USING AI TO AUGMENT
Contact centers look to advance automation , including the use of artificial intelligence ( AI ) to support agents and customers .
However , as this technology rapidly evolves , integrating it into the contact center ’ s existing systems - while ensuring a smooth transition for the agents - can be complex and resource intensive .
Despite this , decision-makers are still lured in by the notion that AI will be a game changer in lowering operational expenditures through reduced agent counts .
As such , many contact centers are rushing to adopt AI applications , including standalone and self-service channels .
HIGH AGENT ATTRITION IS ONE OF THE BIGGEST CHALLENGES CONTACT CENTERS FACE TODAY .
This is a false economy .
While AI can help free up agents ’ time , more complex customer inquiries still require a level of personalized service . And that agents have access to complex and varied business information and systems .
So , offloading the “ easy stuff ” onto AI doesn ’ t equate with simplifying the agent ' s job and reducing training requirements . In fact , it is the opposite .
AI today has impressive capabilities to handle basic interactions but is not ready for long-tail applications when a customer goes off-script . This is why when it comes to troubleshooting issues , many customers still prefer human-to-human interactions over automated responses and AI-driven self-help services .
With Conversational AI , the customer often has to input information into the AI application in order to resolve the issue via self-service . But if the AI hasn ’ t been trained on how to answer the question , it will fail just as assuredly as an agent .
However , when used strategically , contact center AI applications can analyze conversations to guide agents to say the right thing at the right time . As the data sets grow , AI-based guidance will become more accurate , provide agents with more confidence and ensure customer experience consistency .
Using AI to help the agent doesn ’ t reduce interaction complexity . Instead , what it does do is reduce the training needs of the agent by guiding them interactively through the details of the resolution process .
Similarly , AI-driven bots can also be used to automate some of the agent ’ s workflows , such as having bots handle tasks and send messages to other agents , supervisors , and customers .
One promising use case is seamlessly integrating a virtual agent assistant application with AI and a knowledge base into an agent ’ s contact center workspace . AI can augment the agent ’ s capabilities and provide an effective assistance experience for agents , improving productivity , and with faster resolution for customers .
Without a doubt , as we continue to move into the world of digital CX , the agent ’ s job becomes more challenging . There is more data being generated and more channels to manage to meet customers where they are . To be effective , agents need to be provided with the right tools .
Contact center experts agree that we are still in the early stages of AI , and as such we need to set realistic expectations by deploying it narrowly , not organization-wide . The focus should be on the needs of the contact center and their customers , and the AI applications that can effectively address those specific needs .
IMPACTFUL AI APPLICATION INTEGRATIONS
While cost savings are seen to be the primary benefit of deploying AI applications , customers still expect a personal , human-to-human experience .
Therefore , the best short-term ROI will come from supporting the agent ’ s performance . Contact center leaders and IT decision-makers need to think in terms of how AI applications help agents improve CX for today ’ s digital expectations .
AGENT EXPERIENCE
Here are three forms of AI application integrations that will improve the agent experience and , in turn , improve CX and the bottom line .
1 . Deploy a Unified Agent Desktop
As AI is still new for contact centers , IT leaders need to view it as more than just a way to automate operations .
Instead , the focus should be on AI applications that enhance the agent experience by automating repetitive tasks . Also , by providing critical intelligence at the precise time when it can make the biggest CX impact .
Advancing the agent desktop experience requires a level of customization that supports seamless integration with all your existing tools and applications .
AI represents new capabilities , and your agent desktop should have enough flexibility to support the AI applications you ’ ve selected . As AI use cases grow in the contact center , so will the number of applications and integrations .
2 . Shorten the Learning Curve for Agents
Increasing speed to competency is a key benefit of AI for overall contact center operations . Agent training is a great use case for AI applications . They can help agents upskill in less time and more effectively than with other learning tools . AI is better at pattern recognition than humans and can identify which behaviors produce the best outcomes for each specific situation .
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