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CX Platforms in the Age of AI

January 20, 2026

This post reflects recurring themes Donna Fluss, President of DMG Consulting LLC and Sarita Fernandes, Avaya’s VP of Product Management, are hearing in conversations with CX leaders across industries. Donna and Sarita met recently to discuss these themes and their implications for enterprises. 

AI’s potential benefits and contributions are substantial and expansive as it provides tools and intelligence that help transform and improve the customer experience (CX) – enabling companies to better satisfy customers and prospects while decreasing costs. But these innovations don’t eliminate the need for human agents, contact center infrastructure, or CRM solutions. Contact center infrastructure remains the core platform for CX organizations and will for the foreseeable future. AI technology is a highly complementary set of tools that orchestrates and elevates the performance of a CX organization, but it’s not a replacement for the foundational platforms that power these operating environments. 

When transforming a CX organization, the question isn’t ‘AI or a contact center platform’ — it’s how to apply AI on top of a modern, scalable platform. Today’s contact center solutions operate as flexible high-performance environments that come with an AI orchestration layer, a CPaaS integration layer, and a unified data foundation that supports openness, integration, interoperability, and continued innovation. Organizations must invest in platforms that meet their current business requirements while positioning them to leverage innovation as it emerges in a rapidly evolving world. To achieve this, they need:

  • A highly reliable, secure, and scalable omnichannel platform – a modern CX platform must be cloud‑native and maintain full context as customers move across voice, digital, and video channels, ensuring a seamless experience regardless of how customers choose to engage. It needs enterprise-grade reliability with a 99.999% uptime guarantee, full redundancy, and failover to maintain service continuity during peak demand or unexpected outages. The platform must meet stringent security and compliance requirements, including GDRP, HIPAA, PCI-DSS, SOC2, EU AI Act (2024), and the European Accessibility Act, and be adaptable as new regulations are enacted. It should deliver elastic scalability, global reach, and cost efficiencies. 
  • An open AI orchestration layer and hub – operates as an open coordination hub that connects to multiple AI providers and dynamically routes between proprietary and third‑party LLMs based on complexity, performance, and cost. It should provide access to a broad range of AI technologies and solutions while orchestrating how human agents and bots work together. The goal is to optimize departmental performance, elevate customer satisfaction, and manage cost efficiency. 
  • Adaptive real-time intelligent routing engine – analyzes hundreds of variables in milliseconds, including customer history, current context, sentiment, complexity, available resources (human and AI), business priorities, predictive outcomes, and servicing cost – to determine the optimal routing decision for each interaction. This feature significantly improves the customer journey and employee experience. 
  • Conversational AI (CAI) self-service capabilities – utilizes transcription, GenAI, LLMs, workflow, and agentic AI to autonomously deliver intelligent self-service experiences across voice and digital channels. They are multilingual, sentiment-aware, able to access and deliver contextually relevant knowledge, generate natural conversational responses, incorporate real-time information and execute transactions and tasks. While still early in their evolution, CAI solutions are intended to continuously learn and optimize, becoming more capable and effective over time.
  • Agent augmentation tools – AI-enabled applications that enhance human-agent performance rather than replacing them with an automated bot. Key CX-related applications include real-time guidance (RTG), next-best-action (NBA), and automated post-interaction summarization. These tools support human agents with live assistance by accessing relevant historical customer information, sharing procedures and guidelines, issuing reminders to ensure compliance to policies, notifying agents of changing sentiment, troubleshooting issues as conversations unfold, and offering expert recommendations. The result is faster, more accurate first‑interaction resolution, improved customer and employee experience, and reduced average handle time.

Final Thoughts

Contact center infrastructure solutions capable of processing large volumes of interactions are the core operating platforms in CX organizations, whether deployed in the cloud or on-premise. AI technology is highly transformative, but it cannot operate on its own; its value is realized when the right capabilities are applied to the right use cases. When AI’s intelligence is combined with the processing power and operational resilience of modern contact center infrastructure, organizations achieve measurable improvements across the customer journey and meaningful gains to the bottom line. 

To hear more about these topics directly from Sarita and Donna, click here.