In the first two parts of our AI Maturity blog series, we explored the role of people and processes in fostering AI readiness within modern contact centers. Now, it’s time to address the third pillar of AI Maturity: technology.
To build a future-ready contact center, enterprises need to choose the right tools and platforms to seamlessly integrate AI into their operations, amplify human performance, and deliver unparalleled customer experiences.
Strategic Technology Selection
AI-powered tools, and the automation that they enable, are the backbone of any contact center transformation. But selecting the right technology isn’t just about investing in the latest trends in AI; it’s about finding solutions that align with your organization’s unique goals, workflows, and challenges. Poorly matched tools can result in underutilized investments, frustrated agents, sunk costs, and missed opportunities for improvement. By taking a strategic approach, contact centers can ensure their technology stack drives real value and accelerates their journey toward AI maturity.
Foundations for AI and Automation
To effectively implement AI and automation in contact center operations, organizations need an approach that incorporates the “Crawl, Walk, Run” philosophy we talked about in our blogs on people and processes. Here are some key guiding principles to keep in mind as you deploy increasing levels of automation across your organization:
- Pilot programs: Start with a pilot to test the technology in a controlled environment. Be aware that pilots for AI are typically longer (3-6 months) and require larger sample sizes than other technology trials you may have experienced.
- Phased rollout: Introduce automation incrementally, focusing on high-impact areas first.
- Monitor and optimize: Collect feedback from both agents and customers to refine the system.
With that approach in mind, you can shift your focus to implementing a robust system that can convert unstructured conversational data into actionable insights. These include:
- High-quality input: The accuracy of AI models heavily relies on the quality of data fed into them. Achieving high transcription accuracy is essential to ensure that conversations are captured correctly. This foundational step is critical for training effective AI models that can understand and respond to customer inquiries accurately.
- Custom AI models: Generic public models are often inadequate for contact centers. Organizations should leverage best-in-class, task-specific models tailored to unique business needs, providing superior performance across various use cases. Custom models can be trained on historical data specific to the organization, allowing for more relevant and effective interactions.
- Real-time architecture: For AI applications to be effective, they must operate in real-time with minimal latency, even at enterprise scale. Ensuring seamless performance in large deployments is crucial. This architecture allows for immediate data processing and response generation, enhancing the customer experience by reducing wait times.
- Human-in-the-loop system: A user-friendly interface enables business users to train and fine-tune AI models without requiring technical skills, allowing for a more agile response to changing operational needs. This approach empowers users to adapt AI capabilities to their specific contexts, ensuring that the technology evolves alongside business requirements.
- Data integration: Automated updates of CRM records ensure accuracy in customer data, while real-time data exchange consolidates insights and workflows for immediate use, turning every interaction into a competitive advantage. Effective data integration allows for a holistic view of customer interactions, enabling personalized service and informed decision-making.
Key Considerations When Evaluating AI Tools
When evaluating AI tools and platforms, keep the following factors in mind:
- Operational ease: Choose tools that can grow with your organization and adapt to evolving customer needs. Whether you’re scaling to handle higher call volumes – as over 60% of businesses are anticipating call center volume to continue to increase – or introducing new communication channels, your technology should easily provide the flexibility to meet future demands without costly overhauls. The best AI platforms integrate smoothly with your existing CRM, ticketing, and communication systems. This ensures that agents and supervisors alike can easily access AI-powered insights without toggling between disparate platforms, minimizing disruption and maximizing productivity.
- Ease of use: Tools designed with user experience – and ultimately, customer experience – in mind drive faster adoption and greater ROI. Look for platforms that offer intuitive interfaces, straightforward workflows, and minimal learning curves for agents and supervisors alike. Read part 1 of the AI Maturity series to further understand just how critical it is to consider the experience of your frontline teams.
- Actionable insights and performance measurement: Organizations need a robust system that can go beyond automating tasks to converting unstructured conversational data into meaningful, actionable insights. For example, Cresta’s Conversation Intelligence helps supervisors quickly identify coaching opportunities, while real-time Agent Assist empowers agents with immediate suggestions to improve customer interactions.Additionally, advanced AI tools provide key performance indicators (KPIs) to measure the effectiveness of their platforms, enabling organizations to continuously assess and optimize core capabilities such as response accuracy, resolution times, and customer satisfaction scores.
- Future-proofing capabilities: Selecting an AI platform with future-proofing in mind ensures long-term value. Look for tools that are not only adaptable to current needs but also equipped to handle emerging technologies and trends. Scalable architecture, modular features, and a vendor’s commitment to innovation are essential to maintaining a competitive edge as the contact center landscape evolves.
- Data privacy and security: AI tools must comply with industry standards and regulations to protect sensitive customer data. Robust encryption, access controls, and data anonymization features are essential for maintaining trust and compliance. Look out for companies that are certified and compliant with GDPR standards, HIPAA standards, and more. Read a breakdown of Cresta’s approach to trust and security here.
- Vendor expertise and support: Partner with vendors who understand the unique challenges of contact centers, and who offer the training, resources, and ongoing support needed for successful implementation. In the second part of our series, we dive into the importance of a “Crawl, Walk, Run” approach – ensure that you are selecting a vendor that can guide you through every step of maturing your contact center.
Iterative Implementation for Long-Term Success
AI adoption is an ongoing journey; it doesn’t happen overnight. Following our approach outline above allows organizations to test, refine features based on feedback, and scale confidently. Iterative implementation minimizes risks and ensures alignment with operational needs.
Preparing for the AI-Driven Future
The tools and platforms you invest in today will shape your ability to innovate and thrive in an AI-driven landscape. By focusing on foundational elements, enterprises can build intelligent contact centers that deliver exceptional customer experiences and sustainable growth.
Take the Next Step: Schedule a consultation with Cresta to explore how our technology can empower your contact center. Together, we’ll create a roadmap for AI success.
