Big CX News From OpenAI, Google, Salesforce, and Verint

Popular stories from the last week that you may have missed.

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Published: April 8, 2024

Rhys Fisher

Last week saw another busy period for the CX sector.

We had a warning from OpenAI, a CCaaS update from Google, and new features from Salesforce and Verint.

Here are the extracts from some of our most popular news stories over the last seven days.

OpenAI Warns Businesses to Phase Out Voice-Based Authentication, Stalls the Release of Its Voice Cloning Tool

OpenAI has put companies on red alert, warning them that it’s time to move on from voice authentication amid the development of its Voice Engine solution.

Voice Engine is a voice cloning tool that generates natural-sounding speech that “closely resembles” the original speaker.

Now, it’s available in a preview, but OpenAI has chosen to stall the general release in a bid to “bolster societal resilience” against increasingly convincing generative models.

In an unauthored blog post on its website, OpenAI dived deeper into the specifics, noting:

We encourage steps like phasing out voice-based authentication as a security measure for accessing bank accounts and other sensitive information.

The large language model (LLM) pioneer also encouraged businesses to speed up the development and adoption of techniques for tracking the origin of audiovisual content (Read on…).

Google Makes Move to Improve CCaaS Reliability, Announces Auto-QA Solution

During last week’s Enterprise Connect event, Google announced two new additions to its CCaaS solution: the Google Contact Center AI Platform (CCAI-P).

The first is a new multi-region capability that allows enterprises to run the CCAI-P offering automatically and reliably across various global regions and clouds.

In doing so, it offers cross-region failover. That increases resiliency, ensures business continuity, and offers customers “mission-critical uptime”.

Sharing how, in a blog post, Kevin Shatzkamer, MD of ConversationApplied AI Engineering at Google Cloud, and Matthew Clare, Outbound Product Management Lead for CCAI & CX, wrote:

With multi-region support, customers benefit from seamless failover across geo-dispersed Google Cloud regions in the event of a catastrophic regional outage, ensuring that cloud outages never impact critical customer experiences.

Such capabilities are critical as Google aims to accentuate the first of its three CCaaS differentiators (Read on…).

Salesforce Announces New AI Features for MuleSoft, Releases Einstein Copilot for Tableau in Beta

Salesforce has announced new AI-powered features for MuleSoft to pull more data into the Salesforce environment, improve developer productivity, and simplify workflows.

Perhaps most exciting is the Intelligent Document Processing (IDP) capability that “rapidly” extracts and organizes data from documents like PDFs and images.

As IDP integrates with Salesforce Flow, that data may pass across Salesforce Clouds, MuleSoft Anypoint Platform, and MuleSoft RPA.

As a result, it helps to increase cross-app insights, streamline processes, and train AI models embedded across the Salesforce Einstein 1 Platform.

The IDP also comes with ready-made templates for tasks like handling purchase orders, reviewing invoices, and reducing setup time. Meanwhile, users may review AI-generated outputs to ensure accuracy.

In addition, Salesforce has augmented the IDP with Einstein AI to extract data using only natural language commands – eliminating the need for AI model training (Read on…).

Verint Builds a Data Layer Over the Webex Contact Center

Cisco has made the Verint Open Platform’s Data Hub available to its Webex Contact Center customers via the Webex App Hub.

The Data Hub layers over the CCaaS platform – in addition to third-party tools – centralizing behavioral data from every customer conversation.

Whether that data comes from reporting, analytics, survey, quality assurance (QA), or another service-based solution – the data layer pulls it all together and gives it meaning.

Historically, all that data has resided in silos. As a result, limited data becomes useful to contact center leaders.

To bring all the contact center’s behavioral data together, many organizations will have already built a data lake. Yet, that is no stroll in the park.

After all, IT leaders must build adapters, gather data, and normalize it (Read on…).

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