Less than ten years ago, Google pioneered the customer service AI market with the launch of the Google Contact Center AI Suite.
That suite featured groundbreaking conversational AI, agent assist, and conversational intelligence tools that many CCaaS providers used to augment their platforms.
But as the pace of innovation around AI and automation accelerated, customers wanted to adopt new AI capabilities from Google more quickly, without waiting for third-party developers to add these features into their product roadmaps months or even years later. In other words, they wanted an end-to-end platform from Google.
Answering their call, Google released a fully-fledged CCaaS solution: Contact Center AI Platform.
Immediately, it captured attention for its mobile-first design, security features, and – most notably – native AI.
Indeed, AI is baked into the heart of the platform, and thanks to its cloud-native foundation, Google has continued adding cutting-edge AI capabilities throughout 2023.
But, before diving deep into these new-wave features, consider what makes the Google CCaaS platform “truly AI-centric”?
The answer is two-fold: its CRM-centric design, which unifies customer data across the business, and the core AI models that take advantage of this advanced architecture.
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For most CCaaS vendors, CRM integrations rely on data replication and synchronization at 30–60-minute intervals, which impacts both the timeliness of reporting and the completeness of data upon which AI can learn and operate.
Yet, Google is not building on these old integrations. Instead, it introduced a CCaaS platform with a CRM-centric design that enables powerful, real-time bidirectional data flows between the platforms.
As such, contact center AI models can operate on more complete, structured organizational data. Moreover, the contact center can funnel more of the insights it generates – via Google’s conversational intelligence tools - back through to the CRM solution.
Of course, this drives new customer insight into the broader business. But, most crucially, it shows how Google both uses data sets to improve AI and AI to improve data sets. That powerful cycle sets the contact center up for long-term success with AI.
The AI Models at the Heart of the Google Contact Center AI Platform
During the launch of its Contact Center AI Platform last year, Google isolated three cornerstone AI innovations that would benefit from its superior data flow. These are:
1. CCAI Insights – A conversational intelligence tool that lifts insights from all conversations on the platform – whether conducted by a live or virtual agent. Those insights cover contact reasons, customer sentiment, and possible compliance risks – amongst others.
2. Agent Assist – This offers agents step-by-step support during live calls, lifting insights from the knowledge base and CRM while even auto-generating ready-to-send customer responses across digital channels. (More on this later).
3. Virtual Agents – Dialogflow is Google’s Magic Quadrant leading conversational AI platform and sits inside the CCAI platform. There, it enables conversational self-service across voice and digital channels, alongside smooth handoffs to live agents for more complex queries.
Yet, there are many more AI models that contact centers can choose to leverage. For instance, its predictive routing engine is AI- and ML-based, channeling contacts to particular agents – based on employee data and CRM information – to maximize specific outcomes.
With this innovation, contact centers can evolve from rules-driven, skills-based routing while improving central customer experience metrics.
