Why Research Matters for AI in the Contact Center and CX Operations

Just a few years ago, many considered AI an experiment. It was a technology with great promise but had yet to yield real, measurable business results no matter how impressive it might appear on paper.

Today, of course, AI is at work across industries and use cases—including in customer service and contact centers—to streamline workflows and provide employee efficiency.

The problem, however, is that many AI deployments are still deployed as if they’re experiments.

In fact, a recent MIT study found that 95 percent of the Generative AI projects they inspected either never went beyond a pilot program or never produced positive P&L numbers.

The study found that these GenAI deployments failed to generate revenue or savings at the enterprise level because—among other reasons—they couldn’t align with day-to-day operations and business goals.

In other words, their AI experiments failed.

When it comes to customer service, contact centers, and improving customer experience, your company should know that the AI tools in which you’re investing are proven solutions and not experiments.

The experiments should happen long before AI is implemented into business operations, which is the purpose of Verint Da Vinci Labs—where a team of data scientists looks at ways to improve the future of customer service, contact center and employee efficiency, as well as reaches for AI breakthroughs.

In addition to pushing technology forward, the Verint Da Vinci research team, led by Verint Chief Data Scientist Dr. Ian Beaver, Ph. D., ensures that Verint solutions employ the best processes, AI models, and data capabilities available.

They drive the research-to-product pipeline of Verint Da Vinci and Verint Open Platform by focusing on improving our AI and machine learning capabilities.

This means that Verint customers aren’t buying something that’s going to fall into that group of failed pilots in the MIT study. Verint Labs features a team of data and AI scientists actively collaborating with customers, partners, external research organizations and universities.

Their published papers cover a wide range of scientific areas with the end goal of delivering better business outcomes and improving the customer experience.

This research has empowered Verint to combine the best of commercial, open source, and proprietary AI within Verint bots and applications from the core of the platform. This open approach means that all bots are powered by the best available AI models for their specific task.

Verint Da Vinci AI is delivered through specialized bots. We build, train, and embed AI models once and they can benefit multiple specialized bots. These bots are then trained on your customer data, so they are highly accurate and effective to deliver significant ROI.

Verint’s research takes the risk out of AI investment because, again, the experiments happen far upstream of the deployment of the technology.

For example, if a new AI model is released that would work better for your company, our data scientists and engineers can fold that technology into your solution without interruption to your operations. Your internal teams aren’t disrupted by these sorts of changes, and you can rest assured that Verint is keeping pace with the latest in AI.

Here are some of the topics our team of data scientists has recently tackled:

• How to use linguistic markers to detect deceptive conversations and stop contact center fraud.
• How to improve speech recognition performance by overcoming problems presented by speech enhancement.
• A look at a deep-learning speech enhancement architecture in order to optimize hearing aid performance and speech recognition
• An investigation into speech emotion recognition and its capabilities.

To see more Verint research and learn more about our researchers, visit our Verint Da Vinci AI Research page.