and language in order to direct a request appropriately. For this system, Zendesk has its own proprietary models that were trained on Zendesk data. Fonseca said these models understand customer service because they were specifically trained on customer service data and offer a high degree of accuracy.
“The way we see (OpenAI’s generative AI) is basically a tool to help us accelerate things that were already in the roadmap and make a ton of sense to add to our product suite,” said said Fonseca.
As an example, she noted that Zendesk is developing its own approach to suggesting new answers to customer service agents, as well as creating content for a knowledge base on different issues. Without OpenAI, she said the draft content Zendesk was able to generate wasn’t quite polished. Now, with OpenAI integration, data from Zendesk can be used to generate well-written answers and knowledge base articles.
“We try to take advantage of OpenAI and large language models (LLM) to help us perfect everything we do, in addition to the content,” she said.
With all the power that AI brings to Zendesk and its users, Fonseca cautioned that it’s important to realize that AI can’t and shouldn’t do everything when it comes to customer experience. She noted that CX is complex and includes workflows — and sometimes systems — that aren’t built into Zendesk.
“I think the first thing we should do for our customers is help them understand what should be automated and what shouldn’t,” she said. “Because if something can’t be automated, there’s no point trying to get a bot to talk to a customer if the bot can’t add value.”
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