With generative AI and ML systems becoming involved in more customer touchpoints, responsible AI isn’t just a governance checkbox but a business essential, with CX Network research finding that 43 percent of consumers expressed concern around AI ethics.

This session pairs insights from retail and regulated healthcare ecosystems to illuminate how responsible AI strategies differ by context, from mitigating bias in recommendation systems to building compliant, customer-centric data governance strategies. Our speakers will explore where bias creeps in, how to define appropriate guardrails, and why responsible design must be embedded into product and operations from the beginning.

Attendees will learn:

• What responsible AI really means in practice beyond high level principles.
• Approaches for embedding compliance and transparency into customer facing systems.
• How to balance rapid innovation with risk mitigation in diverse industry contexts.

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Customer expectations have fundamentally shifted. CX Network research finds that two thirds of practitioners expect demand for instant, convenient service to dominate strategy in 2026 - yet automation alone doesn't build loyalty.

The brands winning on customer experience aren't choosing between scale and quality. They're delivering both.

Voice is the fastest path from customer intent to resolution. Speaking is the richest and most natural way humans communicate - and AI can now not only understand language, but respond with the tone, empathy, and precision that customers expect from the best human agents.

In this session, ElevenLabs will use real-world deployments at Klarna, Revolut, and Deliveroo to show where voice AI is driving measurable impact - and what it takes to deploy successfully at scale. They will cover how these brands achieved faster resolution times and better outcomes for millions of customers with voice agents.

Attendees will learn:

• Why voice is the fastest path from customer intent to resolution, and how to build a roadmap that balances automation with loyalty-building experiences
• How Klarna, Revolut, and Deliveroo deployed voice AI to achieve faster resolution times and measurably better customer outcomes
• Where voice AI delivers the greatest impact across the customer journey, and the deployment decisions that determine whether it scales or stalls

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While video has long been recognized as a powerful engagement tool for CX, AI is now fundamentally transforming – and accelerating – how video content can be created and deployed across the customer journey. With the right toolset and approach, CX teams can increase the volume of videos produced ten-fold and reduce cost-per-video by 36 percent, all without sacrificing quality.

This session will explore how AI-enriched video is reshaping CX strategies in 2026, encouraging deeper customer engagement while improving operational efficiency. We’ll demonstrate practical applications of AI-enriched video that CX teams can implement today, showing how AI enables faster content creation that can be paired with deeper personalization, and scalable delivery of consistent, on-brand experiences.

• Key enterprise video use cases where video + personalization creates the most significant impact on CX and operational efficiency.
• Specific AI capabilities that are transforming the CX content engine, such as document-to-video and AI avatars, enabling teams to create professional videos at scale while reducing production time and maintaining quality.
• Practical approaches with real-world examples of AI-enriched videos for different real-world CX scenarios.

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Join PumpCX’s CEO, Hamish Graham, and VP of Business Development, Trent Evans, for a deep dive into the single most overlooked assurance gap companies are encountering after AI-driven CX deployments.

Voice bots and agentic workflows often perform well in controlled testing environments, and then behave differently when deployed into live contact center ecosystems. For complex journeys involving multiple platforms, policies, and handoffs, functional unit testing of individual components does not necessarily guarantee successful customer outcomes in production. Nor does it provide verifiable evidence that AI-led interactions are safe, compliant, and controlled.

In this session, we’ll explore the pitfalls of treating AI testing as a one-time activity, and why continuous validation is emerging as the industry standard for maintaining confidence as models evolve, journeys change, and systems are updated.

Attendees will learn:

• What often-overlooked factors can cause AI-driven customer journeys to behave differently in live customer environments than in controlled testing.
• Why validating customer journeys before and after deployment is becoming a critical capability for safely scaling AI in customer experience.
• Practical approaches for deploying AI-driven CX with confidence across complex multi-vendor environments.

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At the world’s largest online retailer, agentic AI isn’t a buzzword, it is a reality. In this case study, Rajesh Sura, Head of Data Engineering and Analytics for North America Stores at Amazon, will break down how he and his team moved beyond rule-based automation to build a multi-agent orchestration framework to transform vendor experience.

We will look at the conversational BI agents and fully autonomous dispute-resolution agents that proactively spot and resolve issues with zero human intervention resulting in faster resolution times, personalized recommendations for vendors and hundreds of thousands of hours of work saved for internal teams.

We will hear how Rajesh and his team designed an explainable agentic ecosystem, keeping humans in the loop at critical points. We will also unpack how AI can identify shipping inefficiencies and personalized marketing strategies, allowing vendors to act with a single approval click.

Attendees will learn:

• How to design and implement multiple AI agents to solve complex, high-volume challenges with minimal human intervention.
• Ways to combine personalization at scale with explainable AI to secure trust and adoption.
• The governance and access-control considerations organizations must consider before deploying agentic AI.

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