Building Trust and Agility in the Age of Agentic AI: How Avaya Is Redefining CX for 2026 and Beyond
Imagine a customer reaching out to a brand—starting with a quick chat on the app, moving seamlessly to a voice conversation, and wrapping up with a short video walk-through—all without losing context. The interaction feels personal, natural, and effortless. Behind this fluid experience isn’t just good tech—it’s agentic AI at work, embedding trust, adaptability, and human alignment into digital intelligence.
And few leaders understand this transformation better than Sarita Fernandes, Vice President of Product Management at Avaya. With over 25 years in SaaS, cloud communications, and customer experience leadership, Fernandes has spent her career shaping the intersection of automation, people, and empathy. In this exclusive conversation with CXQuest.com, she shares how Avaya is empowering enterprises to evolve customer engagement through a practical, trust-driven AI approach.
What Is Agentic AI and Why CX Teams Need It?
Agentic AI refers to autonomous systems capable of proactive decision-making—optimizing interactions without losing alignment with brand values or customer trust.
For CX leaders, this means rethinking AI from a set of static automations to adaptive assistants that co-pilot customer engagement across roles. Fernandes explains Avaya’s vision:
“Avaya takes a practical approach to agentic AI, offering customers AI assistants that adapt in real time. These AI assistants support agents, supervisors, administrators, and other key personas within the contact center. We give customers the flexibility to use Avaya-built assistants or create their own. The biggest challenge has been striking the right balance between automation and trust. We’ve spent a lot of time developing strong guardrails and responsible AI design principles so teams feel empowered to use automation where it matters most.”
This approach bridges a crucial CX gap—how to blend AI efficiency with authentic human touch. By embedding responsible AI principles and transparency-based design, Avaya frames automation not as a replacement, but as a reinforcer of trust.
Key Insights
- Agentic AI ≠ Autonomous AI: It’s designed to collaborate, not replace.
- Guardrails build confidence: Teams adopt automation faster when trust is built in.
- Customization = Control: Enterprises can tailor assistants for real-world complexity, not one-size automation.
Common Pitfall
Over-automation without context. Many organizations deploy AI that reacts, not reasons. The result? Fragmented journeys and reduced customer confidence.
How Can CX Leaders Build Resilience and Agility?
CX agility isn’t just about speed—it’s about absorbing change smoothly, whether it’s a new AI model, regulation, or customer expectation. Fernandes emphasizes platform design as the foundation:
“We’ve intentionally built agility into Avaya Infinity™. The platform is modular and open, allowing customers to adopt new capabilities at their own pace. They can use Avaya’s agentic AI or seamlessly integrate their own AI models, tools, and orchestration engines. Our backward-compatible approach lets customers modernize without business disruption. We’ve found this flexibility empowers teams to adapt quickly to shifting expectations, evolving regulations, and changing market conditions.”
Avaya’s modular architecture is a strategic differentiator. Rather than forcing change from top-down transformations, Infinity supports incremental innovation—letting organizations evolve while maintaining operational stability.
Framework for CX Agility
| Framework Element | Description | Example in Action |
|---|---|---|
| Modularity | Break large systems into flexible components. | Integrating a new AI chatbot without overhauling routing infrastructure. |
| Openness | Allow third-party models and tools. | Plugging enterprise-specific LLMs for personalization. |
| Backward Compatibility | Prevent disruption during upgrades. | Running legacy CRM integrations alongside new AI workflows. |
| Iterative Delivery | Deploy new CX capabilities in sprints. | Testing voice biometrics with select customer groups. |
Key Insights
- Operational continuity enables transformation.
- Agility thrives on interoperability, not isolation.
- Teams need freedom to experiment, backed by platform safety nets.
When organizations treat agility as design DNA rather than a downstream adjustment, resilience becomes measurable—reduced churn, faster onboarding, and higher adoption of AI-driven innovation.
