

As a business grows, it becomes more and more challenging to deliver a quality customer experience (CX) at scale. Automation and autonomous CX addresses this issue by increasing efficiencies and simultaneously eliminating bottlenecks in people-heavy tasks, improving the experience for both agents and customers.
Autonomous CX involves using AI-based technology with self-learning capabilities to serve inbound callers at a contact center. While it is not a highly mature solution, it is considered an advanced form of CX automation that has generated a lot of interest and investment with the potential to transform into a mainstream solution very soon.
In autonomous CX, an intelligent bot efficiently handles end-to-end customer interactions through voice or text. Using machine learning (a subset of AI), autonomous CX independently learns the best practices and grows or adapts its capability profile.
Autonomous CX is characterized by:
Autonomous CX drastically improves the efficiency of contact centers by facilitating the quick handling of cases by agents, thereby enabling them to serve more customers. The typical customer queries are resolved without human intervention, which leads to a quicker mean time to resolution. Agents are then free to attend to complex customer queries providing a more engaging experience.
Autonomous CX is available 24/7 giving customers the flexibility to reach out as per their preferred hours and opening the business to audiences across different time zones.
Once autonomous assistants are implemented, endless call queues, long hold times, unintuitive IVR menus, etc. are eliminated. Oftentimes, customers tend to avoid direct interaction and would rather prefer self-help, which is why autonomous CX is an attractive alternative.
Automation typically involves identifying repetitive tasks across the CX cycle that can be performed without relying on human assistance. Introducing applications that support these tasks will allow customers to quickly progress to the next stage of the engagement cycle.
People are slowly adapting to interactions with automated technologies like voice, chat, and SMS. This intuitive and frictionless experience allows customers to achieve the desired results quickly.
Introducing automation to the digital transformation journey of a business is truly an upgrade and diversification of the customer experience, reducing response times significantly and doing away with the impersonal elements of the process. Additionally, employees appreciate the streamlined communication and the extra time they can utilize to focus more on improving their direct interactions with customers.
It is reasonable to view autonomous CX and CX automation as belonging to the same continuum. However, the subtle differences shouldn’t be overlooked.
Automation is not necessarily autonomous. The two are easily distinguishable by the amount of learning, adaptation, and decision-making that is integrated into the system.
Automation typically involves a well-defined set of parameters that essentially restricts the tasks that can be performed. The decisions or actions taken by an automated system are based on these pre-defined rules.
An autonomous system learns and adapts as the environment around it changes. The data that the autonomous CX system learns and adapts to may be beyond what was initially contemplated during its deployment. It learns and evolves from these incoming data sets, eventually becoming more reliable over time.
Which is better; autonomous CX or CX automation? Understandably, autonomous CX may often be considered superior simply due to the higher complexity involved when it comes to its processing capabilities. However, the answer completely depends on the situation and the problem that needs to be resolved.
If there is a requirement for a highly predictable system that needs to perform the same task repeatedly, CX automation will offer superior value due to its simplicity, easy maintenance, and the need for fewer resources. Autonomous CX, in this case, could result in unnecessary and incorrect learning thereby leading to inaccurate actions.
Autonomous CX is more effective in ever-evolving landscapes where it’s not possible to exhaustively predict all possible conditions ahead of time and requires adaption and learning as the environment and other inputs develop over time.
Because of its evolving and adaptive nature, autonomous CX is self-sufficient and requires no agent intervention. It has the capability to learn and adjust to dynamic environments.
CX automation, on the other hand, follows well-defined criteria dedicated to a specific task, and there are limitations on the CX-related tasks that can be automated, thereby requiring human intervention for the rest of the processes in the CX cycle.
Automation is not something you set up and forget about expecting it to magically handle the entire process on its own nor is it a blanket solution for all CX requirements. Therefore, finding a good balance between CX automation and autonomous CX can improve the overall efficiency of the entire process, creating a positive and frictionless experience for both the agents and the customers.
Parameters | CX Automation | Autonomous CX |
---|---|---|
Automation vs Autonomous | These systems automatically perform repetitive tasks and streamline communication with customers. | These systems self-learn and adapt to dynamic environments that may be beyond what was contemplated during their initial deployment. |
Operation | CX automation is limited to specific tasks and follows pre-determined rules. | It evolves and adapts to the changing environment with the help of an underlying ML framework and sophisticated algorithms. |
Predictability of tasks | Yes | No |
Self-learning capabilities | No | Yes |
Superiority | Effective in cases where a highly predictable system is required to perform the same tasks repeatedly. | Effective where it’s not possible to exhaustively predict all possible conditions ahead of time. |
Human intervention | Partial human intervention is required. | It eliminates the need for human intervention entirely. |
Examples | Chatbots, automated text responses, IVAs for query execution, call queues, auto attendants, etc. | AI-powered live agent assist, AI-based real-time sentiment and customer insights, advanced Intelligent Voice Assistants (IVAs), IVRs, agent augmentation, etc. |
By smartly leveraging Contact Center AI, ML, deep learning, machine vision, and other advanced technologies, the customer service industry is notably progressing from adopting CX automation to autonomous CX.
Talk to our experts about how you can improve your CX.
Prakash Hariharasubramanian, Director & Practice Lead, Intelligent Process Automation (IPA), HGS
Prakash has led various IPA implementations across multiple industry verticals in his tenure of 7 years with HGS. In his role, Prakash develops IPA practice frameworks, creates IPA solutions, and serves as a key automation evangelist for HGS.
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