If you asked some C-suite executives or tech leaders, they might have you believe AI contact center solutions mean a room full of robots that have taken over on the customer service front, rendering human agents all but useless.
Such visions, ambitious as they might seem, are usually cooked up by big thinkers who are far removed from a contact center’s day-to-day operations. In reality, this picture couldn’t be further from the truth.
The truth about AI in the contact center is that despite its exciting and promising capabilities—and there are many of them—it cannot and does not replace the capabilities of living, breathing agents. Instead, AI in the contact center is at its most effective when it’s used in a complementary fashion with human agents, to enhance their output rather than attempting to take their place.
What’s more, the amount of money spent on research, development, and deployment of AI continues to rise. According to a study by Gartner, between 2018 and 2019 the number of organizations that use AI grew from 4% to 14%. Across customer care especially there is growing pressure for AI applications because of the seamlessness it provides.
The trends in AI contact center solutions fall into four broad categories with many practical applications:
- Agent enhancement
- Aggregation of data
- Accelerated decision making
Let’s have a look at the top 4 AI contact center solutions trends. For more details, download our free AI ebook here.
What are the New Trends for AI Contact Center Solutions?
AI-powered virtual assistants can leverage CRM integrations and machine learning to mimic live agent-customer interactions nearly flawlessly while becoming smarter every time.
Accurate and automated data collection that’s actionable
Another practical application for AI in the contact center is task automation. The possibilities are endless here because larger amounts of data mean more accurate learning for AI applications. But, it’s not just about large quantities of data, it’s also about the quality of that data.
The more accurate data is the more informed your AI tools can be in their presentation and predictive analysis. So, before moving to automate tasks in the contact center it’s important to organize the data that’s necessary to carry out those tasks you’re looking to automate first.
For instance, when using AI-powered speech analytics for call transcription and calibration, you need to program what keywords to look for and also make sure instructions for where to store and how to populate reports are input.
On the other hand, AI contact center solutions are being deployed in a conversational IVR use case to initiate SMS conversations based on programmable triggers to offer customers the option to jump out of the call queue and resolve issues digitally.
Aggregation of data
AI is helping contact center managers to refine business processes and create more intuitive workflows. Administrative work is time-consuming. With more data sets to use AI can move beyond rote manual tasks. Form filling, report generation, post-call documentation, lead generation, and even cross-selling can all be done via AI-enabled systems to improve service agent productivity and streamline customer experience via faster data collection upfront.
Customer care processes of issue discovery, analysis, issue resolution, implementation, and quality control can be monitored and carried out by AI contact center solutions, too.
Consider static agent scripts for instance. With the use of call recording and speech analytics,
suggestions can be made in the script in real-time on the agent screen based on customer keyword triggers.
This helps prepare agents for more complex customer calls. It also lets them focus on the results of the automated processes and employ their uniquely human skills to build upon that work and improve customer satisfaction.
Accelerated decision making
Instead of making decisions on the fly based on one-off transactional interactions, AI contact center solutions can be deployed to help recognize patterns in everything from customer issue types to inbound volume to campaign success and even channel traffic.
For more practical applications of AI in the contact center, download our free ebook here.