In today’s fast-evolving customer experience (CX) landscape, data is often referred to as the “new oil”—a critical resource powering innovation and efficiency.
Nowhere is this truer than in contact centers, where data from customer interactions fuels everything from service delivery to strategic decision-making. With generative AI (gen AI) entering the scene, this data is not just an asset but a requirement. For contact centers, data is the lifeblood that enables artificial intelligence (AI) to deliver real-time, personalized experiences, optimize workflows, and streamline issue resolutions.
But before you jump into implementing gen AI, there’s a key question to address: Is your data ready?
The success of AI initiatives hinges not just on the quantity of data but its quality, accessibility, and structure. Data readiness becomes the foundation for any successful AI deployment, ensuring that your contact center is prepared to harness AI’s full potential. But what exactly is data readiness, and how can you assess whether your contact center has it? Let’s dive deeper…
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What is data readiness?
Data readiness is the state of your organization’s data in terms of quality, quantity, structure, and availability to support AI-driven solutions. In the context of gen AI in contact centers, it refers to having the right kind of structured and unstructured data—voice transcripts, chat logs and customer relationship management (CRM) interactions, etc.—that AI systems can process, learn from, and use to generate intelligent insights or automate workflows.
Think of it like cooking a gourmet meal: You can have the best kitchen equipment (AI tools), but if your ingredients (data) are spoiled or mismanaged, the final dish will be a disaster. The same goes for AI implementation in contact centers — without properly prepared data, even the most advanced gen AI tools can underperform.
What should your data be like for gen AI success?
For gen AI to work effectively in contact centers, the data needs to meet several key criteria:
Exhibit 1: Checklist for data readiness
Source: Everest Group
Stages of data readiness
Understanding where your organization stands in its data readiness journey is key to planning for gen AI. Here are typical stages:
Exhibit 2: Stages of Data Readiness
Source: Everest Group
To identify your state in data readiness, answering the following questions will give you a clear picture of your current state:
Exhibit 3: Questions to identify your current state in data readiness
Source: Everest Group
Tangible steps to improve data readiness
Once you identify your stage, you can follow the below approach to progress toward AI readiness:
Exhibit 4: Tangible steps to improve data readiness
Source: Everest Group
Leveraging technology, automation, and AI to boost data readiness
Automation tools and AI can play a big role in speeding up the data readiness process. For instance:
- Automation for data cleaning: Deploy Robotic Process Automation (RPA) for cleaning and structuring large datasets, eliminating repetitive manual tasks
- AI-based feedback loops: Implement AI to constantly monitor data quality, identifying gaps and correcting inconsistencies in real-time
- Self-learning systems: As your gen AI models evolve, create a feedback mechanism where the AI itself learns from the data it processes, ensuring continuous improvements
Conclusion
Data readiness isn’t a destination—it’s a continuous journey that ensures your contact center is prepared to maximize the potential of gen AI.
Whether you’re in the early stages of organizing your data or already utilizing advanced AI systems, taking steps to improve your data’s quality, accessibility, and contextual richness will dramatically impact your AI’s effectiveness.
As gen AI continues to evolve, ensuring your data is prepared will not only enhance the customer experience, but also drive efficiency and innovation across your contact center operations. Don’t let poor data hold your AI back—start optimizing today!
If you found this blog interesting, check out our blog focusing on Generative AI In Healthcare – A Game Changer Or Another Fad? | Blog – Everest Group (everestgrp.com), which delves deeper into another topic regarding gen AI.
If you have questions or want to discuss CX strategies and solutions, please contact Mohit Kumar or Chhandak Biswas.
