"... AI AND HUMAN AGENTS SHOULD BE WORKING FROM THE SAME INFORMATION. CLEAR HANDOFFS AND SHARED CONTEXT GO A LONG WAY IN KEEPING THE EXPERIENCE CONSISTENT."
CONNECTING THE CUSTOMERS
The dominant model emerging is not AI replacing agents. It is automating where possible, with humans handling what matters most. AI handles volume. Humans handle value. Complex, emotionally nuanced conversations remain firmly in human hands.
Finally, how contact centers measure success is shifting. Handle time gives way to Customer Effort Score, Net Promoter Score, and real-time sentiment as the metrics that truly reflect AI ' s impact on CX.
WHAT ARE YOUR RECOMMENDATIONS WHEN CHOOSING, DEPLOYING, AND USING INBOUND AND OUTBOUND CUSTOMER CONTACT APPLICATIONS?
SARITA FERNANDES: The biggest thing is to look at how everything works together, not just the individual tools, and to select a platform that’ s open and does not lock you into a vendor.
A lot of organizations solve for specific use cases, but the systems don’ t share context or connect well. That creates friction quickly, both for agents and customers.
Interoperability is key. Systems should be able to connect across channels, workflows, and AI models. Flexibility matters too, especially as the AI landscape continues to evolve. Supporting both private and public models helps avoid having to start over later.
Real-time context is another big factor. Applications perform better when they can understand what’ s happening in the moment and adjust. More dynamic workflows tend to handle real-world variability better than rigid ones.
It’ s also important to think about how interaction data is used. Every conversation is a signal. When that data is captured and used effectively, it helps the business make better decisions and spot trends earlier.
On the operational side, AI and human agents should be working from the same information. Clear handoffs and shared context go a long way in keeping the experience consistent.
Finally, deployment flexibility and governance still matter. Most organizations are balancing cloud and on-prem environments while meeting security and compliance requirements. The solution should support that without adding unnecessary complexity.
If those pieces are in place, it becomes much easier to build a system that can adapt and improve over time.
LISA ORFORD: The biggest mistake I see is purchasing point solutions that solve today ' s problem but create tomorrow ' s headache. If your inbound, outbound, and AI systems don ' t share the same customer data, every interaction starts from scratch. Unified data isn ' t a feature: it ' s the whole game.
Sequence your AI investments carefully. Automation works best on top of mature operations with real interaction data. If you deploy AI before you understand your contact patterns, you ' ll get low containment rates and frustrated customers. The data you collect in Year One is what makes AI actually useful in Year Two.
Finally, measure what customers experience, not just what agents do. Volume metrics tell you how your operation is running.
First contact resolution( FCR), customer effort, and loyalty tell you whether it ' s actually working. Build your evaluation framework around outcomes from the start: that ' s the only way to know if the technology is earning its keep.
"... AI AND HUMAN AGENTS SHOULD BE WORKING FROM THE SAME INFORMATION. CLEAR HANDOFFS AND SHARED CONTEXT GO A LONG WAY IN KEEPING THE EXPERIENCE CONSISTENT."
-- SARITA FERNANDES
SARIKA PRASAD: Simply choosing a platform and setting it and forgetting it is no longer enough when managing customer contact applications.
For businesses to see true success, they need to have full visibility into their contact center operations, leaning on that data to develop informed, strategic plans based on their functions or product / service lines for CX decisions and deployment. As examples:
• Organizations that typically manage more complex interactions, such as financial services, healthcare, or government, need to focus their investment and automation strategy around information security, seamless escalation, and human agent empowerment.
• Organizations in the retail space must prioritize solutions that are built for managing high-volume inquiries, quickly and effectively.
To ensure customer contact platforms continue to align with company business goals and customer expectations, I recommend conducting regular audits, gathering real-time analytics, and regularly sourcing customer feedback and agent insights.
The more data leaders have into resolution, consumer behavior, and agent experience, the more successful they will be in optimizing their contact center strategies and turning CX into a revenue driver.
Brendan Read is Editor of Contact Center Pipeline. He has been covering and working in customer service and sales and for contact center companies for most of his career. Brendan has edited and written for leading industry publications and has been an industry analyst. He also has authored and co-authored books on contact center design, customer support, and working from home. Brendan can be reached at brendan @ contactcenterpipeline. com.
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