Home News How Premature AI Adoption Can Lead To Customer Frustration, Explains Ravi Kumar Of Cubastion Consulting | News

How Premature AI Adoption Can Lead To Customer Frustration, Explains Ravi Kumar Of Cubastion Consulting | News

by khushahal vishwakarma


In a world where companies are increasingly embracing Artificial Intelligence (AI) to enhance customer service and streamline operations, it’s essential to understand the importance of a solid traditional tech foundation. Premature AI adoption, without a robust infrastructure in place, can lead to customer frustration. Ravi Kumar, Partner Director at Cubastion Consulting, a new age tech solution provider, shed insights on the prerequisites for successful AI integration, its potential benefits, and the critical role of data analytics and data security in establishing a robust tech foundation. 

Q. When you mention that companies should have strong traditional tech support before joining the AI trend, could you elaborate on what you mean by this statement? 

Before embracing AI, it’s essential for companies to have a solid foundation in their traditional technology infrastructure. This means having reliable IT systems, data management, and support structures in place. AI is a powerful tool that relies heavily on data and technology. Without a strong traditional tech support system, organisations may struggle to manage the data and infrastructure required for AI. This can lead to system crashes, inefficiencies, and difficulties in maintaining AI solutions.

Q. Can you provide insights into the tech solutions that should be in place before embracing AI to enhance Customer Relationship Management or Customer Experience? 

Before integrating AI in CX and CRM, companies should have the following in place: 

* Robust Data Management: An organised and well-structured data management system to collect, store, and manage customer data.

* Customer Data Security: Data security measures to protect customer information and ensure compliance with privacy regulations.

* Scalable Infrastructure: IT infrastructure that can handle the increased workload that AI-driven CRM or CX enhancements may require.

* Analytics Tools: Data analytics and reporting tools to extract meaningful insights from customer data.

* Feedback Mechanisms: Mechanisms to capture and analyse customer feedback for continuous improvement.

* Integration Capabilities: Systems that can seamlessly integrate AI components into the existing CRM or CX infrastructure.

Q. How can AI enhance customer experience (CX), and what potential negative impacts should be considered? 

AI can enhance CX in many ways such as: 

* Personalisation: AI can analyse customer data to provide personalised product recommendations and content.

* Efficiency: It can automate routine tasks, reducing response times and improving efficiency.

* Predictive Analysis: AI can predict customer needs and behaviours, enabling proactive service.

* 24/7 Availability: Chatbots and virtual assistants can provide round-the-clock customer support.

And the Potential negative impacts include data privacy concerns, customer resistance to automation, and the risk of bias in AI decision-making. Striking the right balance is crucial. 

Q. In which sector(s) is AI adoption most effective, and where is the demand primarily coming from? 

AI adoption is highly effective across various sectors, but it has seen significant impact and demand in industries such as healthcare (for diagnostics and patient care), finance (for fraud detection and risk assessment), e-commerce (for personalisation and recommendation systems), and manufacturing (for process optimisation and predictive maintenance). We at Cubastion are actively involved in new business projects related to providing AI integration services and building robust data management systems in various industries, including banks, telecom, and the automotive sector. We are working on innovative projects to help these industries improve their operations, customer experiences, and overall performance through enabling their infrastructure and making industry ready for AI technologies and solutions.



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