Introduction
Infosys Cortex, an AI-based Contact center platform, is ever-evolving to revolutionize customer services. Since the introduction of GPT models, it has enhanced the experience of contact center personas viz recruiter, trainer, trainee, agent, QA tester, customer, etc. by bringing in Generative AI features. Let us see a glimpse of it in this blog.
The Combo of Contact Centre and Generative AI
Generative AI’s popularity is increasing with the masses day by day. Enterprises have also become aware of it and have started incorporating Generative AI in their offerings or solutions across various domains. It has even pervaded the Contact center industry and we should be able to see perceivable changes soon. Hyper scalers are providing relevant services to build Generative AI-based contact centers. Certain companies are offering specialized Generative AI-based capabilities in this regard.
Conversational AI agents play an integral role in contact centers these days. Its evolution from rule-based to AI to Generative AI is also one of the reasons, for Generative AI-based contact centers coming into existence, apart from the availability of various related plugins.
How can Infosys Cortex Provide a Positive Lift to Contact Center Persona Experiences?
There are different personas in a contact center and let us see how the latest Generative AI-enabled Infosys Cortex will impact them.
a) Recruiter
- AI-Assisted Hiring
The platform provides a digital interface to capture responses from candidates on various configurable interview questions related to soft skills, behavioral aspects, etc. which can then be evaluated through a combination of Speech AI (STT) and Generative AI technologies. It helps the recruiters to do the initial screening of candidates.
b) Trainer
- Training Content Generation
The platform helps create realistic contact center audio conversations on various situations and customer personas, which can be used for training. It does so by first generating the conversation on a provided scenario, which after review is used to create audio conversation through the use of Speech AI (TTS). It also generates FAQ’s on these calls to be used by the trainer to evaluate how well the trainees understand the courses.
- Automated Evaluation
The platform helps to do an automated evaluation of soft skills, domain, behavioral, and compliance aspects from trainee’s conversations and responses captured in a simulated environment by using Speech AI (STT) and Generative AI technologies.
c) Trainee
- Simulated Learning
The platform provides a simulated learning environment that allows trainees to practice their skills in a completely immersive environment, thus ensuring readiness for the actual job. It provides a no-code configuration-driven studio to create any combination of scenarios (e.g., troubleshooting, plan upgrade, etc.) and personas (age, gender, location, language, sentiment, etc.) to practice the conversation on the agent desktop with support for enterprise integrations and proactive/on-demand assistance. For e.g., trainees can easily practice conversation on “Angry Adam calling third time for Wi-Fi connectivity issue”. This acts as a powerful medium for contact center trainees in terms of enhancing their skills and thereby building up their confidence to face real customers.
- Automated Feedback
The platform provides automated Generative AI-driven feedback on the trainee’s performance in the simulated learning environment so that the trainee can work on the improvements and thereby give better performance.
d) Agent
- Proactive Assistance
The platform provides proactive assistance through digital nudges on the agent’s desktop by listening to the conversation between the agent and customer and recommending actions by analyzing those conversations. These recommendations include Generative AI-driven dynamic guided workflows, insights, next-best actions, etc.
- On-Demand Assistance
The platform provides a conversational AI interface for agents to search for enterprise knowledge which makes use of RAG to extract/generate the responses through integration with enterprise knowledge systems.
- Automated Call Disposition
The platform provides an automated call summary along with issue, cause, and resolution details on call completion which can be reviewed and submitted by the agent, hence saving time and effort in preparing these details manually as well as bringing more accuracy to these submissions.
These Generative AI-enabled features help agents equip themselves with the necessary details to address various customer queries, which leads to reduced issue resolution time, faster call handling, and improved productivity.
e) QA Tester & Supervisor
- Conversational Analytics
The platform’s conversational analytics uses Generative AI to focus on deriving values, KPIs, and insights from the conversations. The calls and chats stored in the contact center can be processed to generate value-driven insights across process, engagement, and business. The insights generated are around the sentiment trend, pain points, opportunities, and improvement recommendations. It also automatically provides a summary of key points from conversations. These insights will help the QA and supervisors in performing their roles more effectively.
f) Customer
- Self Service
The platform uses the power of Generative AI in voice/chat-enabled conversational assistants to elevate conversation quality through improved intent detection, response elevation by considering the long-term short-term context, and improved knowledge retrieval through RAG on enterprise knowledge, thereby improving the overall customer experience.
Conclusion
Through these Generative AI features, a contact center solution provider can engage better with a customer by hiring better candidates, providing enhanced training empowering its employees to resolve customer queries accurately, and improving the overall customer experience. This better experience along with improved self-service will leave the customer with a positive feeling. All in all, this is a win-win situation for all the parties involved.
Glossary
- AI – Artificial Intelligence
- GPT – Generative Pre-trained Transformer
- QA – Quality Assurance
- RAG – Retrieval Augmented Generation
- TTS – Text To Speech
- STT – Speech To Text
- KPI – Key Performance Index
- FAQ – Frequently Asked Questions
References