Why Multimodal CX Is the Next Competitive Frontier
Customers now expect every brand conversation to feel fluid—moving between chat, call, and video as naturally as switching apps. According to Fernandes, this is no longer optional:
“At Avaya, we see multimodal support quickly becoming a core expectation. Built to be a unified platform, Avaya Infinity™ enables customers to move seamlessly between text, voice, video, and visual interactions without losing context. Because the platform is open, enterprises can also integrate their own AI models or multimodal tools to personalize the experience. All of this helps create interactions that feel more natural and fluid, preparing customers for the future of multimodal CX.”
What Multimodal Means for 2026 and Beyond
- Unified context: No need to reintroduce issues when switching channels.
- Accessibility: Customers choose the medium comfortable for them.
- Hybrid experiences: Visual troubleshooting, voice guidance, and text summarization combined.
Agentic AI in CX: Key Insight
Multimodal design transforms omnichannel from being a presence strategy (available on many channels) into an experience strategy (coherent across channels).
Common Pitfall
Siloed channel analytics. Without shared data models, multimodal interactions lose continuity, frustrating both agents and customers.
Building Trust at the Heart of CX Transformation
Whether it’s agentic AI or multimodal engagement, the common thread running through Avaya’s vision is trust. Trust in automation. Trust in adaptability. Above all, trust in data use and customer transparency.
This aligns with a growing industry realization: CX innovation must be auditable, explainable, and human-led. As enterprises move deeper into AI-driven service orchestration, design ethics become as important as speed or accuracy.
Trust Framework Essentials
- Transparency: Explain AI decisions to both users and teams.
- Consent: Offer customers clear control over AI-driven personalization.
- Auditability: Track how and when AI influences interactions.
- Guardrails: Protect human oversight and emotional intelligence in automation.
This “trust-first” mindset turns technology adoption from a risk-management exercise into a relationship-enabling strategy.
About Sarita Fernandes
Sarita Fernandes is Vice President of Product Management at Avaya, an enterprise software leader that helps organizations and government agencies forge unbreakable connections. With 25+ years in SaaS, cloud communications, and contact center innovation, she has held leadership roles at Verint, Vonage, NewVoiceMedia, Lifesize, and Calix. Her work continues to shape the practical, human-centric evolution of AI and CX technology.
Explore more at Avaya.com.
Frequently Asked Questions
1. How does agentic AI differ from traditional AI in CX?
Agentic AI autonomously adapts responses based on context and goals, while traditional AI follows predefined rules. It’s collaborative, not reactive.
2. Can agentic AI replace human agents in contact centers?
No. It enhances human capability rather than replacing it by providing insights, automation, and proactive suggestions that save time.
3. What is backward compatibility, and why is it vital for CX platforms?
It ensures new features integrate smoothly with existing systems, reducing disruption during modernization efforts.
4. How can enterprises avoid over-automation while adopting AI?
Set human oversight checkpoints, apply responsible AI principles, and define value-driven automation boundaries before deployment.
5. What are the business outcomes of multimodal CX?
Improved CSAT, reduced handling times, and stronger brand trust through seamless, context-rich interactions across channels.
6. What skills should CX leaders develop for an AI-driven future?
Data literacy, change management, ethical design understanding, and cross-functional collaboration between tech, marketing, and service teams.
Actionable Takeaways for CX Leaders
- Adopt a modular architecture that supports gradual AI expansion instead of large-scale disruptions.
- Define AI guardrails early to promote responsible implementation and internal confidence.
- Build trust dashboards tracking transparency, explainability, and automation outcomes.
- Invest in multimodal orchestration tools that unify context across channels.
- Co-design AI workflows with agents, ensuring usability and ownership.
- Prioritize data interoperability for unified analytics across legacy and new systems.
- Conduct quarterly AI ethics audits to ensure compliance and customer trust.
- Cultivate agility rituals—retrospectives, innovation sprints, and feedback loops—to sustain momentum.
